DATA COLLECTION AND ANALYSIS

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "DATA COLLECTION AND ANALYSIS"

Transcription

1 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

2 Objectives of the Discussion 2 Discuss important principles of research when engaging in the data collection and analysis phases of the project? Operationalize the variables in the research question(s) Choose appropriate data collection methods Choose appropriate data collection tools Identify and collect from the proper data sources Be acutely aware of timing Avoid sampling error and bias Ensure privacy and confidentiality Store data properly Define the different types of validity and reliability and the relationship between these two important characteristics of data and the results of data analysis. Describe the types of measuring instruments used to collect data in qualitative and quantitative studies.

3 Variables 3 A variable is a construct that can take on two or more values. A constant takes on only one value. For Data Collection, variables must be operationalized. That is, the researcher must define a rule for how a variable is to be measured. Interest in Science may be operationalize as (1) the score on a science interest inventory or questionnaire, or (2) the number of science courses that an individual took during grades 9-12.

4 Quantitative and Qualitative Variables 4 Quantitative variables are ordinal, interval and ratio variables. Variates differ in magnitude. scores, heights, speed, age, weight Qualitative Variables are nominal or categorical variables. Variates differ in kind. political party affiliation; eye color; gender; race/ethnicity Quantitative variables exist on a continuum that ranges from low to high or less to more. Qualitative variables are qualities about how people or objects differ with no relation to natural order.

5 Measurement Scales 5 Measurement is the process of assigning numbers to characteristics of an object or person. The four measurement scales: Nominal Ordinal Interval Ratio Data collected on different measurement scales require different methods of statistical analysis.

6 Nominal and Ordinal Scales 6 Nominal scales define variables that are categorical. Examples: gender, employment status, marital status, type of school. Ordinal scales classify persons or objects and they also rank them in terms of the degree to which they possess a particular characteristic. Examples: class rank, order of finishing a race. These scales classify persons or objects into two or more categories. It is the lowest level of measurement. These scales permit comparisons of higher/lower, for example, but do not indicate how much higher or lower.

7 Interval and Ratio Scales 7 Interval scales have all the properties of nominal and ordinal scales, and also have equal intervals. Ratio scales have all the properties of the other scales and represents the highest, most precise level of measurement. Examples: Achievement, attitudes, motivation, etc. (educational measures). Examples: Height, weight, time, distance, speed (physical measures). Interval scales do not have a true zero point. A score of zero may indicate the lowest level of performance possible, but does not indicate total absence of the characteristic. Ratio scales have a true zero point. It is meaningful to talk about no distance. Ratio scales also permit comparisons by ratios (Aisha weighs twice as Linda).

8 Types of Scores from Instruments 8 Raw Scores The number or point value of items a person answered correctly on an assessment Norm-referenced Scoring A scoring approach in which an individual s performance on an assessment is compared to the performance of others Criterion-referenced Scoring A scoring approach in which an individual s performance on an assessment is compared to a predetermined external standard. Self-referenced Scoring A scoring approach in which an individual s repeated performances on a single assessment are compared over time.

9 Types of Scores from Instruments 9 Raw Scores Cedric earned a raw score of 92 on his biology test. Norm-referenced Scoring Jenelle s has a percentile rank of 92 on her algebra test. Criterion-referenced Scoring Richard earned 92% on his chemistry test. Self-referenced Scoring Sheri scored 92% higher on this week s geometry quiz than she did on last week s geometry quiz.

10 Independent and Dependent Variables 10 Experimental Research The independent variable (causal or manipulated variable) is the intended cause of the dependent variable (outcome, effect, or criterion variable). Non-Experimental Research The independent variable (status variable not manipulated) is the variable that logically has some effect on a dependent variable. Examples of IVs include: gender, race-ethnicity, marital status, eye color, employment status, etc.

11 11 Research Questions: Identifying Independent and Dependent Variables Do ninth-grade girls will have different attitudes toward science than ninth-grade boys? Is there a relationship between middle-school students grades and their self-confidence in science and math? Is personalized instruction from a teacher more effective for increasing students critical thinking skills than computer-based instruction?

