Marketing Research (MBA) - Final Exam

Size: px
Start display at page:

Download "Marketing Research (MBA) - Final Exam"

Transcription

1 Marketing Research (MBA) - Final Exam Student: 1. Bad question/setups are any questions or directives that the fundamental communications from respondent to researcher. A.Distort B.Enlighten C.Allow D.Clarify 2. Which one of the following is an example of a bad question or response format? A.Loaded items B.Unanswerable items C.Leading items D.Double-barreled questions 3. Which one of the following is an example of a leading question? A."What was your parent's annual after-tax income three years ago?" B."This country is built on the ideals of personal freedom and liberty. Should the government raise taxes on cigarettes to discourage them from smoking?" C."Do you drink Coke with breakfast, lunch, and dinner?" D.All of the above 4. On a survey, a student comes across a question that asks, "To what extent did you find marketing and accounting courses useful?" This question is (most closely) an example of a/an: A.Incomprehensible question B.Unanswerable question C.Leading question D.Loaded question E.Double-barreled question 1

2 5. All of the following are guidelines for writing good questions for a survey, EXCEPT: A.Questions should avoid qualifying phrases B.Question response categories should be overlapping C.Questions and scale items should be meaningful to the respondent D.Questions should be simple and straightforward E.Questions should avoid technical or sophisticated words 6. After observing a family eating dessert after their meals, an ethnographer records their behavior in her journal. She then asks the head of the family to read her description to verify that the story she was telling was accurate. In doing this, the ethnographer is involved in: A.Member checking B.Thick description C.Data categorization D.Memo check back E.Respondent courtesy check 7. A researcher is in the process of reading transcripts from a field study and developing categories to put different responses in. When similar responses are encountered, they are coded similarly. The process this researcher is engaged in is called: A.Data reduction B.Data assimilation C.Data display D.Data verification E.Data congruence 8. Abstraction refers to the process of: A.Asking key informants to read the researcher's report and verify that the story they are telling is accurate B.Placing portions of transcripts into similar groups based on their content C.Collapsing some categories or themes into a higher order construct D.Developing and refining theory and constructs by analyzing the differences and similarities in passages, themes, or types of participants E.Preparing an abstract (executive summary) of a qualitative data analysis report 2

3 9. Which of the following processes most clearly establishes the boundary conditions for the theory that is being developed? A.Negative case analysis B.Memoing C.Thick description D.Tabulation 10. If a researcher is interested in developing some initial insights into the relationship between themes, she should look at: A.The number of times each theme is mentioned by respondents B.The co-occurrence of themes in the study C.The number of times there are negative cases of one or both the themes D.The number of times there are lone wolf comments about the themes 11. Emic validity can be established using: A.Comparison B.Axial coding C.Triangulation D.Member checking E.Selective coding 12. A researcher collects data using ethnographic studies. In order to confirm his findings, he collects data through in-depth interviews. In doing so, the researcher is doing: A.Cross-tabulation B.Credibility assessment C.Triangulation D.Cross-validity assessment 3

4 13. Data validation: A.Is the process to determine, to the extent possible, if surveys, interviews, or observations were conducted correctly and free of interviewer fraud B.Is a term used in the marketing research industry to imply cheating or falsification of data collection C.Is the process where the interviewer/survey instruments are checked for mistakes that may have occurred by either the interviewer or the respondent during data collection D.Involves grouping and assigning value to various responses from the survey instrument E.Are those tasks involved with the direct input of the coded data into some specified software package that will ultimately allow the research analyst to manipulate and transform the raw data into useful information 14. If a researcher asks if a friend completed the questionnaire rather than a chosen participant, he or she is dealing with a question of: A.Fraud B.Screening C.Procedure D.Completeness E.Courtesy 15. If a researcher asks if a respondent only answered a few of the questions from the interview, the researcher is dealing with a question of: A.Fraud B.Editing C.Instrumentation D.Completeness E.Courtesy 16. A researcher decides to assign a value of 1 if the respondent is male and a value of 2 if the respondent is a female. By assigning numbers to different genders, the researcher is engaged in the process of: A.Data coding B.Data editing C.Data validation D.Data parsing E.Data sifting 4

5 17. Open-ended questions: A.Allow for an exact list of potential responses to prepare B.Lack variability in responses C.Provide unique problems to the coding process D.Produce little information of value 18. John is in the process of assigning codes for a question that has two responses- Yes or No. What is the suggested numerical code for "Yes"? A.0 B.1 C.2 D.100 E Which of the following methods eliminates the need for data entry? A.Touch-screen terminals B.Light pens C.Optical scanning D.Online surveys 20. Which of the following measures is an indicator of how similar or dissimilar the numbers are in the set of responses? A.Cross-tabulations B.Mean C.Median D.Mode E.Standard deviation 21. The mean, median, and mode are all: A.Inferential statistics B.Predictive statistics C.Descriptive statistics D.Multivariate statistics 5

