Internet Term used to capture both and World Wide Web (WWW) applications.
|
|
- Cecil Cobb
- 7 years ago
- Views:
Transcription
1 Web-Based Surveys R. Michael Alvarez and Carla VanBeselaere 1 California Institute of Technology I. Introduction II. Methodological Issues III. Web-Survey Typology IV. Developing Web-Surveys Glossary Framing or Priming Activating different mental constructs to see how they influence responses. In surveys this usually involves altering question wording or the information accompanying questions. Internet Term used to capture both and World Wide Web (WWW) applications. random digit dialing (RDD) A method of number selection that includes all possible telephone numbers including unlisted numbers and new numbers. RDD often uses information about which interchanges will likely contain residential numbers as a basis for selecting a sample of telephone numbers. sample The units from the population that are drawn from the sampling frame to be included in the survey. sampling frame A list of sampling units from which the sample can be selected. 1 Support for our research on Internet surveys has come from the IBM Corporation through their University Matching Grants Program, from the California Institute of Technology, and from the USC-Caltech Center for the Study of Law and Politics. We acknowledge the contributions of Robert Sherman to our research, and the assistance of Catherine Wilson and Karen Kerbs. 1
2 sampling units Groupings of the target population that cover the whole population but do not overlap every element of the population belongs to one and only one sampling unit. self-completion survey A survey completed by the respondent without assistance from an interviewer. target population The entire set of units (whether individuals, households, organizations, institutions, geographic entities, or others) for which the researcher wants to make generalizations or inferences. World Wide Web (WWW or Web) A system of extensively interlinked hypertext documents. The World Wide Web (WWW) or Internet has recently been recognized as a valuable instrument for conducting surveys (Dillman 2000). Low costs, rapid turn around, access to a vast geographically diverse pool of potential respondents, and the ability to present complex graphical material make the Web appealing as a new survey mode. While this new survey mode may offer many opportunities, its strengths and weaknesses are still being studied. As the Internet develops especially as Internet access widens to include a more representative cross-section of the adult population the applications for Webbased surveying are likely to flourish. The future of Web-based surveys will undoubtedly be hotly debated but an understanding of the fundamentals of Internet surveying is a prerequisite for such a debate. 2
3 I. Introduction A. What are Web-Based Surveys? Web-based surveys are not a new creation. Rather, the World Wide Web simply provides a new medium through which survey data can be collected. Surveys published on the Web can be accessed by potential respondents who have a computer with an Internet connection and Web-browsing software. A variety of computer programs and languages, such as the Hypertext Markup Language (HTML), are used to present surveys and collect data. To participate in these surveys, respondents are usually required to visit a particular Web-address or universal resource locator (URL). Once respondents complete the survey and submit their responses, data is transmitted electronically to the researcher for analysis. Early Internet surveys were generally distributed by but, while facilitates the distribution of surveys, responses cannot be automatically submitted to a database. This essay focuses primarily on Web-based surveys since this new survey mode appears to offer more opportunities that surveys. The flexibility of HTML and related computer languages allows the deployment of diverse types of surveys. Exploiting the graphical capabilities of Web-browsers, such as Internet Explorer or Netscape, Web-based surveys can incorporate images and multimedia material. Web-based surveys can also be programmed to provide respondents a tailored experience. Like other types of computer assisted surveys, Web-based surveys can be designed to automatically skip questions that are irrelevant based on responses to previous questions or to randomize the order of questions or response options. A key feature of Web-based surveys is that they do not require interviewers. Like mail surveys, Internet surveys are self-administered. Respondents complete the survey at their leisure and transmit their responses electronically. This process makes Internet surveying relatively low cost, reduces data entry requirements, eliminates the possibility of transcription or data entry errors, and greatly accelerates survey administration. As a result Internet surveys are proliferating at an amazing rate. In 1999 Kaye and Johnson 3
4 identified over 2,000 Web-based surveys using an informal yahoo.com search. B. How and Where Web-Surveys are Used Web-based surveys have been used for a variety of different purposes; these surveys have been used to collect opinion data, demographic information, and purchasing behaviour, to name but a few. Web-based surveys are used by academics, market researchers, corporations, the media, and many others. Topics range from political polls to surveys of illicit drug dealing behaviour. Web-based surveys are used for marketing purposes for public opinion polling and to study the behaviour and beliefs of Internet users. Internet searches reveal a large number of companies that offer Web-based survey services and software. Existing research companies expanded their services by offering Internet based surveys while other new companies entered the field offering unique Webbased technology for surveys. Academic institutions are also using the Internet to contact respondents. Some prominent Internet survey groups include Harris Interactive, Knowledge Networks, the Internet Survey of American Opinion, the GVU WWW User survey, and Greenfield On-line. Although coverage error and non-response bias are a concern for Web-based surveys, several surveys have performed well on the objective measure of election forecasting; in the 2000 presidential election, the Harris Interactive poll did better at predicting state level presidential votes than similar telephone surveys (Berrens et al. 2003). Since Web-based surveys generate a large number of responses and can be easily programmed to provide respondents a tailored experience, they are optimal venues for testing how the wording of questions affects responses. By providing different respondents with different question wording or accompanying text, researchers can examine how framing or priming affects responses. Rapid turn around, low costs and high response volumes makes Web-based surveys an attractive medium for this type of survey experimentation. Web-based surveys also promise to democratize the process of survey data collection: 4
5 Not only can researchers get access to undreamed numbers of respondents at dramatically lower costs than traditional methods, but members of the general population too can put survey questions on dedicated sites offering free services and collect data from potentially thousands of people (Couper 2000: ). Given the popularity and accessibility of Web-surveying, it is important that we understand the fundamental issues related to Internet surveying. Not all Web-surveys are equal. The validity and value of Web-surveys will depend on how the survey is designed and implemented. Recognizing the strengths and weaknesses of Internet surveys will ensure that Web-surveys are designed appropriately and that results are considered carefully. C. Article Overview This article examines some of the fundamental issues about using the Internet as a survey tool. In addition to considering the practical issues involved in implementing Web-based surveys, this paper presents an overview of the different types of Web-based surveys. Section II examines methodological issues such as coverage and sampling. In an attempt to facilitate the task of evaluating and improving Web-surveys, a typology of Web-surveys is offered in Section III. Section IV contains some final details about implementing Websurveys. II. Methodological Issues While the Internet or WWW offers a new and exciting mechanism for the collection of survey data, this new survey mode faces many important methodological issues. The validity of survey results depends on how well the survey is designed and the techniques used to obtain the sample. Cochran (1977) lists the following principle steps that should be considered in any sample survey: Determine the objectives of the survey. Define the population about which information is wanted (target population). 5
