# T-test & factor analysis

Save this PDF as:

Size: px
Start display at page:

## Transcription

1 Parametric tests T-test & factor analysis Better than non parametric tests Stringent assumptions More strings attached Assumes population distribution of sample is normal Major problem Alternatives Continue using parametric test if the sample is large or enough evidence available to prove the usage Transforming and manipulating variables Use non parametric test Dr. Paurav Shukla t-test Tests used for significant differences between groups Independent sample t-test Paired sample t-test One-way ANOVA (between groups) One-way ANOVA (repeated groups) Two-way ANOVA (between groups) MANOVA Used when they are two groups only Compares the mean score on some continuous variable Largely used in measuring before after effect Also called intervention effect Option 1: Same sample over a period of time Option 2: Two different groups at a single point of time Assumptions associated with t-test Population distribution of sample is normal Probability (random) sampling Level of measurement Dependent variable is continuous Observed or measured data must be independent If interaction is unavoidable use a stringent alpha value (p<.01) Homogeneity of variance Assumes that samples are obtained from populations of equal variance ANOVA is reasonably robust against this Why t-test is important? Highly used technique for hypothesis testing Can lead to wrong conclusions Type 1 error Reject null hypothesis instead of accepting When we assume there is a difference between groups, when it is not Type 2 error Accept null hypothesis instead of rejecting When we assume there is no difference between groups, when there is Solution Interdependency between both errors Selection of alpha level Dr. Paurav Shukla 1

2 Factors influencing power of t-test Procedure for independent sample t-test Sample size Strength of interdependency between dependent and independent variable (Strength of Association or Effect Size) Alpha level Compare means Independent sample t-test Interpreting independent samples t-test Calculating the effect size Group statistics Look for N (missing values) Independent samples test Levene s test If sig value is higher than 0.05 use equal variance assumed If sig value is lower than 0.05 use equal variances not assumed Assessing difference between groups If the sig (2-tailed) is equal or less than 0.05 There is a significant difference in the mean scores If the sig (2-tailed) is great than 0.05 There is no significant difference between the two groups SPSS does not calculate Eta squared to measure effect size for t-test Calculation Eta squared = t 2 + (N1 + N2 2) Interpretation values 0.01 = Small effect 0.06 = Moderate effect 0.14 = Large effect t 2 Paired sample t-test Interpreting paired sample t-test Compare means Paired samples t-test Determining overall significance If the sig (2-tailed) is less than 0.05 Significant difference between two scores If the sig (2-tailed) is higher than 0.05 No significant difference between two scores Comparing mean values Mean values Effect size t 2 Eta squared = t 2 + N - 1 Dr. Paurav Shukla 2

3 Non-parametric alternatives Independent sample t-test Mann-Whitney U test Instead of comparing mean it compares medians Procedure Non-parametric tests 2 Independent samples Paired sample t-test Wilcoxon signed rank test Procedure Non-parametric tests 2 Related samples Factor Analysis Session overview Basic concept Basic Concept Factor Analysis Model Types of factor analysis Statistics Associated with Factor Analysis Conducting factor analysis Applications of factor analysis A data reduction technique designed to represent a wide range of attributes on a smaller number of dimensions. Factor analysis is an interdependence technique in that an entire set of interdependent relationships is examined without making the distinction between dependent and independent variables. Factor analysis is used in the following circumstances: To identify underlying dimensions, or factors, that explain the correlations among a set of variables. To identify a new, smaller, set of uncorrelated variables to replace the original set of correlated variables in subsequent multivariate analysis (regression or discriminant analysis). To identify a smaller set of salient variables from a larger set for use in subsequent multivariate analysis. Standard Model Types of factor analysis Mathematically, each variable is expressed as a linear combination of underlying factors. The covariation among the variables is described in terms of a small number of common factors plus a unique factor for each variable. If the variables are standardized, the factor model may be represented as: Xi = Ai 1F1 + Ai 2F2 + Ai 3F AimFm + ViUi where Xi = i th standardized variable Aij = standardized multiple regression coefficient of variable i on common factor j F = common factor Vi = standardized regression coefficient of variable i on unique factor i Ui = the unique factor for variable i m = number of common factors Exploratory factor analysis Largely known as Principal Components Analysis (PCA) Confirmatory factor analysis Structural Equation Modelling Dr. Paurav Shukla 3