6 22. Independent samples are: A.Two or more groups of responses that are tested as though they may come from different populations B.Two or more groups of responses that originated from the sample population C.Used when the sample size is larger than 30 and the standard deviation is unknown D.The errors made by rejecting the null hypothesis when it is true 23. Related samples are: A.Two or more groups of responses that are tested as though they may come from different populations B.Two or more groups of responses that originated from the same sample population C.The researcher's preconceived notion of the relationships the data should present D.The errors made by rejecting the null hypothesis when it is true 24. If a group of salespeople is tested on their product knowledge both before and after a training program, these salespeople would represent: A.Independent groups B.Related groups C.Bimodal groups D.Unigroups 25. ANOVA is: A.A statistical technique that determines if three or more means are statistically different form each other B.The ratio of within-group mean squared variance to between-group mean-squared variance C.A test that flags the means which are statistically different from each other D.Used to compare two groups 26. In one-way ANOVA, which of the following requirements must be met? A.Both the dependent and independent variables must be categorical B.Both the dependent and independent variables must be metric C.The dependent variable must be metric while the independent variable must be categorical D.The dependent variable must be categorical while the independent variable must be metric 6

7 27. A follow-up test is: A.Used to statistically evaluate the differences between the group means in ANOVA B.The ratio of between-group mean squared variance to within-group mean-squared variance C.A test that flags the means which are statistically different from each other D.The average squared deviations about the mean of a distribution of values 28. If the variance between groups is 3 and the variance within groups is 2, the F-ratio is: A.1 B.0.67 C.5 D.1.5 E.9/4 29. A researcher is interested in studying if there are differences in coffee consumption among people from three ethnic backgrounds- Hispanics, White, and African Americans. The most appropriate test for this is: A.Univariate t-test B.Bivariate t-test C.ANOVA D.n-way ANOVA 30. A researcher is interested in studying if there are differences in coffee consumption and fast food consumption among people from three ethnic backgrounds- Hispanics, White, and African Americans. The most appropriate test for this is: A.Univariate t-test B.Bivariate t-test C.ANOVA D.n-way ANOVA 7

8 31. A curvilinear relationship is: A.A condition under which there is a consistent and systematic linkage between two or more variables B.A relationship between two variables whereby the strength and nature of the relationship remains he same over the range of both variables C.A relationship between two variables whereby the strength and/or direction of their relationship changes over the range of both variables D.Easier to work with than a linear relationship E.A graphic plot of the relative position of two variables using a horizontal and vertical axis to represent the values of the respective variables 32. "As the ownership of DVD players goes up, DVD rentals at Blockbuster will also go up." This statement illustrates the concept of: A.Co-dependence B.Co-alteration C.Covariation D.Co-existence E.Convergence 33. A researcher plots a scatter diagram of two variables. The dots on the plot are scattered roughly as a circle. This indicates that the relationship (covariation) between the two variables: A.Is linear, positive B.Is linear, negative C.Is circular, positive D.Is circular, negative E.Is very close to zero 34. The Pearson correlation coefficient is: A.A statistical measure of the strength of a linear relationship between two metric variables B.A number measuring the proportion of variation in one variable accounted for by another C.A statistical measure of the linear association between two variables where both have been measured using ordinal scales D.A statistical technique which analyzes the linear relationship between two variables by estimating coefficients for an equation for a straight line E.When the nature and extent of a relationship between two variables is known with certainty 8

9 35. For a retail store, there exists a strong relationship between the amount spent on local television advertising and store sales. As it increases advertising expenditure, sales go up. Which of the following seems to be the most appropriate Pearson correlation coefficient for this relationship? A.0.01 B.0.05 C.0.90 D E As a rule of thumb, the relationship between two variables is considered very strong if the absolute value of the Pearson correlation coefficient is: A.Greater than 0.1 B.Greater than 0.5 C.Greater than 0.8 D.Greater than 1.0 E.Greater than The Spearman rank order correlation coefficient is: A.Not used when two variables have been measured using ordinal scales B.A number measuring the proportion of variation in one variable accounted for by another C.A statistical measure of the linear association between two variables where both have been measured using ordinal scales D.A measure that tends to produce the highest coefficient and is not considered a conservative measure E.When the nature and extent of a relationship between two variables is known with certainty. 38. The r-square coefficient of determination is: A.A statistical measure of the strength of a linear relationship between two metric variables B.A number measuring the proportion of variation in one variable accounted for by another variable C.A statistical measure of the linear association between two variables where both have been measured using ordinal scales D.A statistical technique which analyzes the linear relationship between two variables by estimating coefficients for an equation for a straight line E.When the nature and extent of a relationship between two variables is known with certainty 9

10 39. Given below are values of the coefficient of correlation and the level of statistical significance. In which of the following cases are both the statistical significance and substantive significance high? A.-0.8, 0.01 B.0.1, 0.9 C.0.9, 0.2 D.0.1, 0.1 E.0.5, The formula for a straight line is Y = a + bx, where X stands for: A.The dependent variable B.The independent variable C.The Y intercept D.The slope 41. If a researcher is interested in measuring the effect of two independent variables on a dependent variable, she should use: A.Pearson correlation coefficient B.Spearman correlation coefficient C.Bivariate regression analysis D.Multiple regression analysis 42. The difference between the observed value of the dependent variable and the predicted value of the dependent variable in a regression equation is called the: A.Error B.Beta weight C.Slope D.Y-intercept 10

11 43. In a regression analysis, the strength of the relationship between the independent and dependent variables is indicated by: A.The regression coefficient B.The r 2 C.The significance level D.The t statistic 44. Multicollinearity is: A.A statistical procedure that estimates regression equation coefficients which produce the lowest sum of squared differences between the actual and predicted values of the dependent variable B.A statistical technique which analyzes the linear relationship between a dependent variable and multiple independent variables by estimating coefficients for the equation for a straight line C.An estimated regression coefficient which has been recalculated to have a mean of zero and a standard deviation of 1 D.A statistic which compares the amount of variation in the dependent measure "explained" or associated with the independent variables to the "unexplained" or error variance E.A situation in which several independent variables are highly correlated with each other 45. Industry best practices suggest to always keep in mind five problem areas that may arise when writing a marketing research report, these include which of the following? A.Lack of data interpretation B.Unnecessary use of multivariate statistics C.Lack of relevance D.Too much emphasis is placed on too few statistics 11

Simple Linear Regression Inference

Simple Linear Regression Inference Simple Linear Regression Inference 1 Inference requirements The Normality assumption of the stochastic term e is needed for inference even if it is not a OLS requirement. Therefore we have: Interpretation

More information

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses.

