Quote of the day Information is meaningless absent a language to communicate it. Statistics is that language. - J Schutte.

Slides:



Advertisements
Similar presentations
Population vs. Sample Population: A large group of people to which we are interested in generalizing. parameter Sample: A smaller group drawn from a population.
Advertisements

From Concepts to Variables Sociology 690 – Measurement.
What are Concepts and Variables? Book #2. DEVELOPING CONCEPTS EVENT OF INTEREST NOMINAL CONCEPT INDICATOR OPERATIONAL DEFINITION ELEMENTS EXAMPLE - 1.
Appendix A. Descriptive Statistics Statistics used to organize and summarize data in a meaningful way.
Sociology 690 – Data Analysis Simple Quantitative Data Analysis.
Agricultural and Biological Statistics
BHS Methods in Behavioral Sciences I April 18, 2003 Chapter 4 (Ray) – Descriptive Statistics.
Statistical Methods in Computer Science Data 2: Central Tendency & Variability Ido Dagan.
Descriptive Statistics Chapter 3 Numerical Scales Nominal scale-Uses numbers for identification (student ID numbers) Ordinal scale- Uses numbers for.
Chapter 13 Analyzing Quantitative data. LEVELS OF MEASUREMENT Nominal Measurement Ordinal Measurement Interval Measurement Ratio Measurement.
Chapter 14 Analyzing Quantitative Data. LEVELS OF MEASUREMENT Nominal Measurement Nominal Measurement Ordinal Measurement Ordinal Measurement Interval.
Descriptive Statistics
Statistical Analysis SC504/HS927 Spring Term 2008 Week 17 (25th January 2008): Analysing data.
Analysis of Research Data
Introduction to Educational Statistics
Central Tendency & Variability Dec. 7. Central Tendency Summarizing the characteristics of data Provide common reference point for comparing two groups.
Quantitative Data Analysis Definitions Examples of a data set Creating a data set Displaying and presenting data – frequency distributions Grouping and.
Chapter 5 – 1 Chapter 5 Measures of Variability The importance of measuring variability IQV (index of qualitative variation) The range IQR (inter-quartile.
SHOWTIME! STATISTICAL TOOLS IN EVALUATION DESCRIPTIVE VALUES MEASURES OF VARIABILITY.
CHAPTER 4 Research in Psychology: Methods & Design
Summarizing Scores With Measures of Central Tendency
@ 2012 Wadsworth, Cengage Learning Chapter 5 Description of Behavior Through Numerical 2012 Wadsworth, Cengage Learning.
Southampton Education School Southampton Education School Dissertation Studies Quantitative Data Analysis.
With Statistics Workshop with Statistics Workshop FunFunFunFun.
EPE/EDP 557 Key Concepts / Terms –Empirical vs. Normative Questions Empirical Questions Normative Questions –Statistics Descriptive Statistics Inferential.
Class Meeting #11 Data Analysis. Types of Statistics Descriptive Statistics used to describe things, frequently groups of people.  Central Tendency 
Chapters 1 & 2 Displaying Order; Central Tendency & Variability Thurs. Aug 21, 2014.
Basic Statistics. Scales of measurement Nominal The one that has names Ordinal Rank ordered Interval Equal differences in the scores Ratio Has a true.
PPA 501 – Analytical Methods in Administration Lecture 5a - Counting and Charting Responses.
Chapter 5 – 1 Chapter 5: Measures of Variability The Importance of Measuring Variability IQV (Index of Qualitative Variation) The Range IQR (Inter-Quartile.
UNDERSTANDING RESEARCH RESULTS: DESCRIPTION AND CORRELATION © 2012 The McGraw-Hill Companies, Inc.
METHODS IN BEHAVIORAL RESEARCH NINTH EDITION PAUL C. COZBY Copyright © 2007 The McGraw-Hill Companies, Inc.
Descriptive Statistics
Research Methodology Lecture No :24. Recap Lecture In the last lecture we discussed about: Frequencies Bar charts and pie charts Histogram Stem and leaf.
Counseling Research: Quantitative, Qualitative, and Mixed Methods, 1e © 2010 Pearson Education, Inc. All rights reserved. Basic Statistical Concepts Sang.
Chapter 2 Statistical Concepts Robert J. Drummond and Karyn Dayle Jones Assessment Procedures for Counselors and Helping Professionals, 6 th edition Copyright.
Research Methods. Measures of Central Tendency You will be familiar with measures of central tendency- averages. Mean Median Mode.
Agenda Descriptive Statistics Measures of Spread - Variability.
Psy 230 Jeopardy Measurement Research Strategies Frequency Distributions Descriptive Stats Grab Bag $100 $200$200 $300 $500 $400 $300 $400 $300 $400 $500.
© 2011 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part, except for use as permitted in a license.
Barnett/Ziegler/Byleen Finite Mathematics 11e1 Chapter 11 Review Important Terms, Symbols, Concepts Sect Graphing Data Bar graphs, broken-line graphs,
BASIC STATISTICAL CONCEPTS Chapter Three. CHAPTER OBJECTIVES Scales of Measurement Measures of central tendency (mean, median, mode) Frequency distribution.
Descriptive Statistics. My immediate family includes my wife Barbara, my sons Adam and Devon, and myself. I am 62, Barbara is 61, and the boys are both.
IE(DS)1 Descriptive Statistics Data - Quantitative observation of Behavior What do numbers mean? If we call one thing 1 and another thing 2 what do we.
Statistical Analysis of Data. What is a Statistic???? Population Sample Parameter: value that describes a population Statistic: a value that describes.
Measures of Central Tendency (MCT) 1. Describe how MCT describe data 2. Explain mean, median & mode 3. Explain sample means 4. Explain “deviations around.
Data Analysis. Statistics - a powerful tool for analyzing data 1. Descriptive Statistics - provide an overview of the attributes of a data set. These.
Welcome to… The Exciting World of Descriptive Statistics in Educational Assessment!
Chapter 2 The Mean, Variance, Standard Deviation, and Z Scores.
MGT-491 QUANTITATIVE ANALYSIS AND RESEARCH FOR MANAGEMENT OSMAN BIN SAIF Session 18.
Chapter 12 Understanding Research Results: Description and Correlation
Statistical Methods Michael J. Watts
Statistical Methods Michael J. Watts
CHAPTER 4 Research in Psychology: Methods & Design
Module 6: Descriptive Statistics
Summarizing Scores With Measures of Central Tendency
Description of Data (Summary and Variability measures)
Understanding Research Results: Description and Correlation
Descriptive Statistics
Introduction to Statistics
Summary descriptive statistics: means and standard deviations:
Sociology 690 – Data Analysis
Descriptive and Inferential
Lesson 12: Presentation and Analysis of Data
Ms. Saint-Paul A.P. Psychology
Descriptive Statistics
Sociology 690 – Data Analysis
Ch 5: Measurement Concepts
Lecture 4 Psyc 300A.
Biostatistics Lecture (2).
Presentation transcript:

Quote of the day Information is meaningless absent a language to communicate it. Statistics is that language. - J Schutte

Developing Concepts and Measuring Variables Book #2

Today’s Four Sessions 1.Developing Concepts into Variables 2. Using Non-Quantitative Measurement 3. Using Quantitative Measurement 4. The Reliability and Validity of Measurement

DEVELOPING CONCEPTS EVENT OF INTEREST NOMINAL CONCEPT INDICATOR OPERATIONAL DEFINITION ELEMENTS EXAMPLE - 1 SOME PEOPLE HAVE MORE “THINGS” THAN OTHERS WEALTH SALARY SELF REPORT ON W-2 INCOME RECEIVED VARIABLEDOLLARS PER YEAR

EVENT OF INTEREST NOMINAL CONCEPT INDICATORS OPERATIONAL DEFINITION ELEMENTSEXAMPLE - 2 ROMANTIC FEELINGS LOVE ATTRACTION, RESPECT COMMITMENT, SUPPORT VARIABLE SCORE ON SCALE ATTITUDINAL SCALE DEVELOPING CONCEPTS

Levels of Measurement I Non-Quantitative A. Nominal B. Ordinal II Quantitative A. Interval B. Ratio Categorizing Ordering Categories Scale of Measurement Scale with Absolute Zero

Describing Non-Quantitative Data I Frequency Distributions A. Percentages B. Ratios C. Rates II Grouping and Graphing A. Real Limits and Midpoints B. Bar Graphs and Pie Charts C. Histograms and Frequency Polygons D. Line Charts and Pictograms

I. Measures of Central Tendency A. Mode B. Median C. Mean II. Measures of Dispersion A. Range B. Mean Deviation C. Variance Most Frequent Score Score at Middle Position Sum of Values / N Highest – Lowest Score +1 Sum of Absolute Deviations / N Sum of Squared Deviations / N D. Standard Deviation Square Root of Variance Describing Quantitative Data

Reliability and Validity I Reliability A. Test-Retest B. Split Half II Validity A. Face B. Content C. Criterion 1. Concurrent 2. Predictive