6 What shall the component be called? Rotated Component Matrix a Component Status not related to me Indicate wealth Status is important to me Status enhance my.764 image When a variable is loaded on two or more factors include it with the factor where it has highest value Status not related to me Indicate wealth Status is important to me Status enhance my image Willing to try new drink Willing to try new drink Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 6 iterations. Calculating component scores Component Plot in Rotated Space Helps in brand level comparisons n t e 0.0 o n p m o C Indicate_wealth Symbol_of_success Gain_respect Interest_in_status S_import_me S_enhan_ima Show_who_I_am Presence_o_others Try_new_drink Component Symbol_of_prestige 1.0 Value Component -1.0 Because it s a 3 factor solution we are getting a 3 dimensional plot. What if we get a 2 factor solution? How to get this represented in 2 dimension plot so it is easier to understand? Tricks of the trade Applications of factor analysis Self-determining number of factors Combining reliability analysis (Cronbach s Alpha) A more concise representation of the marketing situation and hence communication may be enhanced Fewer questions may be required on future surveys Market segmentation and identifying the underlying variables on which to group customers Identifying brand attributes that influence customer choice Identifying media consumption habits of consumers Perceptual maps become feasible Dr. Paurav Shukla 6

7 Further questions Confirmatory factor analysis What if we want to measure a hypothesis or theories concerning the structure underlying a set of variables? Such as, in our case do all these variables affect the psychological association of a brand and which in turn would affect status consumption? to be a popular person in groups. to show who I am. to be a symbol of success. to be a symbol of prestige. to indicate my wealth. to be noticed by others. to indicate my achievement. to be appreciated by others. because status interests me. because status is important to me. because status enhances my image. because I am interested in new alcoholic beverages with status. because I would pay more for an alcoholic beverage if it had status. because the status of an alcoholic beverage is irrelevant to me. to increase my own value from others point of view. to be more attractive than others. Psychological association Status consumption Robust but complex Used by a lot of advance level researchers The in phenomenon in research Software: Lisrel or Amos (SPSS) and several others Confirmatory factor analysis (Structural Equation Modelling) Dr. Paurav Shukla 7

### Factor Analysis. Principal components factor analysis. Use of extracted factors in multivariate dependency models

Factor Analysis Principal components factor analysis Use of extracted factors in multivariate dependency models 2 KEY CONCEPTS ***** Factor Analysis Interdependency technique Assumptions of factor analysis

### SPSS ADVANCED ANALYSIS WENDIANN SETHI SPRING 2011

SPSS ADVANCED ANALYSIS WENDIANN SETHI SPRING 2011 Statistical techniques to be covered Explore relationships among variables Correlation Regression/Multiple regression Logistic regression Factor analysis

### Doing Quantitative Research 26E02900, 6 ECTS Lecture 2: Measurement Scales. Olli-Pekka Kauppila Rilana Riikkinen

Doing Quantitative Research 26E02900, 6 ECTS Lecture 2: Measurement Scales Olli-Pekka Kauppila Rilana Riikkinen Learning Objectives 1. Develop the ability to assess a quality of measurement instruments

### 5.2 Customers Types for Grocery Shopping Scenario

------------------------------------------------------------------------------------------------------- CHAPTER 5: RESULTS AND ANALYSIS -------------------------------------------------------------------------------------------------------

### Chapter 7 Factor Analysis SPSS

Chapter 7 Factor Analysis SPSS Factor analysis attempts to identify underlying variables, or factors, that explain the pattern of correlations within a set of observed variables. Factor analysis is often

### Exploratory Factor Analysis of Demographic Characteristics of Antenatal Clinic Attendees and their Association with HIV Risk

Doi:10.5901/mjss.2014.v5n20p303 Abstract Exploratory Factor Analysis of Demographic Characteristics of Antenatal Clinic Attendees and their Association with HIV Risk Wilbert Sibanda Philip D. Pretorius

### APPRAISAL OF FINANCIAL AND ADMINISTRATIVE FUNCTIONING OF PUNJAB TECHNICAL UNIVERSITY

APPRAISAL OF FINANCIAL AND ADMINISTRATIVE FUNCTIONING OF PUNJAB TECHNICAL UNIVERSITY In the previous chapters the budgets of the university have been analyzed using various techniques to understand the