12 Data Collection Methods 12 Quantitative Methods Tests Surveys Questionnaires Rubrics Checklists Qualitative Methods Observations Interviews Document Reviews Focus Groups Photographs/Drawings Recordings Social Media/ Phone Calls/Recordings

13 Formats for Data Collection Tools 13 Selection & Supply Methods: Used predominately by quantitative researchers; paper and pencil or electronic. Selection Methods Multiple-choice, true-false, and matching items Supply Methods Administer a short answer/essay question tests; fill in the blank items; and performance assessments (assessment of a product or a process) Rubrics Interviews, Focus Groups, Observations: Used predominately by qualitative researchers. Data are collected by observation, conversation, or extended written communication.

14 Validity of Assessment Results 14 Validity is the most important characteristic of the assessment results; is concerned with the appropriateness of the interpretations made from assessment results; is best thought of in terms of degree; is specific to the interpretation being made and to the group being assessed.

15 Types of Validity 15 Content Validity- the degree to which the assessment results are a reflection of the intended content area. Criterion-Related Validity- determined by relating performance on one measure to performance on a second measure. Concurrent Validity (SAT scores and ACT scores) Predictive Validity (SAT scores and freshman g.p.a.; GRE scores and success in first year of graduate school)

16 Types of Validity 16 Construct Validity- is the most important form of validity because it asks the fundamental validity question: What is this assessment tool really measuring? Examples Mathematics tests and reading levels Reading and language tests Interest in STEM Consequential Validity - the extent to which the use of assessment results has intended or unintended effects for the user. Test scores and graduation, teacher certification, teacher effectiveness A narrowing of the curriculum and classroom teaching to focus only on what is tested

17 Reliability of Measuring Instruments 17 Reliability is the degree to which a test consistently measures whatever it is measuring. Reliability is expressed as a reliability coefficient which is obtained by using correlation. Error is present in all measurement. High reliability means small errors of measurement.

18 Types of Reliability 18 Test-retest Reliability Equivalent-forms Reliability Internal Consistency Reliability Split-Half Reliability Cronbach s Alpha Reliability Scorer/Rater Reliability

19 19 Validity and Reliability of Instruments A valid test is always reliable, but a reliable test is not always valid.

20 Validity and Reliability of Observational Data 20 Factors that influence the validity and reliability of observational data: The research question Errors of measurement Training of the observer(s) results in familiarity with the setting the culture the focus of the study the observation protocol how to record data (and not summaries or personal opinions)

21 Data Collection Procedures and Environments 21 Every effort should be made to ensure appropriate data collection procedures and ideal environments (e.g., test administration conditions such as proper lighting, minimum noise level, comfortable seating, etc.) Failing to administer procedures precisely or altering the administration procedures, especially on standardized tests, lowers the validity of the test. High noise levels may be a distraction to study participants during data collection.

22 DATA ANALYSIS

23 Types of Statistics Descriptive Statistics Descriptive statistics are used to organize, describe, and summarize a set of data. Inferential Statistics Inferential statistics are used to draw inferences about the conditions that exist in a population from study of a sample drawn from that population.

24 Types of Statistics Analyses in Quantitative Research Descriptive Statistics Measures of central tendency Mean, median, mode Measures of variability Range, variance, standard deviation, semiinterquartile range Effect Size Inferential Statistics Parametric Tests t-tests, Analysis of variance (ANOVA), Regression analysis Non-parametric Tests Chi-Square test; the sign test

25 Inferential Statistics Types of hypotheses Research hypothesis Null hypothesis Tests of the null hypothesis among Relationships Means Proportions

26 Correlational Techniques Correlation: A measure of the degree of association between two or more variables. Pearson s correlation, r; (both variables are continuous and quantitative) Mathematics achievement and mathematics anxiety Phi coefficient is the Pearson correlation for two variables that are both qualitative and dichotomous Gender and Science major or not Spearman s rho (both variables are expressed as ranks) Class rank and ranking in a science fair competition

27 Tests of Significance Simple Analysis of Variance: one independent variablegender, and one dependent variable - college gpa. Multi-Factor Analysis of Variance: (two or more independent variables - gender, SES, participation in summer bridge program; and one dependent variable, college freshman gpa). Multiple Regression: tells us how much of the variance in the dependent variable (e.g., on-time graduation ) is explained by the set of independent variables (e.g., high school gpa, SAT/ACT mathematics and verbal scores, freshman college gpa).

