Meeting-5 MEASUREMENT 8-1

Similar documents
11-3. Learning Objectives

Daniel Boduszek University of Huddersfield

Ch. 11 Measurement. Paul I-Hai Lin, Professor A Core Course for M.S. Technology Purdue University Fort Wayne Campus

Ch. 11 Measurement. Measurement

TESTING AND MEASUREMENT. MERVE DENİZCİ NAZLIGÜL, M.S. Çankaya University

Measurement and Scales

CHAPTER 4 THE QUESTIONNAIRE DESIGN /SOLUTION DESIGN. This chapter contains explanations that become a basic knowledge to create a good

32.5. percent of U.S. manufacturers experiencing unfair currency manipulation in the trade practices of other countries.

02a: Test-Retest and Parallel Forms Reliability

On the purpose of testing:

Data Analysis. A cross-tabulation allows the researcher to see the relationships between the values of two different variables

CHAPTER ONE CORRELATION

Business Research Methods. Introduction to Data Analysis

ADMS Sampling Technique and Survey Studies

Intro to SPSS. Using SPSS through WebFAS

Daniel Boduszek University of Huddersfield

POL 242Y Final Test (Take Home) Name

Data Analysis for Project. Tutorial

DATA is derived either through. Self-Report Observation Measurement

Daniel Boduszek University of Huddersfield

PTHP 7101 Research 1 Chapter Assignments

Day 11: Measures of Association and ANOVA

EVALUATING AND IMPROVING MULTIPLE CHOICE QUESTIONS

Measurement and Scaling Techniques

WELCOME! Lecture 11 Thommy Perlinger

Making a psychometric. Dr Benjamin Cowan- Lecture 9

Using SPSS for Correlation

Survey Project Data Analysis Guide

Daniel Boduszek University of Huddersfield

So far. INFOWO Lecture M5 Homogeneity and Reliability. Homogeneity. Homogeneity

Introduction to SPSS: Defining Variables and Data Entry

Correlation and Regression

Student name: SOCI 420 Advanced Methods of Social Research Fall 2017

Bivariate Correlations

Chapter 14: More Powerful Statistical Methods

CHAPTER 3 RESEARCH METHODOLOGY. In this chapter, research design, data collection, sampling frame and analysis

Collecting & Making Sense of


DATA GATHERING. Define : Is a process of collecting data from sample, so as for testing & analyzing before reporting research findings.

Basic SPSS for Postgraduate

SOME NOTES ON STATISTICAL INTERPRETATION

RELATIONSHIP BETWEEN EMOTIONAL INTELLIGENCE AND ETHICAL COMPETENCE: AN EMPIRICAL STUDY

The Asian Conference on Education & International Development 2015 Official Conference Proceedings. iafor

Effect of work stress on auditor performance in the financial audit board of the republic of Indonesia representative of North Sulawesi province

Analysis and Interpretation of Data Part 1

Part 8 Logistic Regression

CHAPTER VI RESEARCH METHODOLOGY

Skala Stress. Putaran 1 Reliability. Case Processing Summary. N % Excluded a 0.0 Total

Prepared by: Assoc. Prof. Dr Bahaman Abu Samah Department of Professional Development and Continuing Education Faculty of Educational Studies

FACTORIAL CONSTRUCTION OF A LIKERT SCALE

Title: The Theory of Planned Behavior (TPB) and Texting While Driving Behavior in College Students MS # Manuscript ID GCPI

An Introduction to Research Statistics

Published by: PIONEER RESEARCH & DEVELOPMENT GROUP ( 108

Reliability. Scale: Empathy

Overview of Experimentation

Quantitative Methods in Computing Education Research (A brief overview tips and techniques)

CHAPTER III RESEARCH METHOD. method the major components include: Research Design, Research Site and

The Institute of Chartered Accountants of Sri Lanka

INTRODUCTION TO STATISTICS SORANA D. BOLBOACĂ

Introduction to SPSS S0

Examining differences between two sets of scores

CHAPTER TWO REGRESSION

Step 3 Tutorial #3: Obtaining equations for scoring new cases in an advanced example with quadratic term

Psychometric Instrument Development

Module One: What is Statistics? Online Session

bivariate analysis: The statistical analysis of the relationship between two variables.

CHAPTER III METHODOLOGY

The following are questions that students had difficulty with on the first three exams.

Selecting the Right Data Analysis Technique

The Nature of Probability and Statistics

Psychology Research Methods Lab Session Week 10. Survey Design. Due at the Start of Lab: Lab Assignment 3. Rationale for Today s Lab Session

Effect of Sample Size on Correlation and Regression Coefficients

Simple Linear Regression One Categorical Independent Variable with Several Categories

Tech Talk: Using the Lafayette ESS Report Generator

Designing a Questionnaire

CHAPTER 3. Research Methodology

UNDERSTANDING QUANTITATIVE RESEARCH

POLS 5377 Scope & Method of Political Science. Correlation within SPSS. Key Questions: How to compute and interpret the following measures in SPSS

SPSS Correlation/Regression

A COMPARISON BETWEEN MULTIVARIATE AND BIVARIATE ANALYSIS USED IN MARKETING RESEARCH

Validity. Ch. 5: Validity. Griggs v. Duke Power - 2. Griggs v. Duke Power (1971)

CHAPTER 3 METHODOLOGY

Selecting and Designing Instruments: Item Development, Reliability, and Validity John D. Hathcoat, PhD & Courtney B. Sanders, MS, Nikole Gregg, BA

HPS301 Exam Notes- Contents

Types of variables. Introduction

DIFFERENTIATE: ACCURACY AND PRECISION

Before we get started:

commentary Time is a jailer: what do alpha and its alternatives tell us about reliability?