### Common factor analysis

Common factor analysis This is what people generally mean when they say "factor analysis" This family of techniques uses an estimate of common variance among the original variables to generate the factor

### FACTOR ANALYSIS EXPLORATORY APPROACHES. Kristofer Årestedt

FACTOR ANALYSIS EXPLORATORY APPROACHES Kristofer Årestedt 2013-04-28 UNIDIMENSIONALITY Unidimensionality imply that a set of items forming an instrument measure one thing in common Unidimensionality is

### Introduction to Principal Components and FactorAnalysis

Introduction to Principal Components and FactorAnalysis Multivariate Analysis often starts out with data involving a substantial number of correlated variables. Principal Component Analysis (PCA) is a

### Research 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

### ANSWERS TO EXERCISES AND REVIEW QUESTIONS

ANSWERS TO EXERCISES AND REVIEW QUESTIONS PART FIVE: STATISTICAL TECHNIQUES TO COMPARE GROUPS Before attempting these questions read through the introduction to Part Five and Chapters 16-21 of the SPSS

### Data 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

### Factor Analysis. Chapter 420. Introduction

Chapter 420 Introduction (FA) is an exploratory technique applied to a set of observed variables that seeks to find underlying factors (subsets of variables) from which the observed variables were generated.

### Principal Components Analysis (PCA)

Principal Components Analysis (PCA) Janette Walde janette.walde@uibk.ac.at Department of Statistics University of Innsbruck Outline I Introduction Idea of PCA Principle of the Method Decomposing an Association

### DATA ANALYSIS AND INTERPRETATION OF EMPLOYEES PERSPECTIVES ON HIGH ATTRITION

DATA ANALYSIS AND INTERPRETATION OF EMPLOYEES PERSPECTIVES ON HIGH ATTRITION Analysis is the key element of any research as it is the reliable way to test the hypotheses framed by the investigator. This

### Overview of Factor Analysis

Overview of Factor Analysis Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 35487-0348 Phone: (205) 348-4431 Fax: (205) 348-8648 August 1,

### A Brief Introduction to SPSS Factor Analysis

A Brief Introduction to SPSS Factor Analysis SPSS has a procedure that conducts exploratory factor analysis. Before launching into a step by step example of how to use this procedure, it is recommended

### INTERPRETING THE REPEATED-MEASURES ANOVA

INTERPRETING THE REPEATED-MEASURES ANOVA USING THE SPSS GENERAL LINEAR MODEL PROGRAM RM ANOVA In this scenario (based on a RM ANOVA example from Leech, Barrett, and Morgan, 2005) each of 12 participants

### 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

### FACTOR ANALYSIS NASC

FACTOR ANALYSIS NASC Factor Analysis A data reduction technique designed to represent a wide range of attributes on a smaller number of dimensions. Aim is to identify groups of variables which are relatively

### Module 9: Nonparametric Tests. The Applied Research Center

Module 9: Nonparametric Tests The Applied Research Center Module 9 Overview } Nonparametric Tests } Parametric vs. Nonparametric Tests } Restrictions of Nonparametric Tests } One-Sample Chi-Square Test

Factor Analysis Advanced Financial Accounting II Åbo Akademi School of Business Factor analysis A statistical method used to describe variability among observed variables in terms of fewer unobserved variables

### 2. Linearity (in relationships among the variables--factors are linear constructions of the set of variables) F 2 X 4 U 4

1 Neuendorf Factor Analysis Assumptions: 1. Metric (interval/ratio) data. Linearity (in relationships among the variables--factors are linear constructions of the set of variables) 3. Univariate and multivariate

### Lecture 7: Factor Analysis. Laura McAvinue School of Psychology Trinity College Dublin

Lecture 7: Factor Analysis Laura McAvinue School of Psychology Trinity College Dublin The Relationship between Variables Previous lectures Correlation Measure of strength of association between two variables

### SCHOOL 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

### 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,

### INTERPRETING THE ONE-WAY ANALYSIS OF VARIANCE (ANOVA)

INTERPRETING THE ONE-WAY ANALYSIS OF VARIANCE (ANOVA) As with other parametric statistics, we begin the one-way ANOVA with a test of the underlying assumptions. Our first assumption is the assumption of

### Principal Component Analysis

Principal Component Analysis Principle Component Analysis: A statistical technique used to examine the interrelations among a set of variables in order to identify the underlying structure of those variables.