6 Determine the relevant data to be collected. Specify the degree of precision wanted from the sample. Determine format of the survey to be implemented. Define the sampling frame from which a sample is to be drawn. Divide the population into sampling units and select a sample from among these units. Organize the survey administration Summarize and analyze the data. Careful implementation of these steps helps to ensure that survey results are valid and generalizable. In the context of Internet surveying, there are three components of survey sampling that may introduce problems. These issues are coverage error, sampling issues and non-responses bias. Recognizing the concerns surrounding these issues, adjustments in survey objectives and administration may be necessary. A. Coverage Error Coverage error is the deviation between the sampling frame and the target population. The degree to which coverage error is an issue depends on the population about which we wish to make general statements. For example, if we are interested in sampling from a population for whom we have addresses there is no coverage error because we can use the list of addresses as the sampling frame. If, however, we are interested in surveying a large group, such as all eligible voters in the United States, the coverage error is a significant concern because not all voters have Internet access nor is there a list of addresses for this population. In order to develop an appropriate sampling frame for Web-based surveys we must be able to identify the units to include. In some cases, the population and sampling frame 6
7 are known with certainty: examples of these types of situations usually involve smaller populations, like groups with known addresses, visitors to particular Web-sites, or the like. In these circumstances it is possible to easily identify all members of the target population and ensure that they have a positive probability of being sampled. Unfortunately, there are many circumstances where the population is not known with certainty, especially if we are interested in studying large populations like the universe of Americans adults. For many large populations of interest a simple list for the sampling frame does not exist. For example, there is no general list of addresses for the adult American population. Web-based surveys of large groups, like all eligible voters, is further complicated by the fact that not all potential respondents have computers or Internet access. According to NUA Ltd. ( many online/index.html), in February 2002, approximately million people (8.96% of the population) had Internet access throughout the world. Internet penetration is the highest in North America; in the U.S. approximately million people (58.5% of the population) had Internet access. While Internet penetration rates continue to grow, we are a long way from being able to access all potential respondents if the target population is the entire American population. B. Sampling Despite the difficulties in developing a complete sampling frame of Internet users, researchers have pursued a variety of ways to obtain Internet survey responses. Since no established methods exist for recruiting survey respondents, a variety of approaches have been considered to obtain Web-based survey samples. Couper (2000) identifies two basic approaches to Web-survey recruitment: probability and non-probability surveys. Probability approaches involve the researcher identifying the population, developing a sampling frame and using the sampling frame to generate a random research sample. Using this approach, the probability that any unit of the population will be sampled is known and thus the sampling error can be calculated. Probability-based Web-surveys 7
8 can be used to make generalizations about the population upon which they are based. Two basic approaches have arisen to conduct probability-based surveying on the Web. One is to restrict the population to only Internet users and to devise methods of randomly selecting Internet users into a sampling frame. The second is to use other approaches to contact a broader spectrum of potential respondents (i.e., telephone) and then recruit them into a pool or panel of potential survey respondents. The other types of Internet surveys, based on non-probability approaches, are probably the most ubiquitous surveys on the Internet. These surveys make no attempt to identify the sampling frame or randomly select respondents. These types of Web-survey are frequently used when it is difficult to identify members of the target population or contact a probabilistic sample from the population. Any inferences made about population parameters from non-probability surveys are potentially problematic. For surveys of the general American population, probability-based sampling over the Internet is complicated. While the same problem arose in telephone surveying, the development of technologies like random digit dialing (RDD) enabled researchers to approximate random samples of the American population. Assuming that most households have a telephone and given that RDD techniques ensure that each residential phone number has an equal probability of being drawn, RDD generates a random sample of potential respondents. Unfortunately, this method does not generalize directly to the Internet. First, over 95% of households have telephones but less than 50% of households have Internet access (U.S. Department of Commerce 2000). In addition, since addresses (the Web equivalent of telephone numbers) involve more than simple seven-digit numerical combinations, it is extremely difficult to randomly generate valid addresses. Furthermore, even if random generation of addresses were possible, sending large quantities of unsolicited (spam) is frowned upon. As a result, contacting a random sample from a large population for which no contact list exists is difficult and may not generate representative samples even if we condition on having Internet access. Until Internet access becomes universal and all-inclusive directories are devel- 8
9 oped, obtaining probability samples using only Web-based tools will be difficult. To overcome this many researchers have implemented multi-mode surveys. Respondents are often contacted by telephone and asked to participate in a Web-based survey. Knowledge Networks claims to have solved the problem of sample representativeness by providing pre-recruited pools of survey respondents Internet access in exchange for completing regular Web-based surveys. Alternatively, researchers have used telephone surveys to supplement Web-based surveys. For example, Harris Interactive undertakes a telephone survey in order to develop appropriate weights for their Web-based survey responses. C. Non-Response Bias The methodological concerns do not end once a sample of potential respondents have been contacted. Error or non-response bias may also be introduced because some members of the selected sample are unable or unwilling to complete the survey. The extent of bias depends on both the incidence of non-response and on how non-respondents differ from respondents on variables of interest. The effect of non-response is to confound the behavioural parameters of interest with parameters that determine response. Nonresponse bias is not unique to Internet surveys but the potential problem is quite severe for Web-based surveys that have low response rates and non-random recruitment procedures. Web-survey non-response might be aggravated because potential respondents encounter technological difficulties. Internet respondents need to have basic literacy skills, know how to surf the Web, be able to use the mouse to select response options from menus, and know how to type answers in the fields provided. Furthermore, technological hurdles, such as browser incompatibility and slow Internet connections, will influence whether a potential respondent completes a survey (Couper et al. 2001). Since Internet access tends to be correlated with demographic characteristics such as income and age, Internet survey data will provide biased results if these demographics affect the variables of interest. Several methods exist to account for selection bias in survey samples but these cor- 9