28 Correlational Techniques Correlation: A measure of the degree of association between two or more variables. Bi-serial correlation (one variable is continuous and quantitative and the other would be, expect it has been reduced to two categories) Multiple correlation, R, is the Pearson correlation between the variable to be predicted and the bestweighted combination of several predictors. To calculate R, we must know Pearson s r between each pair of variables.

29 Data Analysis in Qualitative Research Engage in a great deal of analysis before data collection is complete. Reflect on two questions Is the research questions still answerable? Are the data collection techniques catching the kind of data that is wanted and filtering out the data that is not wanted? Avoid premature actions based on early analysis and interpretation of data.

30 Data Analysis in Qualitative Research Qualitative data analysis is a cyclical, iterative process of reviewing data for common topics or themes. One approach is to follow three iterative steps: Reading and memo-ing Describing what is going on in the setting Classifying research data

31 Data Analysis in Qualitative Research Constant Comparative Analysis Phenomenological Approaches Ethnographic Methods Narrative Analysis & Discourse Analysis

32 Data Analysis Strategies Identifying Themes -- emerges for ideas found in the review of the literature and the data collection. Coding -- the process of marking units of text with codes or labels as a way to indicate patterns and meaning in data. Asking questions Who is centrally involved? ; What major activities or issues are relevant to the problem? Then seeking answers in the data. Concept Mapping a visual display of the major influences that have affected the study.

33 33 Questions?

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

Guided Reading 9 th Edition. informed consent, protection from harm, deception, confidentiality, and anonymity.

Guided Reading 9 th Edition. informed consent, protection from harm, deception, confidentiality, and anonymity. Guided Reading Educational Research: Competencies for Analysis and Applications 9th Edition EDFS 635: Educational Research Chapter 1: Introduction to Educational Research 1. List and briefly describe the

More 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

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

Statistics. Measurement. Scales of Measurement 7/18/2012

Statistics. Measurement. Scales of Measurement 7/18/2012 Statistics Measurement Measurement is defined as a set of rules for assigning numbers to represent objects, traits, attributes, or behaviors A variableis something that varies (eye color), a constant does

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

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

Causal Comparative Research: Purpose

Causal Comparative Research: Purpose Causal Comparative Research: Purpose Attempts to determine cause and effect not as powerful as experimental designs Alleged cause and effect have already occurred and are being examined after the fact

More information

Statistical basics for Biology: p s, alphas, and measurement scales.

Statistical basics for Biology: p s, alphas, and measurement scales. 334 Volume 25: Mini Workshops Statistical basics for Biology: p s, alphas, and measurement scales. Catherine Teare Ketter School of Marine Programs University of Georgia Athens Georgia 30602-3636 (706)

More information

There are three kinds of people in the world those who are good at math and those who are not. PSY 511: Advanced Statistics for Psychological and Behavioral Research 1 Positive Views The record of a month

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

WHAT IS A JOURNAL CLUB?

WHAT IS A JOURNAL CLUB? WHAT IS A JOURNAL CLUB? With its September 2002 issue, the American Journal of Critical Care debuts a new feature, the AJCC Journal Club. Each issue of the journal will now feature an AJCC Journal Club

More information

Research Methods & Experimental Design

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

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

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

Module 9: Nonparametric Tests. The Applied Research Center

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

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

Correlational Research. Correlational Research. Stephen E. Brock, Ph.D., NCSP EDS 250. Descriptive Research 1. Correlational Research: Scatter Plots

Correlational Research. Correlational Research. Stephen E. Brock, Ph.D., NCSP EDS 250. Descriptive Research 1. Correlational Research: Scatter Plots Correlational Research Stephen E. Brock, Ph.D., NCSP California State University, Sacramento 1 Correlational Research A quantitative methodology used to determine whether, and to what degree, a relationship