DESCRIPTIVE STATISTICS. The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE STATISTICS The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. DESCRIPTIVE VS. INFERENTIAL STATISTICS Descriptive To organize,

More information

11/20/2014. Correlational research is used to describe the relationship between two or more naturally occurring variables.

11/20/2014. Correlational research is used to describe the relationship between two or more naturally occurring variables. Correlational research is used to describe the relationship between two or more naturally occurring variables. Is age related to political conservativism? Are highly extraverted people less afraid of rejection

More information

Introduction to Regression and Data Analysis

Introduction to Regression and Data Analysis Statlab Workshop Introduction to Regression and Data Analysis with Dan Campbell and Sherlock Campbell October 28, 2008 I. The basics A. Types of variables Your variables may take several forms, and it

More information

Simple Linear Regression Chapter 11

Simple Linear Regression Chapter 11 Simple Linear Regression Chapter 11 Rationale Frequently decision-making situations require modeling of relationships among business variables. For instance, the amount of sale of a product may be related

More information

Factors affecting online sales

Factors affecting online sales Factors affecting online sales Table of contents Summary... 1 Research questions... 1 The dataset... 2 Descriptive statistics: The exploratory stage... 3 Confidence intervals... 4 Hypothesis tests... 4

More information

The aspect of the data that we want to describe/measure is the degree of linear relationship between and The statistic r describes/measures the degree

The aspect of the data that we want to describe/measure is the degree of linear relationship between and The statistic r describes/measures the degree PS 511: Advanced Statistics for Psychological and Behavioral Research 1 Both examine linear (straight line) relationships Correlation works with a pair of scores One score on each of two variables ( and

More information

12/31/2016. PSY 512: Advanced Statistics for Psychological and Behavioral Research 2

12/31/2016. PSY 512: Advanced Statistics for Psychological and Behavioral Research 2 PSY 512: Advanced Statistics for Psychological and Behavioral Research 2 Understand linear regression with a single predictor Understand how we assess the fit of a regression model Total Sum of Squares

More information

DATA INTERPRETATION AND STATISTICS

DATA INTERPRETATION AND STATISTICS PholC60 September 001 DATA INTERPRETATION AND STATISTICS Books A easy and systematic introductory text is Essentials of Medical Statistics by Betty Kirkwood, published by Blackwell at about 14. DESCRIPTIVE

More information

CHAPTER 13 SIMPLE LINEAR REGRESSION. Opening Example. Simple Regression. Linear Regression

CHAPTER 13 SIMPLE LINEAR REGRESSION. Opening Example. Simple Regression. Linear Regression Opening Example CHAPTER 13 SIMPLE LINEAR REGREION SIMPLE LINEAR REGREION! Simple Regression! Linear Regression Simple Regression Definition A regression model is a mathematical equation that descries the

More information

Simple Predictive Analytics Curtis Seare

Simple Predictive Analytics Curtis Seare Using Excel to Solve Business Problems: Simple Predictive Analytics Curtis Seare Copyright: Vault Analytics July 2010 Contents Section I: Background Information Why use Predictive Analytics? How to use

More information

Descriptive Statistics

Descriptive Statistics Descriptive Statistics Primer Descriptive statistics Central tendency Variation Relative position Relationships Calculating descriptive statistics Descriptive Statistics Purpose to describe or summarize

More information

Variables and Data A variable contains data about anything we measure. For example; age or gender of the participants or their score on a test.

Variables and Data A variable contains data about anything we measure. For example; age or gender of the participants or their score on a test. The Analysis of Research Data The design of any project will determine what sort of statistical tests you should perform on your data and how successful the data analysis will be. For example if you decide

More information

Part 2: Analysis of Relationship Between Two Variables

Part 2: Analysis of Relationship Between Two Variables Part 2: Analysis of Relationship Between Two Variables Linear Regression Linear correlation Significance Tests Multiple regression Linear Regression Y = a X + b Dependent Variable Independent Variable

More information

Univariate Regression

Univariate Regression Univariate Regression Correlation and Regression The regression line summarizes the linear relationship between 2 variables Correlation coefficient, r, measures strength of relationship: the closer r is

More information

Chapter 13 Introduction to Linear Regression and Correlation Analysis

Chapter 13 Introduction to Linear Regression and Correlation Analysis Chapter 3 Student Lecture Notes 3- Chapter 3 Introduction to Linear Regression and Correlation Analsis Fall 2006 Fundamentals of Business Statistics Chapter Goals To understand the methods for displaing

More information

Module 3: Correlation and Covariance

Module 3: Correlation and Covariance Using Statistical Data to Make Decisions Module 3: Correlation and Covariance Tom Ilvento Dr. Mugdim Pašiƒ University of Delaware Sarajevo Graduate School of Business O ften our interest in data analysis