10 rections are complicated by the fact that Web-based surveys provide very little information about non-respondents. Techniques such as propensity weighting or other simple weighting schemes may be useful in improving the representativeness of Internet survey samples. Simple weighting schemes may be useful in minimizing these biases and errors if there is a strong relationship between the weighting variable and the data in the survey. Supplementing Web-surveys with telephone surveys can be used to develop appropriate weighting schemes. While non-response bias is a significant concern for Internet surveys, recent research makes apparent the fact that traditional methodologies, like RDD telephone surveys, may also be problematic. Alvarez et al. (2003) report data from a telephone survey in which they began with 13,095 residential telephone numbers to obtain 1,500 complete interviews. 3,792 of these phone numbers were bad in some way, 5,479 produced no answer or compete interview, and 1,469 produced a valid contact but the survey interview was refused (Alvarez et al. 2003, Table 1). As few telephone survey studies report statistics like these, it is impossible to characterize the extent to which contemporary telephone survey techniques produce representative samples. The Alvarez et al. evidence suggests that RDD techniques do not necessarily provide truly random samples. Obtaining random samples from large populations may be difficult over the Internet but telephone surveys are not a panacea. III. Web-Survey Typology A. Probability vs. Non-Probability Surveys As discussed above, Web-surveys can be classified based on how they generate respondent samples. The two basic ways of recruiting respondents involve probability or nonprobability approaches to Web-surveying. Cooper (2000) identifies at least four different types of probability-based Web-surveys: 1. Intercept-based surveys of visitors to particular Web-sites 10
11 2. Known lists 3. Pre-recruited panels 4. Mixed-mode survey designs The first, the intercept-based approach, is based on interview techniques used in exit poll surveys or many types of market research. With a sampling frame being all visitors or users of a particular Web-site, the sample is some randomly selected set of visitors who are asked to participate in some form of survey. Known lists are a second form of probability-based Web-survey. When the population is one that has universal Internet access and for which a directory of addresses is available, Web-based surveys can be extremely useful; student, university faculty, or employee surveys are examples of known list surveys. These two types of surveys can minimize sampling and coverage errors. The remaining approaches for probability-based Web-surveys are based on already having a probability sample and then using this sample to obtain Web-survey subjects. In the pre-recruited panel approach, researchers use other techniques of probability sampling, like RDD telephone surveys, to recruit Web-survey samples; such an approach works well for studies of the Internet-using population if respondents with Internet access are willing to provide their addresses and participate in subsequent Web-surveys. Knowledge Networks ( extended this concept by offering a random sample of respondents Internet access in exchange for a commitment to participate in on-going Web-based surveys. Finally, mixed-mode approaches simply offer Web-surveys as one of a multitude of modes for their participants to use (in addition to telephone or other modes). Non-probability Web-surveys are probably the most ubiquitous surveys on the Internet. There are three types of non-probability Web-surveys identified by Couper (2000): 1. Entertainment surveys 2. Self-selected surveys 11
12 3. Volunteer survey panels The first, entertainment surveys, are found all over the Internet. Generally they are not intended for scientific surveying, but for the entertainment of visitors to Web-sites. Selfselected surveys are those on the Internet that give visitors to a Web-site the opportunity to participate in a survey; thus, only visitors to the site are possible subjects and only if they actively initiate the interview. The third type of non-probability Web-survey are volunteer survey panels, where respondents are recruited on the Internet through advertisements of various types. Harris Interactive ( and Greenfield Online ( are perhaps the best known volunteer panels, but the technique is used by many other survey researchers. Volunteer panels require that prospective respondents go to a particular Web-site and provide some information about themselves (including their address). This data is then maintained in a database from which respondents can be sampled for participation in subsequent Web-surveys. Although volunteer panels are not based on probability sampling they are more likely than the other non-probability surveys to attract a representative sample. Non-probability Internet surveys are not based on rigorous sampling procedures, raising concerns about the validity of inferences drawn from them. However, non-probability Internet survey samples can and are being used in situations where researchers desire to exploit within-sample variance in a situation where statistical power can be maximized. For example, Internet survey samples can be used to examine priming or framing, especially studies that might involve graphical or multi-media materials. In such designs, thousands or tens of thousands of subjects might be included in a potential study and, as long as these subjects are assigned to control and experimental groups using some type of probability assignment protocol, this could produce powerful experimental results. B. Web-Survey Formats Examining the different Web-survey formats is also enlightening. While Web-surveys involve many different topics, there are only two main formats for presenting a Web- 12
13 survey: interactively or passively. These two formats are aesthetically different and have distinct advantages and disadvantages. Figure 1 contains an example of a typical interactive survey. As illustrated in this figure, interactive surveys are presented screen-by-screen. By clicking on a button, like the to continue button in Figure 1, respondents can go to a new question on a new screen. This allows the data from the question to immediately be electronically transmitted to the surveyor ensuring that data from partially completed surveys is maintained. However, this format may make it difficult for respondents to review and correct their answers. Interactive surveys can also automatically skip questions which are determined to be irrelevant to the respondents based on how they answer previous questions. For example, if respondents indicate that they do not have children, all subsequent questions related to children can be automatically skipped. A drawback of this design is that respondents do not see the survey in its entirety and therefore cannot easily determine its length. To compensate, a progress indicator can be used to inform the respondent how much of the survey remains to be completed. Another difficulty with interactive surveys is that they may require special software, such as java, potentially making it difficult for respondents with older, less powerful computers and Web-browsers to respond. (Figure 1 about here - Example of Interactive Survey) Passive survey designs involve presenting the entire survey at once. Figure 2 displays the first part of a passive survey. The bar on the right hand side of this figure indicates that respondents can scroll down on the page to view the rest of the survey. The data from passive surveys is transmitted once the respondent has completed all questions and clicked a submit button. An advantage of passive surveys is that respondents can easily browse through questions and review their responses before submitting. These types of Web-surveys are also easy to produce and easy to access so technical difficulties are less likely. (Figure 2 about here - Example of Passive Survey) In addition to these two basic formats, the appearance of a Web-based survey also de- 13
