Inferential Statistics. What are they? When would you use them?


 Bridget Lane
 1 years ago
 Views:
Transcription
1 Inferential Statistics What are they? When would you use them?
2 What are inferential statistics? Why learn about inferential statistics? Why use inferential statistics? When are inferential statistics utilized? Which types of inferential statistics are most commonly used and when? What is important for you to know about inferential statistics?
3 What are inferential statistics? Inferential statistics infer from the sample to the population They determine probability of characteristics of population based on the characteristics of your sample They help assess strength of the relationship between your independent (causal) variables, and you dependent (effect) variables.
4 Why learn about inferential statistics? BEFORE you use any intervention, you should do some research and determine if there is evidence that it works. (i.e., Does the head start program increase educational performance for low income children) BEFORE you work with any group, you want to base your judgments on research, not on stereotypes (i.e., You may want to know what proportion of Latino boys join gangs?) BEFORE you make recommendations, you want to understand the probabilities of success (i.e., What is the probability that a child will have success in school if they participate in your tutorial program?) Before you continue on with a program/intervention, you want to reassure yourself that this program is worth your time and effort. As you apply for grants, you want to ensure the grantees that you can implement a evidence based program. When making policy recommendations or participating in political advocacy, you want to provide empirical support that your intervention actually works.
5 Why use inferential statistics? Many toptiered journals will not publish articles that do NOT use inferential statistics. Allows you to generalize your findings to the larger population. Can determine not just what CAN happen, but what tends to happen in programs like yours. Helps assess strength of the relationship between your independent (causal) variables, and you dependent (effect) variables. Can assess the relative impact of various program inputs on your program outcomes/objectives.
6 When are inferential statistics utilized? Inferential statistics can only be used under the following conditions. You have a complete list of the members of the population. You draw a random sample from this population Using a preestablished formula, you determine that your sample size is large enough. Can you use inferential statistics even if you data do not meet these criteria? Inferential statistics can help determine strength of relationship within your sample. In other words, you can assess the strength of the impact of your independent variables (program inputs) on your outcomes (program outputs) IF it is very difficult to obtain a population list and/or draw a random sample, then you do the best you can with what you have. In this case, you can use inferential statistics and journals may publish it.
7 Which types of inferential statistics are most commonly used and when? The following types of inferential statistics are relatively common and relatively easy to interpret. One sample test of difference/one sample hypothesis test Confidence Interval Contingency Tables and Chi Square Statistic Ttest or Anova Pearson Correlation Bivariate Regression Multivariate Regression
8 First consider univariate statistics. One sample test of difference OR one sample hypothesis test When is it used? To compare responses of program participants on a pre and post test. To determine if implemented program had an impact on one particular outcome. How do you interpret it? If the probability is.05 or less that you will make a mistake in asserting there is a difference between the pre and posttest scores in the population, then you can assert that the program did make a difference on this outcome. In other words, your program is working.
9 First consider univariate statistics. Confidence Interval When is it used? To estimate a value/score in a population based on the score of the participants in your sample. How do you interpret it? A 95% confidence interval indicates you are 95% confident that you can predict/infer the value/score of a population within a specified range based on the value/score of your sample.
10 Next consider bivariate statistics. Contingency tables and ChiSquare statistic When are they used? When you have two categorical variables,. AND you want to know if they are related. (i.e., gender and score on outcome measurement). How do you interpret them? The chisquare statistics can be used to determine the strength of the relationship (i.e., Does knowing someone s gender help you predict their outcome score/value). If the probability associated with the chisquare statistics is.05 of less, then you can assert that the independent variable can be used to predict scores on the dependent or outcome variable. You can also use the contingency table to compare the actual scores across the independent variable on the dependent variable or outcome measurement (i.e., compare the number/percent of males who agreed that the program had a positive impact on their lives to the percent of females who agreed.)