More information

The Big Picture. Correlation. Scatter Plots. Data

The Big Picture. Correlation. Scatter Plots. Data The Big Picture Correlation Bret Hanlon and Bret Larget Department of Statistics Universit of Wisconsin Madison December 6, We have just completed a length series of lectures on ANOVA where we considered

More information

STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance

STA-201-TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance Principles of Statistics STA-201-TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis

More information

Correlation key concepts:

Correlation key concepts: CORRELATION Correlation key concepts: Types of correlation Methods of studying correlation a) Scatter diagram b) Karl pearson s coefficient of correlation c) Spearman s Rank correlation coefficient d)

More information

Chapter 7: Simple linear regression Learning Objectives

Chapter 7: Simple linear regression Learning Objectives Chapter 7: Simple linear regression Learning Objectives Reading: Section 7.1 of OpenIntro Statistics Video: Correlation vs. causation, YouTube (2:19) Video: Intro to Linear Regression, YouTube (5:18) -

More information

A correlation exists between two variables when one of them is related to the other in some way.

A correlation exists between two variables when one of them is related to the other in some way. Lecture #10 Chapter 10 Correlation and Regression The main focus of this chapter is to form inferences based on sample data that come in pairs. Given such paired sample data, we want to determine whether

More information

Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics.

Business Statistics. Successful completion of Introductory and/or Intermediate Algebra courses is recommended before taking Business Statistics. Business Course Text Bowerman, Bruce L., Richard T. O'Connell, J. B. Orris, and Dawn C. Porter. Essentials of Business, 2nd edition, McGraw-Hill/Irwin, 2008, ISBN: 978-0-07-331988-9. Required Computing

More information

Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics

Course Text. Required Computing Software. Course Description. Course Objectives. StraighterLine. Business Statistics Course Text Business Statistics Lind, Douglas A., Marchal, William A. and Samuel A. Wathen. Basic Statistics for Business and Economics, 7th edition, McGraw-Hill/Irwin, 2010, ISBN: 9780077384470 [This

More information

Elementary Statistics. Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination

Elementary Statistics. Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination Scatter Plot, Regression Line, Linear Correlation Coefficient, and Coefficient of Determination What is a Scatter Plot? A Scatter Plot is a plot of ordered pairs (x, y) where the horizontal axis is used

More information

NCSS Statistical Software Principal Components Regression. In ordinary least squares, the regression coefficients are estimated using the formula ( )

NCSS Statistical Software Principal Components Regression. In ordinary least squares, the regression coefficients are estimated using the formula ( ) Chapter 340 Principal Components Regression Introduction is a technique for analyzing multiple regression data that suffer from multicollinearity. When multicollinearity occurs, least squares estimates

More information

Causal Forecasting Models

Causal Forecasting Models CTL.SC1x -Supply Chain & Logistics Fundamentals Causal Forecasting Models MIT Center for Transportation & Logistics Causal Models Used when demand is correlated with some known and measurable environmental

More information

Lesson Lesson Outline Outline

Lesson Lesson Outline Outline Lesson 15 Linear Regression Lesson 15 Outline Review correlation analysis Dependent and Independent variables Least Squares Regression line Calculating l the slope Calculating the Intercept Residuals and

More information

Inferential Statistics

Inferential Statistics Inferential Statistics Sampling and the normal distribution Z-scores Confidence levels and intervals Hypothesis testing Commonly used statistical methods Inferential Statistics Descriptive statistics are

More information

Exercise 1.12 (Pg. 22-23)

Exercise 1.12 (Pg. 22-23) Individuals: The objects that are described by a set of data. They may be people, animals, things, etc. (Also referred to as Cases or Records) Variables: The characteristics recorded about each individual.

More information

Statistics and research

Statistics and research Statistics and research Usaneya Perngparn Chitlada Areesantichai Drug Dependence Research Center (WHOCC for Research and Training in Drug Dependence) College of Public Health Sciences Chulolongkorn University,

More information

Outline: Demand Forecasting

Outline: Demand Forecasting Outline: Demand Forecasting Given the limited background from the surveys and that Chapter 7 in the book is complex, we will cover less material. The role of forecasting in the chain Characteristics of

More information

Simple Regression and Correlation

Simple Regression and Correlation Simple Regression and Correlation Today, we are going to discuss a powerful statistical technique for examining whether or not two variables are related. Specifically, we are going to talk about the ideas

More information

SPSS Guide: Regression Analysis

SPSS Guide: Regression Analysis SPSS Guide: Regression Analysis I put this together to give you a step-by-step guide for replicating what we did in the computer lab. It should help you run the tests we covered. The best way to get familiar

More information

January 26, 2009 The Faculty Center for Teaching and Learning

January 26, 2009 The Faculty Center for Teaching and Learning THE BASICS OF DATA MANAGEMENT AND ANALYSIS A USER GUIDE January 26, 2009 The Faculty Center for Teaching and Learning THE BASICS OF DATA MANAGEMENT AND ANALYSIS Table of Contents Table of Contents... i

More information

Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm

Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm Mgt 540 Research Methods Data Analysis 1 Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jin-tselink/tselink.htm http://web.utk.edu/~dap/random/order/start.htm

More information

where b is the slope of the line and a is the intercept i.e. where the line cuts the y axis.

where b is the slope of the line and a is the intercept i.e. where the line cuts the y axis. Least Squares Introduction We have mentioned that one should not always conclude that because two variables are correlated that one variable is causing the other to behave a certain way. However, sometimes