14 pends on how question response options are presented. There are four distinctly different ways to present response options: drop-down boxes, radio dials, check boxes, and openended boxes. Figure 1 contains an example of radio dials while Figure 2 illustrates both open-ended boxes and drop-down boxes. Drop-down boxes appear in the questionnaire as a box with a downward pointing arrow clicking on this arrow displays the list of response options and allows respondents to select from the list provided. Drop-down boxes are convenient for long lists of items since the response options are hidden. Radio dials, on the other hand, display all the responses options and require the respondent to click in the circle corresponding to their choice. Both drop-down boxes and radio dials are usually used when only one response must be selected from among the options provided. When respondents are allowed to select more than one option from a list, check boxes are the appropriate question format respondents click on all the boxes that correspond to their answers. Finally, open-ended boxes allow respondents to type their responses in the space provided. As with other survey formats, open-ended questions boxes can be useful when the associated question does not have responses that can be conveniently listed. IV. Developing Web-Surveys A. Respondents Web-based surveys are only useful if they actually generate data, thus recruiting respondents is a priority. As discussed in the section on Web-survey typology, there are many different ways to recruit subjects. The choice of recruitment method will of course depend on the objectives of the survey. If the target population can be identified and easily contacted then producing probability-based Web-surveys should be feasible. If, however, the intended target population is not well defined or readily contactable over the Internet, non-probability respondent recruitment methods may be necessary. Inferences made about population parameters from non-probability surveys are potentially problematic although several techniques have been proposed to improve the representativeness of Internet surveys. 14
15 Alvarez et al. (2003) discuss two prominent methods for recruiting respondents over the Internet. The first involves Web advertisements. Advertisements on various Web-sites or newsgroups encouraging people to complete the Web-survey is a fairly effective way of obtaining a large non-probability sample of respondents. Another method to recruit respondents is through subscription or co-registration procedures. This involves asking individuals who registering for another service whether they would like to provide their address and participate in Internet surveys. Once respondents provide their addresses, they can be contacted by to participate in Web-based surveys. B. Web-Based Survey Panels Because recruiting respondents over the Internet can be somewhat complicated, survey panels are popular. Rather than asking respondents to complete a single survey, Webbased survey panels recruit subjects to participate in a series of surveys. In order to obtain probability-based subjects, potential respondents are often initially contacted by telephone. Once respondents agree to participate in a survey panel, they are contacted by when they are required to complete a new survey. Using panels, researchers can draw samples from the registered respondents in order to undertake studies of specific sub-populations. Knowledge Networks claims that their Web-based survey panels is particularly effective for market research (Knowledge Networks 2002). Panels also offer the opportunity to examine temporal changes in respondent behavior and beliefs. Researchers are currently studying the long term effectiveness of Web-survey panels. Although the concept is relatively new, studies to date do not indicate that extended participation in Internet panels affects respondent behaviour. However, preliminary data indicates that response rates do tend to decline with panel tenure. A significant problem for many Internet panels is that participants are frequently unreachable by because they have changed addresses or there are technical problems. These issues need to be continually examined especially for long-standing panels. 15
16 C. Creating the Survey An advantage of Web-based surveys is that they are relatively easy to conduct. All that is needed is a Web-site and some basic Web programming skills. Many surveys are created simply using Hypertext Markup Language (HTML); there are dozens of HTML editors available and they are becoming increasingly sophisticated and easy to use. Data from surveys can be captured either by programming the form to the data to a specified address or through a common gateway interface (CGI) script. Several HTML development packages automate the process of developing CGI scripts necessary to capture data from HTML forms. Internet survey companies have even developed computer programs that automatically create surveys. Despite the fact that Web-based surveys are easy to implement, their effective use requires an understanding of the methodological issues presented above. While Websurveys have many potential uses, making general statements about large populations based on Internet survey results is currently problematic. The Web opens up a whole new realm of survey possibilities but it is important to evaluate surveys based on the fundamental criteria outlined in this article. Bibliography Alvarez, R. M., Sherman, R. P., and VanBeselaere, C. E. (2003). Subject Acquisition for Web-Based Surveys. Political Analysis forthcoming. Berrens, R.P., A. K. Bohara, H. Jenkins-Smith, C. Silva, and D. L. Weimer. (2003). The Advent of Internet Surveys for Political Research: A Comparison of Telephone and Internet Samples. Political Analysis forthcoming. Cochran, W. (1977). Sampling Techniques, (3rd edition.) John Wiley and Sons, New York. 16
17 Couper, Mick P. (2000). Web Surveys: A Review of Issues and Approaches. Public Opinion Quarterly 64, Couper, Mick P., Traugott, Michael W., and Lamias, Mark J. (2001). Web Survey Design and Administration. Public Opinion Quarterly 65, Dillman, Don A. (2000). Mail and Internet Surveys: The Tailored Design Method, 2nd edition. John Wiley and Sons, New York. Kaye, B. K., and Johnson, T. J. (1999). Research Methodology: Taming the Cyber Frontier. Social Science, Computer Review 17, Knowledge Networks. (2002). Decoding the Consumer Genome. Soloman, David J. (2001). Conducting web-based surveys. Practical Assessment, Research and Evaluation Vol. 7 U.S. Department of Commerce. (2000). Falling Through the Net: Toward Digital Inclusion. 17
18 Figure 1. Example of Interactive Style Web-Survey Figure 2. Example of Passive Style Web-Survey 18
19 Figure 1: Example of Interactive Style Web-Survey 19
20 Figure 2: Example of Passive Style Web-Survey 20
Internet Surveys. Examples
Web material accompanying The International Handbook of Survey Methodology Chapter 14 Internet Surveys Katja Lozar Manfreda Vasja Vehovar University of Ljubljana Examples Below follow examples and more
More informationTHE FUTURE OF INTERNET-BASED SURVEY METHODS
Chapter Seven CONCLUSIONS In this chapter, we offer some concluding thoughts on the future of Internet-based surveys, the issues surrounding the use of e-mail and the Web for research surveys, and certain
More informationChapter 8: Quantitative Sampling
Chapter 8: Quantitative Sampling I. Introduction to Sampling a. The primary goal of sampling is to get a representative sample, or a small collection of units or cases from a much larger collection or
More informationSampling Methods for Web and E-mail Surveys
11 Sampling Methods for Web and E-mail Surveys Ronald D. Fricker, Jr ABSTRACT This chapter is a comprehensive overview of sampling methods for web and e-mail ( Internetbased ) surveys. It reviews the various
More informationDescriptive Methods Ch. 6 and 7
Descriptive Methods Ch. 6 and 7 Purpose of Descriptive Research Purely descriptive research describes the characteristics or behaviors of a given population in a systematic and accurate fashion. Correlational
More informationWhy Sample? Why not study everyone? Debate about Census vs. sampling
Sampling Why Sample? Why not study everyone? Debate about Census vs. sampling Problems in Sampling? What problems do you know about? What issues are you aware of? What questions do you have? Key Sampling
More informationAsch, B., personal communications, RAND, Santa Monica, Calif., 2001.
REFERENCES American Association for Public Opinion Research, Best Practices for Survey and Public Opinion Research and Survey Practices AAPOR Condemns, May 1997. Asch, B., personal communications, RAND,
More informationSurvey Research. Classifying surveys on the basis of their scope and their focus gives four categories:
Survey Research Types of Surveys Surveys are classified according to their focus and scope (census and sample surveys) or according to the time frame for data collection (longitudinal and cross-sectional
More informationPOLLING STANDARDS. The following standards were developed by a committee of editors and reporters and should be adhered to when using poll results.