More information

Elementary Statistics

Elementary Statistics Elementary Statistics Chapter 1 Dr. Ghamsary Page 1 Elementary Statistics M. Ghamsary, Ph.D. Chap 01 1 Elementary Statistics Chapter 1 Dr. Ghamsary Page 2 Statistics: Statistics is the science of collecting,

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

Choosing the correct statistical test made easy

Choosing the correct statistical test made easy Classroom Choosing the correct statistical test made easy N Gunawardana Senior Lecturer in Community Medicine, Faculty of Medicine, University of Colombo Gone are the days where researchers had to perform

More information

Introduction to Statistics

Introduction to Statistics 1 Introduction to Statistics LEARNING OBJECTIVES After reading this chapter, you should be able to: 1. Distinguish between descriptive and inferential statistics. 2. Explain how samples and populations,

More information

Psychometrics 101 Part 2: Essentials of Test Score Interpretation. Steve Saladin, Ph.D. University of Idaho

Psychometrics 101 Part 2: Essentials of Test Score Interpretation. Steve Saladin, Ph.D. University of Idaho Psychometrics 101 Part 2: Essentials of Test Score Interpretation Steve Saladin, Ph.D. University of Idaho Standards for Educational and Psychological Testing 15.10 Those responsible for testing programs

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

Basic Concepts in Research and Data Analysis

Basic 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 information

Introduction to Statistics Used in Nursing Research

Introduction to Statistics Used in Nursing Research Introduction to Statistics Used in Nursing Research Laura P. Kimble, PhD, RN, FNP-C, FAAN Professor and Piedmont Healthcare Endowed Chair in Nursing Georgia Baptist College of Nursing Of Mercer University

More information

THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS. Fall 2013

THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS. Fall 2013 THE UNIVERSITY OF TEXAS AT TYLER COLLEGE OF NURSING 1 COURSE SYLLABUS NURS 5317 STATISTICS FOR HEALTH PROVIDERS Fall 2013 & Danice B. Greer, Ph.D., RN, BC dgreer@uttyler.edu Office BRB 1115 (903) 565-5766

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

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

DEPARTMENT OF HEALTH AND HUMAN SCIENCES HS900 RESEARCH METHODS

DEPARTMENT OF HEALTH AND HUMAN SCIENCES HS900 RESEARCH METHODS DEPARTMENT OF HEALTH AND HUMAN SCIENCES HS900 RESEARCH METHODS Using SPSS Session 2 Topics addressed today: 1. Recoding data missing values, collapsing categories 2. Making a simple scale 3. Standardisation

More information

Chapter 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.) 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 information

Analyzing Research Data Using Excel

Analyzing Research Data Using Excel Analyzing Research Data Using Excel Fraser Health Authority, 2012 The Fraser Health Authority ( FH ) authorizes the use, reproduction and/or modification of this publication for purposes other than commercial

More information

Lisa Rosenberg Mathematics and Statistics Department

Lisa Rosenberg Mathematics and Statistics Department Long Assignment for General Statistics Mathematics 110 Lisa Rosenberg Mathematics and Statistics Department Introduction for Faculty Colleagues This assignment is intended for General Statistics (MTH 110)

More information

Chapter Eight: Quantitative Methods

Chapter 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 information

Outline of Topics. Statistical Methods I. Types of Data. Descriptive Statistics

Outline of Topics. Statistical Methods I. Types of Data. Descriptive Statistics Statistical Methods I Tamekia L. Jones, Ph.D. (tjones@cog.ufl.edu) Research Assistant Professor Children s Oncology Group Statistics & Data Center Department of Biostatistics Colleges of Medicine and Public

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

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

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

Statistics, Research, & SPSS: The Basics

Statistics, 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 information

1) Overview 2) Measurement and Scaling 3) Primary Scales of Measurement i. Nominal Scale ii. Ordinal Scale iii. Interval Scale iv.