### CHAPTER 4 KEY PERFORMANCE INDICATORS

CHAPTER 4 KEY PERFORMANCE INDICATORS As the study was focused on Key Performance Indicators of Information Systems in banking industry, the researcher would evaluate whether the IS implemented in bank

### Projects Involving Statistics (& SPSS)

Projects Involving Statistics (& SPSS) Academic Skills Advice Starting a project which involves using statistics can feel confusing as there seems to be many different things you can do (charts, graphs,

### PRINCIPAL COMPONENTS AND THE MAXIMUM LIKELIHOOD METHODS AS TOOLS TO ANALYZE LARGE DATA WITH A PSYCHOLOGICAL TESTING EXAMPLE

PRINCIPAL COMPONENTS AND THE MAXIMUM LIKELIHOOD METHODS AS TOOLS TO ANALYZE LARGE DATA WITH A PSYCHOLOGICAL TESTING EXAMPLE Markela Muca Llukan Puka Klodiana Bani Department of Mathematics, Faculty of

### Overview of Non-Parametric Statistics PRESENTER: ELAINE EISENBEISZ OWNER AND PRINCIPAL, OMEGA STATISTICS

Overview of Non-Parametric Statistics PRESENTER: ELAINE EISENBEISZ OWNER AND PRINCIPAL, OMEGA STATISTICS About Omega Statistics Private practice consultancy based in Southern California, Medical and Clinical

### After considering the above three factors, it should also be very clear in your mind what you want to achieve.

SPSS Tutorial Which Statistical test? Introduction Irrespective of the statistical package that you are using, deciding on the right statistical test to use can be a daunting exercise. In this document,

### EFFECT OF ENVIRONMENTAL CONCERN & SOCIAL NORMS ON ENVIRONMENTAL FRIENDLY BEHAVIORAL INTENTIONS

169 EFFECT OF ENVIRONMENTAL CONCERN & SOCIAL NORMS ON ENVIRONMENTAL FRIENDLY BEHAVIORAL INTENTIONS Joshi Pradeep Assistant Professor, Quantum School of Business, Roorkee, Uttarakhand, India joshipradeep_2004@yahoo.com

### SPSS 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

### 4. There are no dependent variables specified... Instead, the model is: VAR 1. Or, in terms of basic measurement theory, we could model it as:

1 Neuendorf Factor Analysis Assumptions: 1. Metric (interval/ratio) data 2. Linearity (in the relationships among the variables--factors are linear constructions of the set of variables; the critical source

### Rank-Based Non-Parametric Tests

Rank-Based Non-Parametric Tests Reminder: Student Instructional Rating Surveys You have until May 8 th to fill out the student instructional rating surveys at https://sakai.rutgers.edu/portal/site/sirs

### Does organizational culture cheer organizational profitability? A case study on a Bangalore based Software Company

Does organizational culture cheer organizational profitability? A case study on a Bangalore based Software Company S Deepalakshmi Assistant Professor Department of Commerce School of Business, Alliance

### Perform hypothesis testing

Multivariate hypothesis tests for fixed effects Testing homogeneity of level-1 variances In the following sections, we use the model displayed in the figure below to illustrate the hypothesis tests. Partial

### Factors affecting teaching and learning of computer disciplines at. Rajamangala University of Technology

December 2010, Volume 7, No.12 (Serial No.73) US-China Education Review, ISSN 1548-6613, USA Factors affecting teaching and learning of computer disciplines at Rajamangala University of Technology Rungaroon

### Data Analysis. Lecture Empirical Model Building and Methods (Empirische Modellbildung und Methoden) SS Analysis of Experiments - Introduction

Data Analysis Lecture Empirical Model Building and Methods (Empirische Modellbildung und Methoden) Prof. Dr. Dr. h.c. Dieter Rombach Dr. Andreas Jedlitschka SS 2014 Analysis of Experiments - Introduction

### 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

### Semester 2 Statistics Short courses

Semester 2 Statistics Short courses Course: STAA0001 - Basic Statistics Blackboard Site: STAA0001 Dates: Sat 10 th Sept and 22 Oct 2016 (9 am 5 pm) Room EN409 Assumed Knowledge: None Day 1: Exploratory