More information

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number

1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number 1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 3(x - x) B. x 3 x C. 3x - x D. x - 3x 2) Write the following as an algebraic expression

More information

12/31/2016. PSY 512: Advanced Statistics for Psychological and Behavioral Research 2

12/31/2016. PSY 512: Advanced Statistics for Psychological and Behavioral Research 2 PSY 512: Advanced Statistics for Psychological and Behavioral Research 2 Understand when to use multiple Understand the multiple equation and what the coefficients represent Understand different methods

More information

" Y. Notation and Equations for Regression Lecture 11/4. Notation:

 Y. Notation and Equations for Regression Lecture 11/4. Notation: Notation: Notation and Equations for Regression Lecture 11/4 m: The number of predictor variables in a regression Xi: One of multiple predictor variables. The subscript i represents any number from 1 through

More information

business statistics using Excel OXFORD UNIVERSITY PRESS Glyn Davis & Branko Pecar

business statistics using Excel OXFORD UNIVERSITY PRESS Glyn Davis & Branko Pecar business statistics using Excel Glyn Davis & Branko Pecar OXFORD UNIVERSITY PRESS Detailed contents Introduction to Microsoft Excel 2003 Overview Learning Objectives 1.1 Introduction to Microsoft Excel

More information

Algebra 1 Chapter 3 Vocabulary. equivalent - Equations with the same solutions as the original equation are called.

Algebra 1 Chapter 3 Vocabulary. equivalent - Equations with the same solutions as the original equation are called. Chapter 3 Vocabulary equivalent - Equations with the same solutions as the original equation are called. formula - An algebraic equation that relates two or more real-life quantities. unit rate - A rate

More information

2. What is the general linear model to be used to model linear trend? (Write out the model) = + + + or

2. What is the general linear model to be used to model linear trend? (Write out the model) = + + + or Simple and Multiple Regression Analysis Example: Explore the relationships among Month, Adv.$ and Sales $: 1. Prepare a scatter plot of these data. The scatter plots for Adv.$ versus Sales, and Month versus

More information

psyc3010 lecture 8 standard and hierarchical multiple regression last week: correlation and regression Next week: moderated regression

psyc3010 lecture 8 standard and hierarchical multiple regression last week: correlation and regression Next week: moderated regression psyc3010 lecture 8 standard and hierarchical multiple regression last week: correlation and regression Next week: moderated regression 1 last week this week last week we revised correlation & regression

More information

Directions for using SPSS

Directions for using SPSS Directions for using SPSS Table of Contents Connecting and Working with Files 1. Accessing SPSS... 2 2. Transferring Files to N:\drive or your computer... 3 3. Importing Data from Another File Format...

More information

DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF LANCASTER MSC IN PSYCHOLOGICAL RESEARCH METHODS ANALYSING AND INTERPRETING DATA 2 PART 1 WEEK 9

DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF LANCASTER MSC IN PSYCHOLOGICAL RESEARCH METHODS ANALYSING AND INTERPRETING DATA 2 PART 1 WEEK 9 DEPARTMENT OF PSYCHOLOGY UNIVERSITY OF LANCASTER MSC IN PSYCHOLOGICAL RESEARCH METHODS ANALYSING AND INTERPRETING DATA 2 PART 1 WEEK 9 Analysis of covariance and multiple regression So far in this course,

More information

Chicago Booth BUSINESS STATISTICS 41000 Final Exam Fall 2011

Chicago Booth BUSINESS STATISTICS 41000 Final Exam Fall 2011 Chicago Booth BUSINESS STATISTICS 41000 Final Exam Fall 2011 Name: Section: I pledge my honor that I have not violated the Honor Code Signature: This exam has 34 pages. You have 3 hours to complete this

More information

Introduction to Quantitative Methods

Introduction to Quantitative Methods Introduction to Quantitative Methods October 15, 2009 Contents 1 Definition of Key Terms 2 2 Descriptive Statistics 3 2.1 Frequency Tables......................... 4 2.2 Measures of Central Tendencies.................

More information

SELF-TEST: SIMPLE REGRESSION

SELF-TEST: SIMPLE REGRESSION ECO 22000 McRAE SELF-TEST: SIMPLE REGRESSION Note: Those questions indicated with an (N) are unlikely to appear in this form on an in-class examination, but you should be able to describe the procedures

More information

CORRELATIONAL ANALYSIS: PEARSON S r Purpose of correlational analysis The purpose of performing a correlational analysis: To discover whether there

CORRELATIONAL ANALYSIS: PEARSON S r Purpose of correlational analysis The purpose of performing a correlational analysis: To discover whether there CORRELATIONAL ANALYSIS: PEARSON S r Purpose of correlational analysis The purpose of performing a correlational analysis: To discover whether there is a relationship between variables, To find out the

More information

Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo

Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo Readings: Ha and Ha Textbook - Chapters 1 8 Appendix D & E (online) Plous - Chapters 10, 11, 12 and 14 Chapter 10: The Representativeness Heuristic Chapter 11: The Availability Heuristic Chapter 12: Probability

More information

1/27/2013. PSY 512: Advanced Statistics for Psychological and Behavioral Research 2

1/27/2013. PSY 512: Advanced Statistics for Psychological and Behavioral Research 2 PSY 512: Advanced Statistics for Psychological and Behavioral Research 2 Introduce moderated multiple regression Continuous predictor continuous predictor Continuous predictor categorical predictor Understand