A Study on the Impact of Extrovert Personality Traits on the It Working Professionals Stock Investment Decision

A Good Safety Culture Correlates with Increased Positive and Decreased Negative Outcomes: A Questionnaire Based Study at Finnish Defense Forces

Asian American Midlife Women s Sleep Related Symptoms and Physical Activity

What are Indexes and Scales

MULTIPLE LINEAR REGRESSION 24.1 INTRODUCTION AND OBJECTIVES OBJECTIVES

RESULTS. Chapter INTRODUCTION

MEASUREMENT, SCALING AND SAMPLING. Variables

1. Below is the output of a 2 (gender) x 3(music type) completely between subjects factorial ANOVA on stress ratings

Section 6: Analysing Relationships Between Variables

Reliability and Validity checks S-005

International Journal of Scientific & Engineering Research, Volume 4, Issue 12, December ISSN

Survey research (Lecture 1)

Transcription:

Meeting-5 MEASUREMENT 8-1

Measurement Measurement Process: 1. Selecting observable empirical events 2. Using numbers or symbols to represent aspects of the events being measured 3. Applying a mapping rule to connect the observation to the symbol 8-2

8-3 Characteristics of Measurement

What is Measured? Objects: Things of ordinary experience: furniture, people, cars Some things not concrete: genes, attitudes etc. Properties: characteristics of objects: Physical : weight, height and posture Psycological : attitudes, behaviour, intelligence Social : leadership ability, status 8-4

Levels of Measurement Nominal Ordinal interval Ratio Classification Classification Order Classification Order Classification Order Distance Distance Natural Origin 8-5

8-6 Measurement Scales

Data Types Order Distance Origin Nominal none none none Ordinal yes unequal none Interval yes equal or none unequal Ratio yes equal zero 8-7

Sources of Measurement Differences Respondent: employee status, ethnic, social class, fatigue, boredom, hunger, impatience, anxiety Situational factors: the existence of other person Measurer or researcher: rewording, reordering questions, incorrect coding, careless tabulation, faulty statistical calculation Data collection instrument: the use of complex words and syntax, ambigious meaning, mechanical defects 8-8

The Criteria for Evaluating a Measurement Validity: a characteristic of measurement concerned with the extent that a test measures what we actually wish to measure. Reliability: a characteristic of measurement concerned with accuracy, precision and consistency. Practicality is concerned with a wide range of factors of economy, convenience, and interpretability. 8-9

8-10 Understanding Validity and Reliability

Validity and Reliability Test Questionnaire Test Validity Realibility Correlation Analysis (Pearson): Total Variable & Each Variable If Sig. < 0,05 valid If Sig. > 0,05 not valid delete the question Realibility Statistics If Cronbach s Alpha > 0,6 the instrument is reliable. If Cronbach s Alpha < 0,6 the instrument is not reliable 8-11

Validity and Reliability Test 1. Validity Test Using SPSS software to do the correlation analysis Pearson Correlation. Find correlation between each question in the questionnaire and its total value. See the significance value (Sig.): If Sig. < 0.05 the question/instrument is valid If Sig. > 0.05 the question/instrument in not valid deleted/removed 8-12

Validity and Reliability Test Example of validity test: Open SPSS program Open the data: validity&reliability1_original.sav First Step: Making new variable Total 1. Choose Transform Compute variable 2. Type the new name variable. Total in the Target variable box. 3. Entry and suming all variables (from question1 to question15) to Numeric Expression box. 4. Click OK. 5. Then in SPSS - Data View, you can see the new variable (Total) with its values. 8-13

Validity and Reliability Test Second Step: Correlation Analysis 1.Open the data: validity&reliability1_original.sav 2.Choose Analyze Correlation Bivariate 3.Enter all variables to the Variables box 4.Click Pearson s box in the Correlation Coefficient box and click Flag significant correlation s box. 5.Click OK 6.The output as seen below: 8-14

8-15 Validity and Reliability Test

Validity and Reliability Test 2. Realibility Test Using SPSS software to find Realibility Statistics Cronbach s Alpha. If Cronbach s Alpha > 0.6 the instrument is reliable If Cronbach s Alpha < 0.6 not reliable Example of realibility test: The steps: 1.Open SPSS program 2.Open the data: validity&reliability1_original.sav 3.Choose Analyze Scale Reliability Analysis box 4.Entry all variables to the Items box 5.Click Statistics Reliability Analysis box. 6.Click Scale if item deleted in the Decriptive for box 7.Click Continue 8.Click OK. 8-16

Validity and Reliability Test The output of reliability analysis: 8-17