11 Next consider bivariate statistics. Ttest or Anova When is it used? When you have a categorical and continuous variable. And you want to compare mean scores of two or more groups (i.e., you want to compare mean GRP of students you have tutored across race). How do you interpret it? The Ttest or F statistic can be used to determine if the groups have significantly different means. If the probability associated with the F statistics is.05 or less then we can assert that there is a difference in the means.
12 Next consider bivariate statistics. Pearson Correlation When is it used? When you have a continuous independent variable and a continuous dependent variable. How do you interpret it? When the probability associated with the T statistics is.05 of less then you can assume there is a relationship between the dependent and independent variable. For instance you may want to know if the number of hours participants spend in your program is positively related to their scores on school exams.
13 Next consider bivariate statistics. Bivariate Regression When is it used? When you have a continuous independent variable and a continuous dependent (outcome) variable. For instance, you may want to know if the number of hours participants spend in your program is positively related to their scores on school exams. How do you interpret it? When the probability associated with the F statistic is.05 or less then you can assume there is a relationship between the dependent and the independent variable. * NOTE The Pearson Correlation and Bivariate regression are very similar.
14 Finally let us consider multivariate statistics Elaborated ChiSquare statistic When is it used? When you have more than one independent categorical variable, and one dependent categorical variable. How is it interpreted? You divide one of the independent variables into two groups and then do a chi square for each group (i.e., divide gender into males and females, then do a chisquare of males and one for females. So for females you can do a chisquare of outcome measurement by race, and then do the same for males.)
15 Multivariate Regression When is it used? Multivariate regression is used you have more than one independent (causal) variable and one dependent (effect or outcome) variable. You not only want to know if you intervention has an impact on the outcome, but you want to know WHICH aspects of your intervention has an impact and/or the relative impact of different aspects of your intervention. How do you interpret it? If the probability associated with the F statistic is.05 of less, then you can If the probability associated with the T statistic for each of the independent variables is.05 or less, then you can assert that independent variable has an impact on the outcome, independent of the other variables. The value of the T statistics can be compared across the independent variables to determine the relative value of each.
16 What is important for you to know about inferential statistics? You should be able to 1. Read and understand computer printouts 2. Construct tables and graphs from the computer printouts. 3. Interpret and explain these tables and graphs to an audience. 4. Make wise decisions based on valid and accurate data.
17 What if you NEVER intend to use Inferential Statistics? All of us are consumers of information We can learn about inferential statistics and be wiser consumers of information. We are empowered, and have the tools to determine if the information we are reading is accurate/valid. If you implement programs, you are ethically bound to your participants to be able to accurately measure the outcomes of your intervention. If you use government/foundation funding to implement your programs, then you are responsible for using their monies wisely and efficiently.
18 Dr. Carol Albrecht USU Extension Specialist
Contingency Tables and the Chi Square Statistic. Interpreting Computer Printouts and Constructing Tables
Contingency Tables and the Chi Square Statistic Interpreting Computer Printouts and Constructing Tables Contingency Tables/Chi Square Statistics What are they? A contingency table is a table that shows
More informationChapter Eight: Quantitative Methods
Chapter Eight: Quantitative Methods RESEARCH DESIGN Qualitative, Quantitative, and Mixed Methods Approaches Third Edition John W. Creswell Chapter Outline Defining Surveys and Experiments Components of
More informationConstructing and Interpreting Confidence Intervals
Constructing and Interpreting Confidence Intervals Confidence Intervals In this power point, you will learn: Why confidence intervals are important in evaluation research How to interpret a confidence
More informationIs it statistically significant? The chisquare test
UAS Conference Series 2013/14 Is it statistically significant? The chisquare test Dr Gosia Turner Student Data Management and Analysis 14 September 2010 Page 1 Why chisquare? Tests whether two categorical
More informationSection Format Day Begin End Building Rm# Instructor. 001 Lecture Tue 6:45 PM 8:40 PM Silver 401 Ballerini
NEW YORK UNIVERSITY ROBERT F. WAGNER GRADUATE SCHOOL OF PUBLIC SERVICE Course Syllabus Spring 2016 Statistical Methods for Public, Nonprofit, and Health Management Section Format Day Begin End Building
More informationCourse 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, McGrawHill/Irwin, 2010, ISBN: 9780077384470 [This
More informationWhen to Use a Particular Statistical Test
When to Use a Particular Statistical Test Central Tendency Univariate Descriptive Mode the most commonly occurring value 6 people with ages 21, 22, 21, 23, 19, 21  mode = 21 Median the center value the
More informationBusiness 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, McGrawHill/Irwin, 2008, ISBN: 9780073319889. Required Computing
More informationII. 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 informationDescriptive Statistics
Descriptive Statistics Primer Descriptive statistics Central tendency Variation Relative position Relationships Calculating descriptive statistics Descriptive Statistics Purpose to describe or summarize
More informationSimple 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 informationChapter 15 Multiple Choice Questions (The answers are provided after the last question.)