### Factor Analysis Example: SAS program (in blue) and output (in black) interleaved with comments (in red)

Factor Analysis Example: SAS program (in blue) and output (in black) interleaved with comments (in red) The following DATA procedure is to read input data. This will create a SAS dataset named CORRMATR

### EPS 625 INTERMEDIATE STATISTICS FRIEDMAN TEST

EPS 625 INTERMEDIATE STATISTICS The Friedman test is an extension of the Wilcoxon test. The Wilcoxon test can be applied to repeated-measures data if participants are assessed on two occasions or conditions

### 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

### USEFULNESS AND BENEFITS OF E-BANKING / INTERNET BANKING SERVICES

CHAPTER 6 USEFULNESS AND BENEFITS OF E-BANKING / INTERNET BANKING SERVICES 6.1 Introduction In the previous two chapters, bank customers adoption of e-banking / internet banking services and functional

### COMPARISONS 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

### 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

### Hatice Camgöz Akdağ. findings of previous research in which two independent firm clusters were

Innovative Culture and Total Quality Management as a Tool for Sustainable Competitiveness: A Case Study of Turkish Fruit and Vegetable Processing Industry SMEs, Sedef Akgüngör Hatice Camgöz Akdağ Aslı

### An Empirical Examination of the Relationship between Financial Trader s Decision-making and Financial Software Applications

Empirical Examination of Financial decision-making & software apps. An Empirical Examination of the Relationship between Financial Trader s Decision-making and Financial Software Applications Research-in-Progress

### Introduction to Analysis of Variance (ANOVA) Limitations of the t-test

Introduction to Analysis of Variance (ANOVA) The Structural Model, The Summary Table, and the One- Way ANOVA Limitations of the t-test Although the t-test is commonly used, it has limitations Can only

### Post-hoc comparisons & two-way analysis of variance. Two-way ANOVA, II. Post-hoc testing for main effects. Post-hoc testing 9.

Two-way ANOVA, II Post-hoc comparisons & two-way analysis of variance 9.7 4/9/4 Post-hoc testing As before, you can perform post-hoc tests whenever there s a significant F But don t bother if it s a main

### INTRODUCTORY STATISTICS

INTRODUCTORY STATISTICS FIFTH EDITION Thomas H. Wonnacott University of Western Ontario Ronald J. Wonnacott University of Western Ontario WILEY JOHN WILEY & SONS New York Chichester Brisbane Toronto Singapore

### Inferential Statistics. Probability. From Samples to Populations. Katie Rommel-Esham Education 504

Inferential Statistics Katie Rommel-Esham Education 504 Probability Probability is the scientific way of stating the degree of confidence we have in predicting something Tossing coins and rolling dice

### For example, enter the following data in three COLUMNS in a new View window.

Statistics with Statview - 18 Paired t-test A paired t-test compares two groups of measurements when the data in the two groups are in some way paired between the groups (e.g., before and after on the

### Factor Analysis Using SPSS

Factor Analysis Using SPSS The theory of factor analysis was described in your lecture, or read Field (2005) Chapter 15. Example Factor analysis is frequently used to develop questionnaires: after all

### 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

### Rachel J. Goldberg, Guideline Research/Atlanta, Inc., Duluth, GA

PROC FACTOR: How to Interpret the Output of a Real-World Example Rachel J. Goldberg, Guideline Research/Atlanta, Inc., Duluth, GA ABSTRACT THE METHOD This paper summarizes a real-world example of a factor

### Statistical tests for SPSS

Statistical tests for SPSS Paolo Coletti A.Y. 2010/11 Free University of Bolzano Bozen Premise This book is a very quick, rough and fast description of statistical tests and their usage. It is explicitly

### FACTOR ANALYSIS. Factor Analysis is similar to PCA in that it is a technique for studying the interrelationships among variables.