! POLLING STANDARDS June, 2006 The following standards were developed by a committee of editors and reporters and should be adhered to when using poll results. OVERVIEW Reporting on polls is no different
More informationNON-PROBABILITY SAMPLING TECHNIQUES
NON-PROBABILITY SAMPLING TECHNIQUES PRESENTED BY Name: WINNIE MUGERA Reg No: L50/62004/2013 RESEARCH METHODS LDP 603 UNIVERSITY OF NAIROBI Date: APRIL 2013 SAMPLING Sampling is the use of a subset of the
More informationSampling Methods for Online Surveys
14 Sampling Methods for Online Surveys Ronald D. Fricker, Jr INTRODUCTION In the context of conducting surveys or collecting data, sampling is the selection of a subset of a larger population to survey.
More informationBACKGROUND ON THE SURVEY PROCESS
Chapter Two BACKGROUND ON THE SURVEY PROCESS In this chapter, we present an overview of the various aspects of the research survey process. 1 We emphasize that surveying should first be thought of as a
More informationLITERATURE REVIEW OF WEB AND E-MAIL SURVEYS
Chapter Three LITERATURE REVIEW OF WEB AND E-MAIL SURVEYS In this chapter, we examine what has been written about Internet surveys in the literature, specifically Web and e-mail surveys. We address the
More informationThe Savvy Survey #13: Online Surveys 1
AEC407 1 Glenn D. Israel and Jessica L. Gouldthorpe 2 As part of the Savvy Survey Series, this publication provides Extension faculty with an overview of the process that uses email to invite participants
More informationMissing Data. A Typology Of Missing Data. Missing At Random Or Not Missing At Random
[Leeuw, Edith D. de, and Joop Hox. (2008). Missing Data. Encyclopedia of Survey Research Methods. Retrieved from http://sage-ereference.com/survey/article_n298.html] Missing Data An important indicator
More informationUsing Proxy Measures of the Survey Variables in Post-Survey Adjustments in a Transportation Survey
Using Proxy Measures of the Survey Variables in Post-Survey Adjustments in a Transportation Survey Ting Yan 1, Trivellore Raghunathan 2 1 NORC, 1155 East 60th Street, Chicago, IL, 60634 2 Institute for
More informationTypes of Error in Surveys
2 Types of Error in Surveys Surveys are designed to produce statistics about a target population. The process by which this is done rests on inferring the characteristics of the target population from
More informationJon A. Krosnick and LinChiat Chang, Ohio State University. April, 2001. Introduction
A Comparison of the Random Digit Dialing Telephone Survey Methodology with Internet Survey Methodology as Implemented by Knowledge Networks and Harris Interactive Jon A. Krosnick and LinChiat Chang, Ohio
More informationKNOWLEDGEPANEL DESIGN SUMMARY
KNOWLEDGEPANEL DESIGN SUMMARY This document was prepared at the effort and expense of GfK. No part of it may be circulated, copied, or reproduced for distribution without prior written consent. KnowledgePanel
More informationHow do we know what we know?
Research Methods Family in the News Can you identify some main debates (controversies) for your topic? Do you think the authors positions in these debates (i.e., their values) affect their presentation
More informationThe AmeriSpeak ADVANTAGE
OVERVIEW Funded and operated by NORC at the University of Chicago, AmeriSpeak TM is a probabilitybased panel (in contrast to a non-probability panel). Randomly selected households are sampled with a known,
More informationResearch Overview: Telephone versus Online Research Advantages and Pitfalls
. 26030 Highway 74, Suite A, P.O. Box 1094 Kittredge, CO 80457 P: 303.679.6300 F: 303.679.6680 info@praxigroup.net www.praxigroup.net Research Overview: Telephone versus Online Research Advantages and
More informationMixed-Mode Methods for Conducting Survey Research
Mixed-Mode Methods for Conducting Survey Research Herbert M. Baum, Ph.D.; Anna Chandonnet M.A.; Jack Fentress M.S., M.B.A.; and Colleen Rasinowich, B.A. www.datarecognitioncorp.com In November 2010 the
More informationMode and Patient-mix Adjustment of the CAHPS Hospital Survey (HCAHPS)
Mode and Patient-mix Adjustment of the CAHPS Hospital Survey (HCAHPS) April 30, 2008 Abstract A randomized Mode Experiment of 27,229 discharges from 45 hospitals was used to develop adjustments for the
More informationESOMAR 28: SurveyMonkey Audience
ESOMAR 28: SurveyMonkey Audience June 2013 28 Questions to Help Buyers of Online Samples The ESOMAR 28 was established by the European Society for Opinion and Market Research (ESOMAR), a world association
More informationIntroduction... 3. Qualitative Data Collection Methods... 7 In depth interviews... 7 Observation methods... 8 Document review... 8 Focus groups...
1 Table of Contents Introduction... 3 Quantitative Data Collection Methods... 4 Interviews... 4 Telephone interviews... 5 Face to face interviews... 5 Computer Assisted Personal Interviewing (CAPI)...
More informationReflections on Probability vs Nonprobability Sampling
Official Statistics in Honour of Daniel Thorburn, pp. 29 35 Reflections on Probability vs Nonprobability Sampling Jan Wretman 1 A few fundamental things are briefly discussed. First: What is called probability
More informationInternet Blog Usage and Political Participation Ryan Reed, University of California, Davis
Internet Blog Usage and Political Participation Ryan Reed, University of California, Davis Keywords: Internet, blog, media, participation, political knowledge Studies have been conducted which examine
More informationSampling: What is it? Quantitative Research Methods ENGL 5377 Spring 2007
Sampling: What is it? Quantitative Research Methods ENGL 5377 Spring 2007 Bobbie Latham March 8, 2007 Introduction In any research conducted, people, places, and things are studied. The opportunity to
More informationConducted for the Interactive Advertising Bureau. May 2010. Conducted by: Paul J. Lavrakas, Ph.D.
An Evaluation of Methods Used to Assess the Effectiveness of Advertising on the Internet Conducted for the Interactive Advertising Bureau May 2010 Conducted by: Paul J. Lavrakas, Ph.D. 1 Table of Contents
More informationInsurance Markets Ready or Not: Consumers Face New Health Insurance Choices. Employer-based. Insurance Premium. Contribution.