1) Overview 2) Measurement and Scaling 3) Primary Scales of Measurement i. Nominal Scale ii. Ordinal Scale iii. Interval Scale iv. 1) Overview 2) Measurement and Scaling 3) Primary Scales of Measurement i. Nominal Scale ii. Ordinal Scale iii. Interval Scale iv. Ratio Scale 4) A Comparison of Scaling Techniques Comparative Scaling

More information

Some Critical Information about SOME Statistical Tests and Measures of Correlation/Association

Some Critical Information about SOME Statistical Tests and Measures of Correlation/Association Some Critical Information about SOME Statistical Tests and Measures of Correlation/Association This information is adapted from and draws heavily on: Sheskin, David J. 2000. Handbook of Parametric and

More information

Study Guide for the Final Exam

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

More information

UNIVERSITY OF NAIROBI

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

More information

Introduction to Statistics and Quantitative Research Methods

Introduction 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 information

Class 6: Chapter 12. Key Ideas. Explanatory Design. Correlational Designs

Class 6: Chapter 12. Key Ideas. Explanatory Design. Correlational Designs Class 6: Chapter 12 Correlational Designs l 1 Key Ideas Explanatory and predictor designs Characteristics of correlational research Scatterplots and calculating associations Steps in conducting a correlational

More information

MASTER COURSE SYLLABUS-PROTOTYPE PSYCHOLOGY 2317 STATISTICAL METHODS FOR THE BEHAVIORAL SCIENCES

MASTER COURSE SYLLABUS-PROTOTYPE PSYCHOLOGY 2317 STATISTICAL METHODS FOR THE BEHAVIORAL SCIENCES MASTER COURSE SYLLABUS-PROTOTYPE THE PSYCHOLOGY DEPARTMENT VALUES ACADEMIC FREEDOM AND THUS OFFERS THIS MASTER SYLLABUS-PROTOTYPE ONLY AS A GUIDE. THE INSTRUCTORS ARE FREE TO ADAPT THEIR COURSE SYLLABI

More information

Measurement & Data Analysis. On the importance of math & measurement. Steps Involved in Doing Scientific Research. Measurement

Measurement & 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 information

Validity of measurement

Validity of measurement Test Validity S-005 Validity of measurement Reliability refers to consistency Are we getting something stable over time? Internally consistent? Validity refers to accuracy Is the measure accurate? Are

More information

Nursing Journal Toolkit: Critiquing a Quantitative Research Article

Nursing Journal Toolkit: Critiquing a Quantitative Research Article A Virtual World Consortium: Using Second Life to Facilitate Nursing Journal Clubs Nursing Journal Toolkit: Critiquing a Quantitative Research Article 1. Guidelines for Critiquing a Quantitative Research

More information

Mathematics within the Psychology Curriculum

Mathematics within the Psychology Curriculum Mathematics within the Psychology Curriculum Statistical Theory and Data Handling Statistical theory and data handling as studied on the GCSE Mathematics syllabus You may have learnt about statistics and

More information

Biostatistics: Types of Data Analysis

Biostatistics: Types of Data Analysis Biostatistics: Types of Data Analysis Theresa A Scott, MS Vanderbilt University Department of Biostatistics theresa.scott@vanderbilt.edu http://biostat.mc.vanderbilt.edu/theresascott Theresa A Scott, MS

More information

Central Tendency. n Measures of Central Tendency: n Mean. n Median. n Mode

Central Tendency. n Measures of Central Tendency: n Mean. n Median. n Mode Central Tendency Central Tendency n A single summary score that best describes the central location of an entire distribution of scores. n Measures of Central Tendency: n Mean n The sum of all scores divided

More information

RESEARCH METHODS IN I/O PSYCHOLOGY

RESEARCH METHODS IN I/O PSYCHOLOGY RESEARCH METHODS IN I/O PSYCHOLOGY Objectives Understand Empirical Research Cycle Knowledge of Research Methods Conceptual Understanding of Basic Statistics PSYC 353 11A rsch methods 01/17/11 [Arthur]

More information

Section Format Day Begin End Building Rm# Instructor. 001 Lecture Tue 6:45 PM 8:40 PM Silver 401 Ballerini

Section 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 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

Midterm Review Problems

Midterm Review Problems Midterm Review Problems October 19, 2013 1. Consider the following research title: Cooperation among nursery school children under two types of instruction. In this study, what is the independent variable?