Chapter 15 Multiple Choice Questions (The answers are provided after the last question.) 1. What is the median of the following set of scores? 18, 6, 12, 10, 14? a. 10 b. 14 c. 18 d. 12 2. Approximately
More informationThe Dummy s Guide to Data Analysis Using SPSS
The Dummy s Guide to Data Analysis Using SPSS Mathematics 57 Scripps College Amy Gamble April, 2001 Amy Gamble 4/30/01 All Rights Rerserved TABLE OF CONTENTS PAGE Helpful Hints for All Tests...1 Tests
More informationUnit 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 informationVariables 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 informationOrganizing Your Approach to a Data Analysis
Biost/Stat 578 B: Data Analysis Emerson, September 29, 2003 Handout #1 Organizing Your Approach to a Data Analysis The general theme should be to maximize thinking about the data analysis and to minimize
More informationUniversally Accepted Lean Six Sigma Body of Knowledge for Green Belts
Universally Accepted Lean Six Sigma Body of Knowledge for Green Belts The IASSC Certified Green Belt Exam was developed and constructed based on the topics within the body of knowledge listed here. Questions
More informationHYPOTHESIS TESTING: CONFIDENCE INTERVALS, TTESTS, ANOVAS, AND REGRESSION
HYPOTHESIS TESTING: CONFIDENCE INTERVALS, TTESTS, ANOVAS, AND REGRESSION HOD 2990 10 November 2010 Lecture Background This is a lightning speed summary of introductory statistical methods for senior undergraduate
More informationGraphing Data Presentation of Data in Visual Forms
Graphing Data Presentation of Data in Visual Forms Purpose of Graphing Data Audience Appeal Provides a visually appealing and succinct representation of data and summary statistics Provides a visually
More informationUniversity of Maryland School of Medicine Master of Public Health Program. Evaluation of Public Health Competencies
Semester/Year of Graduation University of Maryland School of Medicine Master of Public Health Program Evaluation of Public Health Competencies Students graduating with an MPH degree, and planning to work
More informationMeasurement & Data Analysis. On the importance of math & measurement. Steps Involved in Doing Scientific Research. Measurement
Measurement & Data Analysis Overview of Measurement. Variability & Measurement Error.. Descriptive vs. Inferential Statistics. Descriptive Statistics. Distributions. Standardized Scores. Graphing Data.