Insurance Markets Ready or Not: Consumers Face New Health Insurance Choices Introduction Not long ago, most working Californians, at least those working for large or midsize companies, could expect a standard
More informationJSM 2013 - Survey Research Methods Section
How Representative are Google Consumer Surveys?: Results from an Analysis of a Google Consumer Survey Question Relative National Level Benchmarks with Different Survey Modes and Sample Characteristics
More informationOptimising survey costs in a mixed mode environment
Optimising survey costs in a mixed mode environment Vasja Vehovar 1, Nejc Berzelak 2, Katja Lozar Manfreda 3, Eva Belak 4 1 University of Ljubljana, vasja.vehovar@fdv.uni-lj.si 2 University of Ljubljana,
More informationIntroduction to Survey Methodology. Professor Ron Fricker Naval Postgraduate School Monterey, California
Introduction to Survey Methodology Professor Ron Fricker Naval Postgraduate School Monterey, California 1 Goals for this Lecture Introduce professor and course Define what we mean by the term survey Characteristics
More informationLast Updated: 08/27/2013. Measuring Social Media for Social Change A Guide for Search for Common Ground
Last Updated: 08/27/2013 Measuring Social Media for Social Change A Guide for Search for Common Ground Table of Contents What is Social Media?... 3 Structure of Paper... 4 Social Media Data... 4 Social
More informationDigital media glossary
A Ad banner A graphic message or other media used as an advertisement. Ad impression An ad which is served to a user s browser. Ad impression ratio Click-throughs divided by ad impressions. B Banner A
More informationMarketing Research Core Body Knowledge (MRCBOK ) Learning Objectives
Fulfilling the core market research educational needs of individuals and companies worldwide Presented through a unique partnership between How to Contact Us: Phone: +1-706-542-3537 or 1-800-811-6640 (USA
More informationIntroduction to Sampling. Dr. Safaa R. Amer. Overview. for Non-Statisticians. Part II. Part I. Sample Size. Introduction.
Introduction to Sampling for Non-Statisticians Dr. Safaa R. Amer Overview Part I Part II Introduction Census or Sample Sampling Frame Probability or non-probability sample Sampling with or without replacement
More informationBitrix Site Manager 4.1. User Guide
Bitrix Site Manager 4.1 User Guide 2 Contents REGISTRATION AND AUTHORISATION...3 SITE SECTIONS...5 Creating a section...6 Changing the section properties...8 SITE PAGES...9 Creating a page...10 Editing
More informationOwnership and Usage Patterns of Cell Phones: 2000-2005
Ownership and Usage Patterns of Cell Phones: 2000-2005 Peter Tuckel, Department of Sociology, Hunter College Harry O Neill, Roper Public Affairs, NOP World Key Words: Cell phones, telephone surveys, Nonresponse
More informationOlder Adults and Social Media Social networking use among those ages 50 and older nearly doubled over the past year
Older Adults and Social Media Social networking use among those ages 50 and older nearly doubled over the past year Mary Madden, Senior Research Specialist August 27, 2010 Report URL: http://pewinternet.org/reports/2010/older-adults-and-social-media.aspx
More informationGUIDELINES FOR REVIEWING QUANTITATIVE DESCRIPTIVE STUDIES
GUIDELINES FOR REVIEWING QUANTITATIVE DESCRIPTIVE STUDIES These guidelines are intended to promote quality and consistency in CLEAR reviews of selected studies that use statistical techniques and other
More information2014 V1.0. LiveText e-portfolios
LiveText e-portfolios Table of Contents Introduction... 3 The Purposes of the e- Portfolio... 3 Student e-portfolios... 4 Academic/Reflective... 4 Professional... 5 Faculty Tenure E-Portfolios... 6 Continuous
More information14.30 Introduction to Statistical Methods in Economics Spring 2009
MIT OpenCourseWare http://ocw.mit.edu 14.30 Introduction to tatistical Methods in Economics pring 2009 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms.
More informationIntegrating Cell Phone Numbers into Random Digit-Dialed (RDD) Landline Surveys
Integrating Cell Phone Numbers into Random Digit-Dialed (RDD) Landline Surveys Martin R. Frankel 1, Michael P. Battaglia 2, Michael Link 3, and Ali H. Mokdad 3 1 Baruch College, City University of New
More informationA Guide to Understanding and Using Data for Effective Advocacy
A Guide to Understanding and Using Data for Effective Advocacy Voices For Virginia's Children Voices For V Child We encounter data constantly in our daily lives. From newspaper articles to political campaign
More informationSelf-administered Questionnaire Survey
Primary methods of survey data collection Self-administered questionnaire (SAQ) Mail Face-to-face interview Telephone interview Self-administered Questionnaire Survey 1 Steps are: a. Mail distribution
More informationSampling and Sampling Distributions
Sampling and Sampling Distributions Random Sampling A sample is a group of objects or readings taken from a population for counting or measurement. We shall distinguish between two kinds of populations
More informationResearch into Issues Surrounding Human Bones in Museums Prepared for
Research into Issues Surrounding Human Bones in Museums Prepared for 1 CONTENTS 1. OBJECTIVES & RESEARCH APPROACH 2. FINDINGS a. Visits to Museums and Archaeological Sites b. Interest in Archaeology c.
More informationAmericans and their cell phones
Americans and their cell phones Mobile devices help people solve problems and stave off boredom, but create some new challenges and annoyances Aaron Smith, Senior Research Specialist 8/15/2011 http://pewinternet.org/reports/2011/cell-phones.aspx
More informationBroadband Internet: Removing the Speed Limit for Canadian Firms
Catalogue no. 11-621-MIE No. 016 ISSN: 1707-0503 ISBN: 0-662-38099-1 Analytical Paper Analysis in Brief Broadband Internet: Removing the Speed Limit for Canadian Firms by Mark Uhrbach and Bryan van Tol
More informationUser research for information architecture projects
Donna Maurer Maadmob Interaction Design http://maadmob.com.au/ Unpublished article User research provides a vital input to information architecture projects. It helps us to understand what information
More informationThe Online Market for Health Insurance in Massachusetts and the US. Quarterly Online Insurance Index Winter 2010
The Online Market for Health Insurance in Massachusetts and the US Quarterly Online Insurance Index Winter 2010 Executive Summary This is our third quarterly online insurance index from All Web Leads and
More informationMEMORANDUM FOR THE PRESIDENT S MANAGEMENT COUNCIL. Guidance on Agency Survey and Statistical Information Collections
EXECUTIVE OFFICE OF THE PRESIDENT OFFICE OF MANAGEMENT AND BUDGET WASHINGTON, D.C. 20503 ADMINISTRATOR OFFICE OF INFORMATION AND REGULATORY AFFAIR January 20, 2006 MEMORANDUM FOR THE PRESIDENT S MANAGEMENT
More informationIPDET Module 6: Descriptive, Normative, and Impact Evaluation Designs
IPDET Module 6: Descriptive, Normative, and Impact Evaluation Designs Intervention or Policy Evaluation Questions Design Questions Elements Types Key Points Introduction What Is Evaluation Design? Connecting
More informationArticle. Can We Make Official Statistics with Self-Selection Web Surveys? by Jelke Bethlehem
Component of Statistics Canada Catalogue no. -5-X Statistics Canada s International Symposium Series: Proceedings Article Symposium 008: Data Collection: Challenges, Achievements and New Directions Can
More informationSampling Procedures Y520. Strategies for Educational Inquiry. Robert S Michael
Sampling Procedures Y520 Strategies for Educational Inquiry Robert S Michael RSMichael 2-1 Terms Population (or universe) The group to which inferences are made based on a sample drawn from the population.