More information

Chapter 1: The Nature of Probability and Statistics

Chapter 1: The Nature of Probability and Statistics Chapter 1: The Nature of Probability and Statistics Learning Objectives Upon successful completion of Chapter 1, you will have applicable knowledge of the following concepts: Statistics: An Overview and

More information

Descriptive Statistics and Measurement Scales

Descriptive Statistics and Measurement Scales Descriptive Statistics 1 Descriptive Statistics and Measurement Scales Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample

More information

EBM Cheat Sheet- Measurements Card

EBM Cheat Sheet- Measurements Card EBM Cheat Sheet- Measurements Card Basic terms: Prevalence = Number of existing cases of disease at a point in time / Total population. Notes: Numerator includes old and new cases Prevalence is cross-sectional

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

Fairfield Public Schools

Fairfield 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 information

CREIGHTON UNIVERSITY GRADUATE COLLEGE Fall Semester 2014. Biostatistics & Analysis of Clinical Data for Evidence-based Practice

CREIGHTON UNIVERSITY GRADUATE COLLEGE Fall Semester 2014. Biostatistics & Analysis of Clinical Data for Evidence-based Practice CREIGHTON UNIVERSITY GRADUATE COLLEGE Fall Semester 2014 Course Number: Course Title: Credit Allocation: Placement: CTS 601 Biostatistics & Analysis of Clinical Data for Evidence-based Practice 3 semester

More information

SCHOOL OF HEALTH AND HUMAN SCIENCES DON T FORGET TO RECODE YOUR MISSING VALUES

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

More information

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

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

More information

Step 6: Writing Your Hypotheses Written and Compiled by Amanda J. Rockinson-Szapkiw

Step 6: Writing Your Hypotheses Written and Compiled by Amanda J. Rockinson-Szapkiw Step 6: Writing Your Hypotheses Written and Compiled by Amanda J. Rockinson-Szapkiw Introduction To determine if a theory has the ability to explain, predict, or describe, you conduct experimentation and

More information

Levels of measurement

Levels of measurement Levels of measurement What numerical data actually means and what we can do with it depends on what the numbers represent. Numbers can be grouped into 4 types or levels: nominal, ordinal, interval, and

More information

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 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

More information

X = T + E. Reliability. Reliability. Classical Test Theory 7/18/2012. Refers to the consistency or stability of scores

X = T + E. Reliability. Reliability. Classical Test Theory 7/18/2012. Refers to the consistency or stability of scores Reliability It is the user who must take responsibility for determining whether or not scores are sufficiently trustworthy to justify anticipated uses and interpretations. (AERA et al., 1999) Reliability

More information

Analyzing and interpreting data Evaluation resources from Wilder Research

Analyzing and interpreting data Evaluation resources from Wilder Research Wilder Research Analyzing and interpreting data Evaluation resources from Wilder Research Once data are collected, the next step is to analyze the data. A plan for analyzing your data should be developed

More information

Basic Statistical Concepts, Research Design, & Notation

Basic Statistical Concepts, Research Design, & Notation , Research Design, & Notation Variables, Scores, & Data A variable is a characteristic or condition that can change or take on different values. Most research begins with a general question about the relationship

More information

Concepts of Variables. Levels of Measurement. The Four Levels of Measurement. Nominal Scale. Greg C Elvers, Ph.D.

Concepts of Variables. Levels of Measurement. The Four Levels of Measurement. Nominal Scale. Greg C Elvers, Ph.D. Concepts of Variables Greg C Elvers, Ph.D. 1 Levels of Measurement When we observe and record a variable, it has characteristics that influence the type of statistical analysis that we can perform on it

More information

Data Analysis: Describing Data - Descriptive Statistics

Data Analysis: Describing Data - Descriptive Statistics WHAT IT IS Return to Table of ontents Descriptive statistics include the numbers, tables, charts, and graphs used to describe, organize, summarize, and present raw data. Descriptive statistics are most

More information

Step 7: Identifying, Labeling, and Defining Your Variables Written and Compiled by Amanda J. Rockinson-Szapkiw

Step 7: Identifying, Labeling, and Defining Your Variables Written and Compiled by Amanda J. Rockinson-Szapkiw Step 7: Identifying, Labeling, and Defining Your Variables Written and Compiled by Amanda J. Rockinson-Szapkiw Introduction Your variables are introduced in your purpose statement, questions, and hypotheses,