More informationSPSS Tests for Versions 9 to 13
SPSS Tests for Versions 9 to 13 Chapter 2 Descriptive Statistic (including median) Choose Analyze Descriptive statistics Frequencies... Click on variable(s) then press to move to into Variable(s): list
More informationChapter 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 informationThe University of Texas at Austin School of Social Work SOCIAL WORK STATISTICS
1 The University of Texas at Austin School of Social Work SOCIAL WORK STATISTICS Course Number: SW 318 Instructor: Michael Bergman, Ph.D. Unique Number: 65190 Office Number: SSW 1.214 (IT Classroom) Semester:
More informationStatistical Analysis RSCH 665 Eagle Vision Classroom  Blended Course Syllabus
Statistical Analysis RSCH 665 Eagle Vision Classroom  Blended Course Syllabus Credit Hours: 3 Credits Academic Term: May 2016; 31 May 2016 01 August 2016 Meetings: Fri 18002200 Sat/Sun 09001400 (GMT+1)
More informationCHAPTER 11 CHISQUARE AND F DISTRIBUTIONS
CHAPTER 11 CHISQUARE AND F DISTRIBUTIONS CHISQUARE TESTS OF INDEPENDENCE (SECTION 11.1 OF UNDERSTANDABLE STATISTICS) In chisquare tests of independence we use the hypotheses. H0: The variables are independent
More informationDATA ANALYSIS. QEM Network HBCUUP Fundamentals of Education Research Workshop Gerunda B. Hughes, Ph.D. Howard University
DATA ANALYSIS QEM Network HBCUUP 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 informationDirections 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 informationSPSS Bivariate Statistics
SPSS Bivariate Statistics Social Science Research Lab American University, Washington, D.C. Web. www.american.edu/provost/ctrl/pclabs.cfm Tel. x3862 Email. SSRL@American.edu Course Objectives In this tutorial
More informationSPSS Guide: Regression Analysis
SPSS Guide: Regression Analysis I put this together to give you a stepbystep 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 informationSTA201TE. 5. Measures of relationship: correlation (5%) Correlation coefficient; Pearson r; correlation and causation; proportion of common variance
Principles of Statistics STA201TE This TECEP is an introduction to descriptive and inferential statistics. Topics include: measures of central tendency, variability, correlation, regression, hypothesis
More informationSchool of Mathematics and Science MATH 153 Introduction to Statistical Methods Section: WE1 & WE2
CCBC Essex School of Mathematics and Science MATH 153 Introduction to Statistical Methods Section: WE1 & WE2 CLASSROOM LOCATION: SEMESTER: Fall 2009 INSTRUCTOR: DONNA TUPPER OFFICE LOCATION: F413 (or
More informationStudents' Opinion about Universities: The Faculty of Economics and Political Science (Case Study)
Cairo University Faculty of Economics and Political Science Statistics Department English Section Students' Opinion about Universities: The Faculty of Economics and Political Science (Case Study) Prepared
More informationClass 19: Two Way Tables, Conditional Distributions, ChiSquare (Text: Sections 2.5; 9.1)
Spring 204 Class 9: Two Way Tables, Conditional Distributions, ChiSquare (Text: Sections 2.5; 9.) Big Picture: More than Two Samples In Chapter 7: We looked at quantitative variables and compared the
More informationSilvermine House Steenberg Office Park, Tokai 7945 Cape Town, South Africa Telephone: +27 21 702 4666 www.spsssa.com
SPSSSA Silvermine House Steenberg Office Park, Tokai 7945 Cape Town, South Africa Telephone: +27 21 702 4666 www.spsssa.com SPSSSA Training Brochure 2009 TABLE OF CONTENTS 1 SPSS TRAINING COURSES FOCUSING
More informationIntroduction to Analysis of Variance (ANOVA) Limitations of the ttest
Introduction to Analysis of Variance (ANOVA) The Structural Model, The Summary Table, and the One Way ANOVA Limitations of the ttest Although the ttest is commonly used, it has limitations Can only