More informationsee Designing Surveys by Ron Czaja and Johnny Blair for more information on surveys
SURVEYS Survey = ask the same questions of a large sample see Designing Surveys by Ron Czaja and Johnny Blair for more information on surveys Basic Survey Process: 1. Design Questionnaire 2. Design Sample
More informationWebsite Accessibility Under Title II of the ADA
Chapter 5 Website Accessibility Under Title II of the ADA In this chapter, you will learn how the nondiscrimination requirements of Title II of 1 the ADA apply to state and local government websites. Chapter
More informationUsing Social Media to Recruit Parents for Diabetes Research
International Journal of Nursing December 2014, Vol. 1, No. 2, pp. 39-47 ISSN 2373-7662 (Print) 2373-7670 (Online) Copyright The Author(s). 2014. All Rights Reserved. Published by American Research Institute
More informationDEPARTMENT OF AGRICULTURE. Food and Nutrition Service. Agency Information Collection Activities: Proposed Collection; Comment Request
This document is scheduled to be published in the Federal Register on 07/15/2014 and available online at http://federalregister.gov/a/2014-16586, and on FDsys.gov BILLING CODE: 3410-30-P DEPARTMENT OF
More informationInternet polls: New and revisited challenges
Internet polls: New and revisited challenges Claire Durand, Full professor, Department of Sociology, Université de Montréal Statistics Canada Symposium Producing reliable estimates from imperfect frames
More informationAfter you complete the survey, compare what you saw on the survey to the actual questions listed below:
Creating a Basic Survey Using Qualtrics Clayton State University has purchased a campus license to Qualtrics. Both faculty and students can use Qualtrics to create surveys that contain many different types
More informationAppendix I: Methodology
Appendix I: Methodology SSRS METHODOLOGY SSRS conducted a survey of Muslims and Jews for the Institute for Social Policy and Understanding from January 18 through January 27, 2016. The study investigated
More informationWEB SURVEYS A REVIEW OF ISSUES AND APPROACHES
WEB SURVEYS A REVIEW OF ISSUES AND APPROACHES MICK P. COUPER As we enter the twenty-first century, the Internet is having a profound effect on the survey research industry, as it is on almost every area
More informationClinical Study Design and Methods Terminology
Home College of Veterinary Medicine Washington State University WSU Faculty &Staff Page Page 1 of 5 John Gay, DVM PhD DACVPM AAHP FDIU VCS Clinical Epidemiology & Evidence-Based Medicine Glossary: Clinical
More informationKaiser Family Foundation/New York Times Survey of Chicago Residents
Kaiser Family Foundation/New York Times Survey of Chicago Residents Selected Findings May 2016 Figure 1 Majority of Chicago Residents Feel City is on the Wrong Track Do you feel things in Chicago are generally
More informationHIGH SCHOOL MASS MEDIA AND MEDIA LITERACY STANDARDS
Guidelines for Syllabus Development of Mass Media Course (1084) DRAFT 1 of 7 HIGH SCHOOL MASS MEDIA AND MEDIA LITERACY STANDARDS Students study the importance of mass media as pervasive in modern life
More informationDeterminants of Item Nonresponse to Web and Mail Respondents in Three Address-Based Mixed-Mode Surveys of the General Public
Vol. 5, no 2, 2012 www.surveypractice.org The premier e-journal resource for the public opinion and survey research community Determinants of Item Nonresponse to Web and Mail Respondents in Three Address-Based
More informationLast Updated: June 2013
Society of Petroleum Engineers Privacy Policy Statement Last Updated: June 2013 This Privacy Policy tells you about the information the Society of Petroleum Engineers (SPE) gathers about you and how we
More informationSURVEY RESEARCH RESEARCH METHODOLOGY CLASS. Lecturer : RIRI SATRIA Date : November 10, 2009
SURVEY RESEARCH RESEARCH METHODOLOGY CLASS Lecturer : RIRI SATRIA Date : November 10, 2009 DEFINITION OF SURVEY RESEARCH Survey: A method of primary data collection based on communication with a representative
More informationPolitics on Social Networking Sites
SEPTEMBER 4, 2012 Politics on Social Networking Sites Campaign and policy-related material on SNS plays a modest role in influencing most users views and political activities. Democrats and liberals are
More informationDescriptive Inferential. The First Measured Century. Statistics. Statistics. We will focus on two types of statistical applications
Introduction: Statistics, Data and Statistical Thinking The First Measured Century FREC 408 Dr. Tom Ilvento 213 Townsend Hall ilvento@udel.edu http://www.udel.edu/frec/ilvento http://www.pbs.org/fmc/index.htm
More informationInnovations and new technologies in panel research
Annette Scherpenzeel Innovations and new technologies in panel research Lausanne, October 2009 FORS Working Papers 2009-1 FORS Working Paper series The FORS Working Paper series presents findings related
More informationUsing the Shands HealthCare External Applicant Careers Portal
Using the Shands HealthCare External Applicant Careers Portal Introduction Welcome to the Shands HealthCare employment portal. We are very happy about your interest in seeking an employment opportunity
More informationSurvey Analysis Guidelines Sample Survey Analysis Plan. Survey Analysis. What will I find in this section of the toolkit?