More information

Technical Report. Overview. Revisions in this Edition. Four-Level Assessment Process

Technical Report. Overview. Revisions in this Edition. Four-Level Assessment Process Technical Report Overview The Clinical Evaluation of Language Fundamentals Fourth Edition (CELF 4) is an individually administered test for determining if a student (ages 5 through 21 years) has a language

More information

Course Description. Learning Objectives

Course Description. Learning Objectives STAT X400 (2 semester units in Statistics) Business, Technology & Engineering Technology & Information Management Quantitative Analysis & Analytics Course Description This course introduces students to

More information

TRAINING PROGRAM INFORMATICS

TRAINING PROGRAM INFORMATICS MEDICAL UNIVERSITY SOFIA MEDICAL FACULTY DEPARTMENT SOCIAL MEDICINE AND HEALTH MANAGEMENT SECTION BIOSTATISTICS AND MEDICAL INFORMATICS TRAINING PROGRAM INFORMATICS FOR DENTIST STUDENTS - I st COURSE,

More information

Data Definitions Adapted from the Glossary How to Design and Evaluate Research in Education by Jack R. Fraenkel and Norman E.

Data Definitions Adapted from the Glossary How to Design and Evaluate Research in Education by Jack R. Fraenkel and Norman E. Data Definitions Adapted from the Glossary How to Design and Evaluate Research in Education by Jack R. Fraenkel and Norman E. Wallen, A A-B design A single-subject experimental design in which measurements

More information

Measurement. How are variables measured?

Measurement. How are variables measured? Measurement Y520 Strategies for Educational Inquiry Robert S Michael Measurement-1 How are variables measured? First, variables are defined by conceptual definitions (constructs) that explain the concept

More information

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

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.

More information

1. Why the hell do we need statistics?

1. Why the hell do we need statistics? 1. Why the hell do we need statistics? There are three kind of lies: lies, damned lies, and statistics, British Prime Minister Benjamin Disraeli (as credited by Mark Twain): It is easy to lie with statistics,

More information

Assessment, Case Conceptualization, Diagnosis, and Treatment Planning Overview

Assessment, Case Conceptualization, Diagnosis, and Treatment Planning Overview Assessment, Case Conceptualization, Diagnosis, and Treatment Planning Overview The abilities to gather and interpret information, apply counseling and developmental theories, understand diagnostic frameworks,

More information

PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050

PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050 PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050 Class Hours: 2.0 Credit Hours: 3.0 Laboratory Hours: 2.0 Date Revised: Fall 2013 Catalog Course Description: Descriptive

More information

Testing Group Differences using T-tests, ANOVA, and Nonparametric Measures

Testing Group Differences using T-tests, ANOVA, and Nonparametric Measures Testing Group Differences using T-tests, ANOVA, and Nonparametric Measures Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa, AL 35487-0348 Phone:

More information

RESEARCH METHODS IN I/O PSYCHOLOGY

RESEARCH METHODS IN I/O PSYCHOLOGY RESEARCH METHODS IN I/O PSYCHOLOGY Objectives Understand Empirical Research Cycle Knowledge of Research Methods Conceptual Understanding of Basic Statistics PSYC 353 11A rsch methods 09/01/11 [Arthur]

More information

Objective of the course The main objective is to teach students how to conduct quantitative data analysis in SPSS for research purposes.

Objective of the course The main objective is to teach students how to conduct quantitative data analysis in SPSS for research purposes. COURSE DESCRIPTION The course Data Analysis with SPSS was especially designed for students of Master s Programme System and Software Engineering. The content and teaching methods of the course correspond

More information

Content DESCRIPTIVE STATISTICS. Data & Statistic. Statistics. Example: DATA VS. STATISTIC VS. STATISTICS

Content DESCRIPTIVE STATISTICS. Data & Statistic. Statistics. Example: DATA VS. STATISTIC VS. STATISTICS Content DESCRIPTIVE STATISTICS Dr Najib Majdi bin Yaacob MD, MPH, DrPH (Epidemiology) USM Unit of Biostatistics & Research Methodology School of Medical Sciences Universiti Sains Malaysia. Introduction