More informationSPSS Resources. 1. See website (readings) for SPSS tutorial & Stats handout
Analyzing Data SPSS Resources 1. See website (readings) for SPSS tutorial & Stats handout Don t have your own copy of SPSS? 1. Use the libraries to analyze your data 2. Download a trial version of SPSS
More informationAn introduction to IBM SPSS Statistics
An introduction to IBM SPSS Statistics Contents 1 Introduction... 1 2 Entering your data... 2 3 Preparing your data for analysis... 10 4 Exploring your data: univariate analysis... 14 5 Generating descriptive
More informationWhy Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization. Learning Goals. GENOME 560, Spring 2012
Why Taking This Course? Course Introduction, Descriptive Statistics and Data Visualization GENOME 560, Spring 2012 Data are interesting because they help us understand the world Genomics: Massive Amounts
More informationJanuary 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 informationIBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA
CALIFORNIA STATE UNIVERSITY, LOS ANGELES INFORMATION TECHNOLOGY SERVICES IBM SPSS Statistics 20 Part 4: ChiSquare and ANOVA Summer 2013, Version 2.0 Table of Contents Introduction...2 Downloading the
More informationAn introduction to using Microsoft Excel for quantitative data analysis
Contents An introduction to using Microsoft Excel for quantitative data analysis 1 Introduction... 1 2 Why use Excel?... 2 3 Quantitative data analysis tools in Excel... 3 4 Entering your data... 6 5 Preparing
More informationRoadmap to Data Analysis. Introduction to the Series, and I. Introduction to Statistical ThinkingA (Very) Short Introductory Course for Agencies
Roadmap to Data Analysis Introduction to the Series, and I. Introduction to Statistical ThinkingA (Very) Short Introductory Course for Agencies Objectives of the Series Roadmap to Data Analysis Provide
More informationElementary 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 informationMASTER COURSE SYLLABUSPROTOTYPE PSYCHOLOGY 2317 STATISTICAL METHODS FOR THE BEHAVIORAL SCIENCES
MASTER COURSE SYLLABUSPROTOTYPE THE PSYCHOLOGY DEPARTMENT VALUES ACADEMIC FREEDOM AND THUS OFFERS THIS MASTER SYLLABUSPROTOTYPE ONLY AS A GUIDE. THE INSTRUCTORS ARE FREE TO ADAPT THEIR COURSE SYLLABI
More informationSydney Roberts Predicting Age Group Swimmers 50 Freestyle Time 1. 1. Introduction p. 2. 2. Statistical Methods Used p. 5. 3. 10 and under Males p.
Sydney Roberts Predicting Age Group Swimmers 50 Freestyle Time 1 Table of Contents 1. Introduction p. 2 2. Statistical Methods Used p. 5 3. 10 and under Males p. 8 4. 11 and up Males p. 10 5. 10 and under
More informationBIOM611 Biological Data Analysis
BIOM611 Biological Data Analysis Spring, 2015 Tentative Syllabus Introduction BIOMED611 is a ½ unit course required for all 1 st year BGS students (except GCB students). It will provide an introduction
More informationIntroduction 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 informationQMB 3302 Business Analytics CRN 10251 Spring 2015 T R  11:00am  12:15pm  Lutgert Hall 2209
QMB 3302 Business Analytics CRN 10251 Spring 2015 T R  11:00am  12:15pm  Lutgert Hall 2209 Elias T. Kirche, Ph.D. Associate Professor Department of Information Systems and Operations Management Lutgert
More informationRARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS
RARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS I. Basic Course Information A. Course Number and Title: MATH 111H Statistics II Honors B. New or Modified Course:
More informationIntroduction to Statistics and Quantitative Research Methods
Introduction to Statistics and Quantitative Research Methods Purpose of Presentation To aid in the understanding of basic statistics, including terminology, common terms, and common statistical methods.