More information

Statistics Review PSY379

Statistics Review PSY379 Statistics Review PSY379 Basic concepts Measurement scales Populations vs. samples Continuous vs. discrete variable Independent vs. dependent variable Descriptive vs. inferential stats Common analyses

More information

Practice 3 SPSS. Partially based on Notes from the University of Reading:

Practice 3 SPSS. Partially based on Notes from the University of Reading: Practice 3 SPSS Partially based on Notes from the University of Reading: http://www.reading.ac.uk Simple Linear Regression A simple linear regression model is fitted when you want to investigate whether

More information

17. SIMPLE LINEAR REGRESSION II

17. SIMPLE LINEAR REGRESSION II 17. SIMPLE LINEAR REGRESSION II The Model In linear regression analysis, we assume that the relationship between X and Y is linear. This does not mean, however, that Y can be perfectly predicted from X.

More information

Quantitative Data Analysis: Choosing a statistical test Prepared by the Office of Planning, Assessment, Research and Quality

Quantitative Data Analysis: Choosing a statistical test Prepared by the Office of Planning, Assessment, Research and Quality Quantitative Data Analysis: Choosing a statistical test Prepared by the Office of Planning, Assessment, Research and Quality 1 To help choose which type of quantitative data analysis to use either before

More information

Statistics II Final Exam - January Use the University stationery to give your answers to the following questions.

Statistics II Final Exam - January Use the University stationery to give your answers to the following questions. Statistics II Final Exam - January 2012 Use the University stationery to give your answers to the following questions. Do not forget to write down your name and class group in each page. Indicate clearly

More information

7. Tests of association and Linear Regression

7. Tests of association and Linear Regression 7. Tests of association and Linear Regression In this chapter we consider 1. Tests of Association for 2 qualitative variables. 2. Measures of the strength of linear association between 2 quantitative variables.

More information

LEARNING OBJECTIVES SCALES OF MEASUREMENT: A REVIEW SCALES OF MEASUREMENT: A REVIEW DESCRIBING RESULTS DESCRIBING RESULTS 8/14/2016

LEARNING OBJECTIVES SCALES OF MEASUREMENT: A REVIEW SCALES OF MEASUREMENT: A REVIEW DESCRIBING RESULTS DESCRIBING RESULTS 8/14/2016 UNDERSTANDING RESEARCH RESULTS: DESCRIPTION AND CORRELATION LEARNING OBJECTIVES Contrast three ways of describing results: Comparing group percentages Correlating scores Comparing group means Describe

More information

Section 14 Simple Linear Regression: Introduction to Least Squares Regression

Section 14 Simple Linear Regression: Introduction to Least Squares Regression Slide 1 Section 14 Simple Linear Regression: Introduction to Least Squares Regression There are several different measures of statistical association used for understanding the quantitative relationship

More information

Online Appendix: Thar SHE blows? Gender, Competition, and Bubbles in Experimental Asset Markets, by Catherine C. Eckel and Sascha C.

Online Appendix: Thar SHE blows? Gender, Competition, and Bubbles in Experimental Asset Markets, by Catherine C. Eckel and Sascha C. Online Appendix: Thar SHE blows? Gender, Competition, and Bubbles in Experimental Asset Markets, by Catherine C. Eckel and Sascha C. Füllbrunn A1. META-ANALYSIS Treatment TABLE A1. BUBBLE MEASURES FOR

More information

By Hui Bian Office for Faculty Excellence

By Hui Bian Office for Faculty Excellence By Hui Bian Office for Faculty Excellence 1 Email: bianh@ecu.edu Phone: 328-5428 Location: 2307 Old Cafeteria Complex 2 When want to predict one variable from a combination of several variables. When want

More information

Statistics 151 Practice Midterm 1 Mike Kowalski

Statistics 151 Practice Midterm 1 Mike Kowalski Statistics 151 Practice Midterm 1 Mike Kowalski Statistics 151 Practice Midterm 1 Multiple Choice (50 minutes) Instructions: 1. This is a closed book exam. 2. You may use the STAT 151 formula sheets and

More information

Research Variables. Measurement. Scales of Measurement. Chapter 4: Data & the Nature of Measurement

Research Variables. Measurement. Scales of Measurement. Chapter 4: Data & the Nature of Measurement Chapter 4: Data & the Nature of Graziano, Raulin. Research Methods, a Process of Inquiry Presented by Dustin Adams Research Variables Variable Any characteristic that can take more than one form or value.

More information

X X X a) perfect linear correlation b) no correlation c) positive correlation (r = 1) (r = 0) (0 < r < 1)

X X X a) perfect linear correlation b) no correlation c) positive correlation (r = 1) (r = 0) (0 < r < 1) CORRELATION AND REGRESSION / 47 CHAPTER EIGHT CORRELATION AND REGRESSION Correlation and regression are statistical methods that are commonly used in the medical literature to compare two or more variables.