What will I find in this section of the toolkit? Toolkit Section Introduction to the Toolkit Assessing Local Employer Needs Market Sizing Survey Development Survey Administration Survey Analysis Conducting
More informationBitrix Site Manager 4.0. Quick Start Guide to Newsletters and Subscriptions
Bitrix Site Manager 4.0 Quick Start Guide to Newsletters and Subscriptions Contents PREFACE...3 CONFIGURING THE MODULE...4 SETTING UP FOR MANUAL SENDING E-MAIL MESSAGES...6 Creating a newsletter...6 Providing
More informationGuided Reading 9 th Edition. informed consent, protection from harm, deception, confidentiality, and anonymity.
Guided Reading Educational Research: Competencies for Analysis and Applications 9th Edition EDFS 635: Educational Research Chapter 1: Introduction to Educational Research 1. List and briefly describe the
More information1Lesson 1: Overview of Web Design Concepts Objectives
1Lesson 1: Overview of Web Design Concepts Objectives By the end of this lesson, you will be able to: 1.2.1: Balance customer needs and usability with site design principles and aesthetics (includes distinguishing
More informationChapter 10: Multimedia and the Web
Understanding Computers Today and Tomorrow 12 th Edition Chapter 10: Multimedia and the Web Learning Objectives Define Web-based multimedia and list some advantages and disadvantages of using multimedia.
More informationSelf-Check and Review Chapter 1 Sections 1.1-1.2
Self-Check and Review Chapter 1 Sections 1.1-1.2 Practice True/False 1. The entire collection of individuals or objects about which information is desired is called a sample. 2. A study is an observational
More informationThe Reporting Console
Chapter 1 The Reporting Console This chapter provides a tour of the WebTrends Reporting Console and describes how you can use it to view WebTrends reports. It also provides information about how to customize
More informationCOI Research Management Summary on behalf of the Department of Health
COI Research Management Summary on behalf of the Department of Health Title: Worth Talking About Campaign Evaluation 2010 / 2011 Quantitative research conducted by TNS-BMRB COI Reference number: 114770
More informationFIDELITY APPLICANT PRIVACY AND PROTECTION NOTICE
FIDELITY APPLICANT PRIVACY AND PROTECTION NOTICE Last Updated: November 2012 FMR LLC and its affiliated entities ( Fidelity ) value your trust and are committed to the responsible management, use and protection
More informationTYPING IN ARABIC (WINDOWS XP)
TYPING IN ARABIC (WINDOWS XP) There are two steps involved in setting up your Windows XP computer for Arabic. You must first install support for right-to-left languages; then you must enable Arabic input.
More informationCommunity Life Survey Summary of web experiment findings November 2013
Community Life Survey Summary of web experiment findings November 2013 BMRB Crown copyright 2013 Contents 1. Introduction 3 2. What did we want to find out from the experiment? 4 3. What response rate
More informationInclusion and Exclusion Criteria
Inclusion and Exclusion Criteria Inclusion criteria = attributes of subjects that are essential for their selection to participate. Inclusion criteria function remove the influence of specific confounding
More informationWEB-BASED ORIGIN-DESTINATION SURVEYS: AN ANALYSIS OF RESPONDENT BEHAVIOUR
WEB-BASED ORIGIN-DESTINATION SURVEYS: AN ANALYSIS OF RESPONDENT BEHAVIOUR Pierre-Léo Bourbonnais, Ph.D. Candidate, Department of Civil, Geological and Mining Engineering, École Polytechnique de Montréal,
More informationCHAPTER 3. Research methodology
39 CHAPTER 3 Research methodology 3.1 INTRODUCTION In this chapter the research methodology used in the study is described. The geographical area where the study was conducted, the study design and the
More informationMultimode Strategies for Designing Establishment Surveys
Multimode Strategies for Designing Establishment Surveys Shelton M. Jones RTI International, 3 Cornwallis Rd., Research Triangle Park, NC, 2779 Abstract Design strategies are discussed that improve participation
More informationComparison of Research Designs Template
Comparison of Comparison of The following seven tables provide an annotated template to guide you through the comparison of research designs assignment in this course. These tables help you organize your
More informationAttachment A: Customer Follow Up Phone Survey Of Non-Respondents to the Business Case Customer Survey
Attachment A: Customer Follow Up Phone Survey Of Non-Respondents to the Business Case Customer Survey Purpose: 1. The UAC expressed concerns about the original survey being skewed due to a self-selected
More informationPURPOSE OF GRAPHS YOU ARE ABOUT TO BUILD. To explore for a relationship between the categories of two discrete variables
3 Stacked Bar Graph PURPOSE OF GRAPHS YOU ARE ABOUT TO BUILD To explore for a relationship between the categories of two discrete variables 3.1 Introduction to the Stacked Bar Graph «As with the simple
More informationAmericans and text messaging
Americans and text messaging 31% of text message users prefer texting to voice calls, and young adults stand out in their use of text messaging Aaron Smith, Senior Research Specialist 9/19/2011 http://pewinternet.org/reports/2011/cell-phone-texting-2011.aspx
More informationOnline Media Research. Peter Diem/Vienna
Online Media Research Peter Diem/Vienna Moscow, April 4 th, 2013 Basics of Practical Online Research 1. Online Research about the Internet In this case the aim of online surveys is to clarify facts about
More information2. METHODS OF DATA COLLECTION. Types of Data. Some examples from Wainer, Palmer and Bradlow (Chance):
2. METHODS OF DATA COLLECTION Proper data collection is important. Even sophisticated statistical analyses can t compensate for data with bias, ambiguity or errors. Some examples from Wainer, Palmer and
More informationMaking Surveys Work for You: Some Important Design Considerations
Making Surveys Work for You: Some Important Design Considerations By Don A. Dillman* For Net-Conference on Survey Methods and Measurement June 15,11 *Regents Professor in the Department of Sociology and
More informationInternet-Based Survey Research: Small- and Large-Scale Research for Business Decisions
1 Internet-Based Survey Research: Small- and Large-Scale Research for Business Decisions Albert R. Hollenbeck, Ph.D., Senior Research Advisor, AARP Knowledge Management Abstract Large-scale (n > 2000)
More informationThe Basics of a Compensation Program
The Basics of a Compensation Program Learning Objectives By the end of this chapter, you should be able to: List three ways in which compensation plays a role in the management of the enterprise. Describe
More information1. What is your primary motive for attending this farmers market? (choose only one) Purchase produce. Events/activities Purchase packaged goods
Conducting Market Research Using Primary Data Kynda R. Curtis, Ph.D. Assistant Professor and State Extension Specialist Department of Resource Economics, University of Nevada, Reno WEMC FS#7-08 Overview
More information