More informationResearch Methods & Experimental Design
Research Methods & Experimental Design 16.422 Human Supervisory Control April 2004 Research Methods Qualitative vs. quantitative Understanding the relationship between objectives (research question) and
More informationFairfield Public Schools
Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity
More informationChapter 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 informationAP Statistics 2011 FreeResponse Questions
AP Statistics 2011 FreeResponse Questions About the College Board The College Board is a missiondriven notforprofit organization that connects students to college success and opportunity. Founded in
More informationSTATISTICAL ANALYSIS WITH EXCEL COURSE OUTLINE
STATISTICAL ANALYSIS WITH EXCEL COURSE OUTLINE Perhaps Microsoft has taken pains to hide some of the most powerful tools in Excel. These addins tools work on top of Excel, extending its power and abilities
More informationRECRUITERS PRIORITIES IN PLACING MBA FRESHER: AN EMPIRICAL ANALYSIS
RECRUITERS PRIORITIES IN PLACING MBA FRESHER: AN EMPIRICAL ANALYSIS Miss Sangeeta Mohanty Assistant Professor, Academy of Business Administration, Angaragadia, Balasore, Orissa, India ABSTRACT Recruitment
More informationGood luck! BUSINESS STATISTICS FINAL EXAM INSTRUCTIONS. Name:
Glo bal Leadership M BA BUSINESS STATISTICS FINAL EXAM Name: INSTRUCTIONS 1. Do not open this exam until instructed to do so. 2. Be sure to fill in your name before starting the exam. 3. You have two hours
More informationSimulating ChiSquare Test Using Excel
Simulating ChiSquare Test Using Excel Leslie Chandrakantha John Jay College of Criminal Justice of CUNY Mathematics and Computer Science Department 524 West 59 th Street, New York, NY 10019 lchandra@jjay.cuny.edu
More informationData Mining Techniques Chapter 5: The Lure of Statistics: Data Mining Using Familiar Tools
Data Mining Techniques Chapter 5: The Lure of Statistics: Data Mining Using Familiar Tools Occam s razor.......................................................... 2 A look at data I.........................................................
More informationCOMPARISONS OF CUSTOMER LOYALTY: PUBLIC & PRIVATE INSURANCE COMPANIES.
277 CHAPTER VI COMPARISONS OF CUSTOMER LOYALTY: PUBLIC & PRIVATE INSURANCE COMPANIES. This chapter contains a full discussion of customer loyalty comparisons between private and public insurance companies
More informationSimple 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 informationIntro to Parametric & Nonparametric Statistics
Intro to Parametric & Nonparametric Statistics Kinds & definitions of nonparametric statistics Where parametric stats come from Consequences of parametric assumptions Organizing the models we will cover
More informationPsych. Research 1 Guide to SPSS 11.0
SPSS GUIDE 1 Psych. Research 1 Guide to SPSS 11.0 I. What is SPSS: SPSS (Statistical Package for the Social Sciences) is a data management and analysis program. It allows us to store and analyze very large
More informationCleveland State University NAL/PAD/PDD/UST 504 Section 51 Levin College of Urban Affairs Fall, 2009 W 6 to 9:50 pm UR 108
Cleveland State University NAL/PAD/PDD/UST 504 Section 51 Levin College of Urban Affairs Fall, 2009 W 6 to 9:50 pm UR 108 Department of Urban Studies Email: w.weizer @csuohio.edu Instructor: Winifred Weizer
More informationDescription. Textbook. Grading. Objective
EC151.02 Statistics for Business and Economics (MWF 8:008:50) Instructor: Chiu Yu Ko Office: 462D, 21 Campenalla Way Phone: 26093 Email: kocb@bc.edu Office Hours: by appointment Description This course
More informationOverview of NonParametric Statistics PRESENTER: ELAINE EISENBEISZ OWNER AND PRINCIPAL, OMEGA STATISTICS
Overview of NonParametric Statistics PRESENTER: ELAINE EISENBEISZ OWNER AND PRINCIPAL, OMEGA STATISTICS About Omega Statistics Private practice consultancy based in Southern California, Medical and Clinical
More informationEducation & Training Plan. Accounting Math Professional Certificate Program with Externship
Office of Professional & Continuing Education 301 OD Smith Hall Auburn, AL 36849 http://www.auburn.edu/mycaa Contact: Shavon Williams 3348443108; szw0063@auburn.edu Auburn University is an equal opportunity
More informationAdditional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jintselink/tselink.htm
Mgt 540 Research Methods Data Analysis 1 Additional sources Compilation of sources: http://lrs.ed.uiuc.edu/tseportal/datacollectionmethodologies/jintselink/tselink.htm http://web.utk.edu/~dap/random/order/start.htm
More informationCONTENTS PREFACE 1 INTRODUCTION 1 2 DATA VISUALIZATION 19
PREFACE xi 1 INTRODUCTION 1 1.1 Overview 1 1.2 Definition 1 1.3 Preparation 2 1.3.1 Overview 2 1.3.2 Accessing Tabular Data 3 1.3.3 Accessing Unstructured Data 3 1.3.4 Understanding the Variables and Observations
More informationConsider a study in which. How many subjects? The importance of sample size calculations. An insignificant effect: two possibilities.