More information

Chapter 9. Section Correlation

Chapter 9. Section Correlation Chapter 9 Section 9.1 - Correlation Objectives: Introduce linear correlation, independent and dependent variables, and the types of correlation Find a correlation coefficient Test a population correlation

More information

Chapter 11: Two Variable Regression Analysis

Chapter 11: Two Variable Regression Analysis Department of Mathematics Izmir University of Economics Week 14-15 2014-2015 In this chapter, we will focus on linear models and extend our analysis to relationships between variables, the definitions

More information

Name: Date: Use the following to answer questions 2-3:

Name: Date: Use the following to answer questions 2-3: Name: Date: 1. A study is conducted on students taking a statistics class. Several variables are recorded in the survey. Identify each variable as categorical or quantitative. A) Type of car the student

More information

Common Core Unit Summary Grades 6 to 8

Common Core Unit Summary Grades 6 to 8 Common Core Unit Summary Grades 6 to 8 Grade 8: Unit 1: Congruence and Similarity- 8G1-8G5 rotations reflections and translations,( RRT=congruence) understand congruence of 2 d figures after RRT Dilations

More information

2. Simple Linear Regression

2. Simple Linear Regression Research methods - II 3 2. Simple Linear Regression Simple linear regression is a technique in parametric statistics that is commonly used for analyzing mean response of a variable Y which changes according

More information

Module 5: Multiple Regression Analysis

Module 5: Multiple Regression Analysis Using Statistical Data Using to Make Statistical Decisions: Data Multiple to Make Regression Decisions Analysis Page 1 Module 5: Multiple Regression Analysis Tom Ilvento, University of Delaware, College

More information

11. Analysis of Case-control Studies Logistic Regression

11. Analysis of Case-control Studies Logistic Regression Research methods II 113 11. Analysis of Case-control Studies Logistic Regression This chapter builds upon and further develops the concepts and strategies described in Ch.6 of Mother and Child Health:

More information

Copyright 2010-2012 PEOPLECERT Int. Ltd and IASSC

Copyright 2010-2012 PEOPLECERT Int. Ltd and IASSC PEOPLECERT - Personnel Certification Body 3 Korai st., 105 64 Athens, Greece, Tel.: +30 210 372 9100, Fax: +30 210 372 9101, e-mail: info@peoplecert.org, www.peoplecert.org Copyright 2010-2012 PEOPLECERT

More information

Lecture - 32 Regression Modelling Using SPSS

Lecture - 32 Regression Modelling Using SPSS Applied Multivariate Statistical Modelling Prof. J. Maiti Department of Industrial Engineering and Management Indian Institute of Technology, Kharagpur Lecture - 32 Regression Modelling Using SPSS (Refer

More information

II. DISTRIBUTIONS distribution normal distribution. standard scores

II. DISTRIBUTIONS distribution normal distribution. standard scores Appendix D Basic Measurement And Statistics The following information was developed by Steven Rothke, PhD, Department of Psychology, Rehabilitation Institute of Chicago (RIC) and expanded by Mary F. Schmidt,

More information

2013 MBA Jump Start Program. Statistics Module Part 3

2013 MBA Jump Start Program. Statistics Module Part 3 2013 MBA Jump Start Program Module 1: Statistics Thomas Gilbert Part 3 Statistics Module Part 3 Hypothesis Testing (Inference) Regressions 2 1 Making an Investment Decision A researcher in your firm just

More information

BIOSTATISTICS QUIZ ANSWERS

BIOSTATISTICS QUIZ ANSWERS BIOSTATISTICS QUIZ ANSWERS 1. When you read scientific literature, do you know whether the statistical tests that were used were appropriate and why they were used? a. Always b. Mostly c. Rarely d. Never

More information

DATA ANALYSIS. QEM Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University

DATA ANALYSIS. QEM Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University DATA ANALYSIS QEM Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University Quantitative Research What is Statistics? Statistics (as a subject) is the science

More information

Regression. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question.

Regression. Name: Class: Date: Multiple Choice Identify the choice that best completes the statement or answers the question. Class: Date: Regression Multiple Choice Identify the choice that best completes the statement or answers the question. 1. Given the least squares regression line y8 = 5 2x: a. the relationship between

More information

Improving the Performance of Data Mining Models with Data Preparation Using SAS Enterprise Miner Ricardo Galante, SAS Institute Brasil, São Paulo, SP

Improving the Performance of Data Mining Models with Data Preparation Using SAS Enterprise Miner Ricardo Galante, SAS Institute Brasil, São Paulo, SP Improving the Performance of Data Mining Models with Data Preparation Using SAS Enterprise Miner Ricardo Galante, SAS Institute Brasil, São Paulo, SP ABSTRACT In data mining modelling, data preparation

More information

Using Excel (Microsoft Office 2007 Version) for Graphical Analysis of Data

Using Excel (Microsoft Office 2007 Version) for Graphical Analysis of Data Using Excel (Microsoft Office 2007 Version) for Graphical Analysis of Data Introduction In several upcoming labs, a primary goal will be to determine the mathematical relationship between two variable

More information

Statistical Models in R

Statistical Models in R Statistical Models in R Some Examples Steven Buechler Department of Mathematics 276B Hurley Hall; 1-6233 Fall, 2007 Outline Statistical Models Structure of models in R Model Assessment (Part IA) Anova

More information

Chapter 5 Analysis of variance SPSS Analysis of variance

Chapter 5 Analysis of variance SPSS Analysis of variance Chapter 5 Analysis of variance SPSS Analysis of variance Data file used: gss.sav How to get there: Analyze Compare Means One-way ANOVA To test the null hypothesis that several population means are equal,

More information

UNDERSTANDING MULTIPLE REGRESSION

UNDERSTANDING MULTIPLE REGRESSION UNDERSTANDING Multiple regression analysis (MRA) is any of several related statistical methods for evaluating the effects of more than one independent (or predictor) variable on a dependent (or outcome)