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

Levels of measurement in psychological research:

Levels of measurement in psychological research: Research Skills: Levels of Measurement. Graham Hole, February 2011 Page 1 Levels of measurement in psychological research: Psychology is a science. As such it generally involves objective measurement of

More information

RARITAN VALLEY COMMUNITY COLLEGE ACADEMIC COURSE OUTLINE MATH 111H STATISTICS II HONORS

RARITAN 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 information

SPSS Explore procedure

SPSS Explore procedure SPSS Explore procedure One useful function in SPSS is the Explore procedure, which will produce histograms, boxplots, stem-and-leaf plots and extensive descriptive statistics. To run the Explore procedure,

More information

Research Design Concepts. Independent and dependent variables Data types Sampling Validity and reliability

Research Design Concepts. Independent and dependent variables Data types Sampling Validity and reliability Research Design Concepts Independent and dependent variables Data types Sampling Validity and reliability Research Design Action plan for carrying out research How the research will be conducted to investigate

More information

Chapter 3 Psychometrics: Reliability & Validity

Chapter 3 Psychometrics: Reliability & Validity Chapter 3 Psychometrics: Reliability & Validity 45 Chapter 3 Psychometrics: Reliability & Validity The purpose of classroom assessment in a physical, virtual, or blended classroom is to measure (i.e.,

More information

When to use Excel. When NOT to use Excel 9/24/2014

When to use Excel. When NOT to use Excel 9/24/2014 Analyzing Quantitative Assessment Data with Excel October 2, 2014 Jeremy Penn, Ph.D. Director When to use Excel You want to quickly summarize or analyze your assessment data You want to create basic visual

More information

Statistics Notes Revision in Maths Week

Statistics Notes Revision in Maths Week Statistics Notes Revision in Maths Week 1 Section - Producing Data 1.1 Introduction Statistics is the science that studies the collection and interpretation of numerical data. Statistics divides the study

More information

Statistics I for QBIC. Contents and Objectives. Chapters 1 7. Revised: August 2013

Statistics I for QBIC. Contents and Objectives. Chapters 1 7. Revised: August 2013 Statistics I for QBIC Text Book: Biostatistics, 10 th edition, by Daniel & Cross Contents and Objectives Chapters 1 7 Revised: August 2013 Chapter 1: Nature of Statistics (sections 1.1-1.6) Objectives

More information

QUALIFYING EXAMINATION TEST PREPARATION

QUALIFYING EXAMINATION TEST PREPARATION QUALIFYING EXAMINATION TEST PREPARATION Sponsored by the Department of Educational Leadership Table of Contents Quantitative Research Designs 3 Qualitative Research 4 Mixed Methods Research Design 6 Probability

More information

Applied Statistics Handbook

Applied Statistics Handbook Applied Statistics Handbook Phil Crewson Version 1. Applied Statistics Handbook Copyright 006, AcaStat Software. All rights Reserved. http://www.acastat.com Protected under U.S. Copyright and international

More information

Psychology 312: Lecture 6 Scales of Measurement. Slide #1. Scales of Measurement Reliability, validity, and scales of measurement.

Psychology 312: Lecture 6 Scales of Measurement. Slide #1. Scales of Measurement Reliability, validity, and scales of measurement. Psychology 312: Lecture 6 Scales of Measurement Slide #1 Scales of Measurement Reliability, validity, and scales of measurement. In this lecture we will discuss scales of measurement. Slide #2 Outline

More information

Sample Size and Power in Clinical Trials

Sample Size and Power in Clinical Trials Sample Size and Power in Clinical Trials Version 1.0 May 011 1. Power of a Test. Factors affecting Power 3. Required Sample Size RELATED ISSUES 1. Effect Size. Test Statistics 3. Variation 4. Significance

More information

Foundation of Quantitative Data Analysis

Foundation of Quantitative Data Analysis Foundation of Quantitative Data Analysis Part 1: Data manipulation and descriptive statistics with SPSS/Excel HSRS #10 - October 17, 2013 Reference : A. Aczel, Complete Business Statistics. Chapters 1

More information