Consider a study in which How many subjects? The importance of sample size calculations Office of Research Protections Brown Bag Series KB Boomer, Ph.D. Director, boomer@stat.psu.edu A researcher conducts
More informationParticipant Observation
Participant Observation Purpose Observe Human Social Behavior. Often used to observe behavior over time. This data collection technique is used when you want to Look at process how something occurs (i.e.,
More informationSurvey Data Analysis. Qatar University. Dr. Kenneth M.Coleman (Ken.Coleman@marketstrategies.com)  University of Michigan
The following slides are the property of their authors and are provided on this website as a public service. Please do not copy or redistribute these slides without the written permission of all of the
More informationAssociation Between Variables
Contents 11 Association Between Variables 767 11.1 Introduction............................ 767 11.1.1 Measure of Association................. 768 11.1.2 Chapter Summary.................... 769 11.2 Chi
More informationSPSS Guide Howto, Tips, Tricks & Statistical Techniques
SPSS Guide Howto, Tips, Tricks & Statistical Techniques Support for the course Research Methodology for IB Also useful for your BSc or MSc thesis March 2014 Dr. Marijke Leliveld Jacob Wiebenga, MSc CONTENT
More informationData analysis process
Data analysis process Data collection and preparation Collect data Prepare codebook Set up structure of data Enter data Screen data for errors Exploration of data Descriptive Statistics Graphs Analysis
More informationCurriculum  Doctor of Philosophy
Curriculum  Doctor of Philosophy CORE COURSES Pharm 545546.Pharmacoeconomics, Healthcare Systems Review. (3, 3) Exploration of the cultural foundations of pharmacy. Development of the present state of
More informationLAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE
LAGUARDIA COMMUNITY COLLEGE CITY UNIVERSITY OF NEW YORK DEPARTMENT OF MATHEMATICS, ENGINEERING, AND COMPUTER SCIENCE MAT 119 STATISTICS AND ELEMENTARY ALGEBRA 5 Lecture Hours, 2 Lab Hours, 3 Credits Pre
More informationEconomic Statistics (ECON2006), Statistics and Research Design in Psychology (PSYC2010), Survey Design and Analysis (SOCI2007)
COURSE DESCRIPTION Title Code Level Semester Credits 3 Prerequisites Post requisites Introduction to Statistics ECON1005 (EC160) I I None Economic Statistics (ECON2006), Statistics and Research Design
More informationIntroduction to Statistics Used in Nursing Research
Introduction to Statistics Used in Nursing Research Laura P. Kimble, PhD, RN, FNPC, FAAN Professor and Piedmont Healthcare Endowed Chair in Nursing Georgia Baptist College of Nursing Of Mercer University
More informationData Analysis in SPSS. February 21, 2004. If you wish to cite the contents of this document, the APA reference for them would be
Data Analysis in SPSS Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 354870348 Heather Claypool Department of Psychology Miami University
More informationBasic Concepts in Research and Data Analysis
Basic Concepts in Research and Data Analysis Introduction: A Common Language for Researchers...2 Steps to Follow When Conducting Research...3 The Research Question... 3 The Hypothesis... 4 Defining the
More informationAP Statistics: Syllabus 1
AP Statistics: Syllabus 1 Scoring Components SC1 The course provides instruction in exploring data. 4 SC2 The course provides instruction in sampling. 5 SC3 The course provides instruction in experimentation.