More information

Lesson 4 Part 1. Relationships between. two numerical variables. Correlation Coefficient. Relationship between two

Lesson 4 Part 1. Relationships between. two numerical variables. Correlation Coefficient. Relationship between two Lesson Part Relationships between two numerical variables Correlation Coefficient The correlation coefficient is a summary statistic that describes the linear between two numerical variables Relationship

More information

496 STATISTICAL ANALYSIS OF CAUSE AND EFFECT

496 STATISTICAL ANALYSIS OF CAUSE AND EFFECT 496 STATISTICAL ANALYSIS OF CAUSE AND EFFECT * Use a non-parametric technique. There are statistical methods, called non-parametric methods, that don t make any assumptions about the underlying distribution

More information

03 The full syllabus. 03 The full syllabus continued. For more information visit www.cimaglobal.com PAPER C03 FUNDAMENTALS OF BUSINESS MATHEMATICS

03 The full syllabus. 03 The full syllabus continued. For more information visit www.cimaglobal.com PAPER C03 FUNDAMENTALS OF BUSINESS MATHEMATICS 0 The full syllabus 0 The full syllabus continued PAPER C0 FUNDAMENTALS OF BUSINESS MATHEMATICS Syllabus overview This paper primarily deals with the tools and techniques to understand the mathematics

More information

How to choose a statistical test. Francisco J. Candido dos Reis DGO-FMRP University of São Paulo

How to choose a statistical test. Francisco J. Candido dos Reis DGO-FMRP University of São Paulo How to choose a statistical test Francisco J. Candido dos Reis DGO-FMRP University of São Paulo Choosing the right test One of the most common queries in stats support is Which analysis should I use There

More information

Bivariate Analysis. Correlation. Correlation. Pearson's Correlation Coefficient. Variable 1. Variable 2

Bivariate Analysis. Correlation. Correlation. Pearson's Correlation Coefficient. Variable 1. Variable 2 Bivariate Analysis Variable 2 LEVELS >2 LEVELS COTIUOUS Correlation Used when you measure two continuous variables. Variable 2 2 LEVELS X 2 >2 LEVELS X 2 COTIUOUS t-test X 2 X 2 AOVA (F-test) t-test AOVA

More information

Module 10: Data Analysis and Interpretation

Module 10: Data Analysis and Interpretation IPDET Module 10: Data Analysis and Interpretation Intervention or Policy Subevaluations Qualitative vs. Quantitative Qualitative Quantitative Introduction Data Analysis Strategy Analyzing Qualitative Data

More information

Chapter 14: Analyzing Relationships Between Variables

Chapter 14: Analyzing Relationships Between Variables Chapter Outlines for: Frey, L., Botan, C., & Kreps, G. (1999). Investigating communication: An introduction to research methods. (2nd ed.) Boston: Allyn & Bacon. Chapter 14: Analyzing Relationships Between

More information

e = random error, assumed to be normally distributed with mean 0 and standard deviation σ

e = random error, assumed to be normally distributed with mean 0 and standard deviation σ 1 Linear Regression 1.1 Simple Linear Regression Model The linear regression model is applied if we want to model a numeric response variable and its dependency on at least one numeric factor variable.

More information

Module 5: Statistical Analysis

Module 5: Statistical Analysis Module 5: Statistical Analysis To answer more complex questions using your data, or in statistical terms, to test your hypothesis, you need to use more advanced statistical tests. This module reviews the

More information

About Single Factor ANOVAs

About Single Factor ANOVAs About Single Factor ANOVAs TABLE OF CONTENTS About Single Factor ANOVAs... 1 What is a SINGLE FACTOR ANOVA... 1 Single Factor ANOVA... 1 Calculating Single Factor ANOVAs... 2 STEP 1: State the hypotheses...

More information

Part Three. Cost Behavior Analysis

Part Three. Cost Behavior Analysis Part Three Cost Behavior Analysis Cost Behavior Cost behavior is the manner in which a cost changes as some related activity changes An understanding of cost behavior is necessary to plan and control costs

More information

Regression Analysis: A Complete Example

Regression Analysis: A Complete Example Regression Analysis: A Complete Example This section works out an example that includes all the topics we have discussed so far in this chapter. A complete example of regression analysis. PhotoDisc, Inc./Getty

More information

Statistics revision. Dr. Inna Namestnikova. Statistics revision p. 1/8

Statistics revision. Dr. Inna Namestnikova. Statistics revision p. 1/8 Statistics revision Dr. Inna Namestnikova inna.namestnikova@brunel.ac.uk Statistics revision p. 1/8 Introduction Statistics is the science of collecting, analyzing and drawing conclusions from data. Statistics

More information

Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression

Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression Unit 31 A Hypothesis Test about Correlation and Slope in a Simple Linear Regression Objectives: To perform a hypothesis test concerning the slope of a least squares line To recognize that testing for a

More information

DATA COLLECTION AND ANALYSIS

DATA COLLECTION AND ANALYSIS DATA COLLECTION AND ANALYSIS Quality Education for Minorities (QEM) Network HBCU-UP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. August 23, 2013 Objectives of the Discussion 2 Discuss

More information

Unit 31: One-Way ANOVA

Unit 31: One-Way ANOVA Unit 31: One-Way ANOVA Summary of Video A vase filled with coins takes center stage as the video begins. Students will be taking part in an experiment organized by psychology professor John Kelly in which

More information