FACTOR ANALYSIS Introduction Factor Analysis is similar to PCA in that it is a technique for studying the interrelationships among variables Both methods differ from regression in that they don t have

### A STUDY ON ONBOARDING PROCESS IN SIFY TECHNOLOGIES, CHENNAI

A STUDY ON ONBOARDING PROCESS IN SIFY TECHNOLOGIES, CHENNAI ABSTRACT S. BALAJI*; G. RAMYA** *Assistant Professor, School of Management Studies, Surya Group of Institutions, Vikravandi 605652, Villupuram

### 3. Nonparametric methods

3. Nonparametric methods If the probability distributions of the statistical variables are unknown or are not as required (e.g. normality assumption violated), then we may still apply nonparametric tests

### Research Methodology: Tools

MSc Business Administration Research Methodology: Tools Applied Data Analysis (with SPSS) Lecture 02: Item Analysis / Scale Analysis / Factor Analysis February 2014 Prof. Dr. Jürg Schwarz Lic. phil. Heidi

### Multivariate Analysis of Variance. The general purpose of multivariate analysis of variance (MANOVA) is to determine

2 - Manova 4.3.05 25 Multivariate Analysis of Variance What Multivariate Analysis of Variance is The general purpose of multivariate analysis of variance (MANOVA) is to determine whether multiple levels

### (and sex and drugs and rock 'n' roll) ANDY FIELD

DISCOVERING USING SPSS STATISTICS THIRD EDITION (and sex and drugs and rock 'n' roll) ANDY FIELD CONTENTS Preface How to use this book Acknowledgements Dedication Symbols used in this book Some maths revision

### A STUDY ON FACTORS AFFECTING INDIVIDUALS INVESTMENT TOWARDS LIFE INSURANCE POLICIES

A STUDY ON FACTORS AFFECTING INDIVIDUALS INVESTMENT TOWARDS LIFE INSURANCE POLICIES *Heena Kothari Professor Altius Institute of Universal Studies, Indore (MP) India Email: heena.kothari@altius.ac.in **Roopam

### SEMBIT SQA Unit Code F9HM 04 Applying hypothesis testing

Overview This unit covers the competences required for applying hypothesis testing. It involves calculating the correct sample size to ensure the statistical validity of the hypothesis test, and producing

### Descriptive Statistics

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

### An introduction to. Principal Component Analysis & Factor Analysis. Using SPSS 19 and R (psych package) Robin Beaumont robin@organplayers.co.

An introduction to Principal Component Analysis & Factor Analysis Using SPSS 19 and R (psych package) Robin Beaumont robin@organplayers.co.uk Monday, 23 April 2012 Acknowledgment: The original version

### Examples on Variable Selection in PCA in Sensory Descriptive and Consumer Data

Examples on Variable Selection in PCA in Sensory Descriptive and Consumer Data Per Lea, Frank Westad, Margrethe Hersleth MATFORSK, Ås, Norway Harald Martens KVL, Copenhagen, Denmark 6 th Sensometrics Meeting

### 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

### EPS 625 ANALYSIS OF COVARIANCE (ANCOVA) EXAMPLE USING THE GENERAL LINEAR MODEL PROGRAM

EPS 6 ANALYSIS OF COVARIANCE (ANCOVA) EXAMPLE USING THE GENERAL LINEAR MODEL PROGRAM ANCOVA One Continuous Dependent Variable (DVD Rating) Interest Rating in DVD One Categorical/Discrete Independent Variable

### A Brief Introduction to Factor Analysis

1. Introduction A Brief Introduction to Factor Analysis Factor analysis attempts to represent a set of observed variables X 1, X 2. X n in terms of a number of 'common' factors plus a factor which is unique

### INCOME AND HAPPINESS 1. Income and Happiness

INCOME AND HAPPINESS 1 Income and Happiness Abstract Are wealthier people happier? The research study employed simple linear regression analysis to confirm the positive relationship between income and

### THE KRUSKAL WALLLIS TEST

THE KRUSKAL WALLLIS TEST TEODORA H. MEHOTCHEVA Wednesday, 23 rd April 08 THE KRUSKAL-WALLIS TEST: The non-parametric alternative to ANOVA: testing for difference between several independent groups 2 NON

### A Study to Improve the Response in Email Campaigning by Comparing Data Mining Segmentation Approaches in Aditi Technologies

IAU A Study to Improve the Response in Email Campaigning by Comparing Data Mining Segmentation Approaches in Aditi Technologies 1 *P. Theerthaana, 2 S. Sharad 1 Department of Marketing, Anna University,

### SPSS: Descriptive and Inferential Statistics. For Windows

For Windows August 2012 Table of Contents Section 1: Summarizing Data...3 1.1 Descriptive Statistics...3 Section 2: Inferential Statistics... 10 2.1 Chi-Square Test... 10 2.2 T tests... 11 2.3 Correlation...