More informationElementary Statistics Sample Exam #3
Elementary Statistics Sample Exam #3 Instructions. No books or telephones. Only the supplied calculators are allowed. The exam is worth 100 points. 1. A chi square goodness of fit test is considered to
More informationTeaching Statistics with Fathom
Teaching Statistics with Fathom UCB Extension X369.6 (2 semester units in Education) COURSE DESCRIPTION This is a professionallevel, moderated online course in the use of Fathom Dynamic Data software
More informationElements of statistics (MATH04871)
Elements of statistics (MATH04871) Prof. Dr. Dr. K. Van Steen University of Liège, Belgium December 10, 2012 Introduction to Statistics Basic Probability Revisited Sampling Exploratory Data Analysis 
More informationIntroduction Course in SPSS  Evening 1
ETH Zürich Seminar für Statistik Introduction Course in SPSS  Evening 1 Seminar für Statistik, ETH Zürich All data used during the course can be downloaded from the following ftp server: ftp://stat.ethz.ch/u/sfs/spsskurs/
More informationThis chapter discusses some of the basic concepts in inferential statistics.
Research Skills for Psychology Majors: Everything You Need to Know to Get Started Inferential Statistics: Basic Concepts This chapter discusses some of the basic concepts in inferential statistics. Details
More informationSPSS Explore procedure
SPSS Explore procedure One useful function in SPSS is the Explore procedure, which will produce histograms, boxplots, stemandleaf plots and extensive descriptive statistics. To run the Explore procedure,
More informationLecture 1: Review and Exploratory Data Analysis (EDA)
Lecture 1: Review and Exploratory Data Analysis (EDA) Sandy Eckel seckel@jhsph.edu Department of Biostatistics, The Johns Hopkins University, Baltimore USA 21 April 2008 1 / 40 Course Information I Course
More informationThe Correlation between Information Technology Use and Students Grades in Yanbu University College
The Correlation between Information Technology Use and Students Grades in Yanbu University College Dr. Abdulkareem Alalwani Yanbu University College (SAUDI ARABIA) Abstract This study considers the degree
More informationSCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES
SCHOOL OF HEALTH AND HUMAN SCIENCES Using SPSS Topics addressed today: 1. Differences between groups 2. Graphing Use the s4data.sav file for the first part of this session. DON T FORGET TO RECODE YOUR
More informationUNIT 1: COLLECTING DATA
Core Probability and Statistics Probability and Statistics provides a curriculum focused on understanding key data analysis and probabilistic concepts, calculations, and relevance to realworld applications.
More informationEXCEL Analysis TookPak [Statistical Analysis] 1. First of all, check to make sure that the Analysis ToolPak is installed. Here is how you do it:
EXCEL Analysis TookPak [Statistical Analysis] 1 First of all, check to make sure that the Analysis ToolPak is installed. Here is how you do it: a. From the Tools menu, choose AddIns b. Make sure Analysis
More informationAdverse Impact and Test Validation Book Series: Multiple Regression. Introduction. Comparison of Compensation using
Adverse Impact and Test Validation Book Series: Multiple Regression Using Multiple Regression to Examine Compensation Practices Introduction Reasons for Investigating Pay Equity: The Equal Pay Act of 1963
More informationQuantitative Analysis for Business BSNS102. Course Outline Semester One 2014
Quantitative Analysis for Business BSNS102 Course Outline Semester One 2014 Quantitative Analysis for Business This paper covers descriptive and inferential statistics for students majoring in Commerce,
More informationStudy Guide for the Final Exam
Study Guide for the Final Exam When studying, remember that the computational portion of the exam will only involve new material (covered after the second midterm), that material from Exam 1 will make
More informationStatistics, Research, & SPSS: The Basics
Statistics, Research, & SPSS: The Basics SPSS (Statistical Package for the Social Sciences) is a software program that makes the calculation and presentation of statistics relatively easy. It is an incredibly
More informationEducation & Training Plan Accounting Math Professional Certificate Program with Externship
University of Texas at El Paso Professional and Public Programs 500 W. University Kelly Hall Ste. 212 & 214 El Paso, TX 79968 http://www.ppp.utep.edu/ Contact: Sylvia Monsisvais 9157477578 samonsisvais@utep.edu
More information