### c. The factor is the type of TV program that was watched. The treatment is the embedded commercials in the TV programs.

STAT E-150 - Statistical Methods Assignment 9 Solutions Exercises 12.8, 12.13, 12.75 For each test: Include appropriate graphs to see that the conditions are met. Use Tukey's Honestly Significant Difference

### UNDERSTANDING THE TWO-WAY ANOVA

UNDERSTANDING THE e have seen how the one-way ANOVA can be used to compare two or more sample means in studies involving a single independent variable. This can be extended to two independent variables

### The Statistics Tutor s

statstutor community project encouraging academics to share statistics support resources All stcp resources are released under a Creative Commons licence Stcp-marshallowen-7 The Statistics Tutor s www.statstutor.ac.uk

### Factors Influencing 3G Internet Usage Satisfaction of Youth in Dhaka Metropolitan area

Factors Influencing 3G Internet Usage Satisfaction of Youth in Dhaka Metropolitan area Iffat Tarannum 1, Ummay Sumaiya Mutiatur Rasu 2 * 1 Faculty of Business School, BRAC University, Dhaka Bangladesh.

### CRJ Doctoral Comprehensive Exam Statistics Friday August 23, :00pm 5:30pm

CRJ Doctoral Comprehensive Exam Statistics Friday August 23, 23 2:pm 5:3pm Instructions: (Answer all questions below) Question I: Data Collection and Bivariate Hypothesis Testing. Answer the following

### 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

### MODERATING EFFECT OF INFORMATION TECHNOLOGY UTILIZATION ON THE RELATIONSHIP BETWEEN COMMITMENT AND CUSTOMER SATISFACTION

MODERATING EFFECT OF INFORMATION TECHNOLOGY UTILIZATION ON THE RELATIONSHIP BETWEEN COMMITMENT AND CUSTOMER SATISFACTION Charles Boise Nyameino Dr. Ronald Bonuke Prof. Thomas Kimeli Cheruiyot Moi University

### Hypothesis Testing & Data Analysis. Statistics. Descriptive Statistics. What is the difference between descriptive and inferential statistics?

2 Hypothesis Testing & Data Analysis 5 What is the difference between descriptive and inferential statistics? Statistics 8 Tools to help us understand our data. Makes a complicated mess simple to understand.

### UNIVERSITY OF NAIROBI

UNIVERSITY OF NAIROBI MASTERS IN PROJECT PLANNING AND MANAGEMENT NAME: SARU CAROLYNN ELIZABETH REGISTRATION NO: L50/61646/2013 COURSE CODE: LDP 603 COURSE TITLE: RESEARCH METHODS LECTURER: GAKUU CHRISTOPHER

### Study 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

### CHAPTER VI ON PRIORITY SECTOR LENDING

CHAPTER VI IMPACT OF PRIORITY SECTOR LENDING 6.1 PRINCIPAL FACTORS THAT HAVE DIRECT IMPACT ON PRIORITY SECTOR LENDING 6.2 ASSOCIATION BETWEEN THE PROFILE VARIABLES AND IMPACT OF PRIORITY SECTOR CREDIT

### Canonical Correlation

Chapter 400 Introduction Canonical correlation analysis is the study of the linear relations between two sets of variables. It is the multivariate extension of correlation analysis. Although we will present

### Testing for differences I exercises with SPSS

Testing for differences I exercises with SPSS Introduction The exercises presented here are all about the t-test and its non-parametric equivalents in their various forms. In SPSS, all these tests can

### Exploratory Factor Analysis

Introduction Principal components: explain many variables using few new variables. Not many assumptions attached. Exploratory Factor Analysis Exploratory factor analysis: similar idea, but based on model.

### Non-parametric tests I

Non-parametric tests I Objectives Mann-Whitney Wilcoxon Signed Rank Relation of Parametric to Non-parametric tests 1 the problem Our testing procedures thus far have relied on assumptions of independence,

### 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

### SPSS Guide: Tests of Differences

SPSS Guide: Tests of Differences 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

### Hypothesis Testing. Dr. Bob Gee Dean Scott Bonney Professor William G. Journigan American Meridian University

Hypothesis Testing Dr. Bob Gee Dean Scott Bonney Professor William G. Journigan American Meridian University 1 AMU / Bon-Tech, LLC, Journi-Tech Corporation Copyright 2015 Learning Objectives Upon successful