Sources of Data Levin and Fox Ch. 1: The Experiment The Survey Content Analysis Participant Observation Secondary Analysis 1.

Slides:



Advertisements
Similar presentations
Richard M. Jacobs, OSA, Ph.D.
Advertisements

Conceptualization, Operationalization, and Measurement
Designing Research Concepts, Hypotheses, and Measurement
EDU 660 Methods of Educational Research Descriptive Statistics John Wilson Ph.D.
Introduction to Statistics Quantitative Methods in HPELS 440:210.
Statistics.
Review of Basics. REVIEW OF BASICS PART I Measurement Descriptive Statistics Frequency Distributions.
QUANTITATIVE DATA ANALYSIS
EdPsy 511 August 28, Common Research Designs Correlational –Do two qualities “go together”. Comparing intact groups –a.k.a. causal-comparative and.
Example: Theories in Public Policy Process
Mean, Median, Mode These are measures of central tendency All three give us information about a sample But some are more meaningful depending on the level.
Introduction to Educational Statistics
1 The Assumptions. 2 Fundamental Concepts of Statistics Measurement - any result from any procedure that assigns a value to an observable phenomenon.
Levels of Measurement Nominal measurement Involves assigning numbers to classify characteristics into categories Ordinal measurement Involves sorting objects.
Descriptive Statistics: Part One Farrokh Alemi Ph.D. Kashif Haqqi M.D.
BASIC STATISTICS WE MOST OFTEN USE Student Affairs Assessment Council Portland State University June 2012.
Today: Central Tendency & Dispersion
Introduction to Statistics February 21, Statistics and Research Design Statistics: Theory and method of analyzing quantitative data from samples.
Chapter 1: Introduction to Statistics
Descriptive Statistics: Maarten Buis Lecture 1: Central tendency, scales of measurement, and shapes of distributions.
Chapter 1: Introduction to Statistics
CHAPTER 4 Research in Psychology: Methods & Design
@ 2012 Wadsworth, Cengage Learning Chapter 5 Description of Behavior Through Numerical 2012 Wadsworth, Cengage Learning.
Descriptive Statistics Used to describe the basic features of the data in any quantitative study. Both graphical displays and descriptive summary statistics.
Completing the Experiment. Your Question should be in the proper format: The Effect of Weight on the Drone’s Ability to Fly in Meters In this format,
Statistics and Research methods Wiskunde voor HMI Betsy van Dijk.
Biostatistics ZMP 602 E_Mail:
© 2006 McGraw-Hill Higher Education. All rights reserved. Numbers Numbers mean different things in different situations. Consider three answers that appear.
Descriptive Statistics And related matters. Two families of statistics Descriptive statistics – procedures for summarizing, organizing, graphing, and,
Chapter 5 Conceptualization, Operationalization, and Measurement.
© 2006 McGraw-Hill Higher Education. All rights reserved. Numbers Numbers mean different things in different situations. Consider three answers that appear.
EDPSY Chp. 2: Measurement and Statistical Notation.
1 STAT 500 – Statistics for Managers STAT 500 Statistics for Managers.
Educational Research: Competencies for Analysis and Application, 9 th edition. Gay, Mills, & Airasian © 2009 Pearson Education, Inc. All rights reserved.
Research Ethics:. Ethics in psychological research: History of Ethics and Research – WWII, Nuremberg, UN, Human and Animal rights Today - Tri-Council.
Measures of Central Tendency: The Mean, Median, and Mode
Psy 230 Jeopardy Measurement Research Strategies Frequency Distributions Descriptive Stats Grab Bag $100 $200$200 $300 $500 $400 $300 $400 $300 $400 $500.
1 Statistics A new language Specific notations that differ across disciplines Statistics and math are very different.
© 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.
© 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.
Statistics AP Psychology 2010 J. Mulder. Why are statistics important? “Proof is virtually impossible for psychology researchers to attain because controlling.
Chapter Eight: Using Statistics to Answer Questions.
Chapter 3: Central Tendency. Central Tendency In general terms, central tendency is a statistical measure that determines a single value that accurately.
BASIC STATISTICAL CONCEPTS Chapter Three. CHAPTER OBJECTIVES Scales of Measurement Measures of central tendency (mean, median, mode) Frequency distribution.
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.
IMPORTANCE OF STATISTICS MR.CHITHRAVEL.V ASST.PROFESSOR ACN.
Statistical Analysis of Data. What is a Statistic???? Population Sample Parameter: value that describes a population Statistic: a value that describes.
Chapter 1: Introduction to Statistics. Variables A variable is a characteristic or condition that can change or take on different values. Most research.
1 Outline 1. Why do we need statistics? 2. Descriptive statistics 3. Inferential statistics 4. Measurement scales 5. Frequency distributions 6. Z scores.
LIS 570 Summarising and presenting data - Univariate analysis.
Descriptive and Inferential Statistics Or How I Learned to Stop Worrying and Love My IA.
Educational Research: Data analysis and interpretation – 1 Descriptive statistics EDU 8603 Educational Research Richard M. Jacobs, OSA, Ph.D.
Chapter 2 Describing and Presenting a Distribution of Scores.
A way to organize data so that it has meaning!.  Descriptive - Allow us to make observations about the sample. Cannot make conclusions.  Inferential.
Lesson 3 Measurement and Scaling. Case: “What is performance?” brandesign.co.za.
Descriptive Statistics Printing information at: Class website:
©2013, The McGraw-Hill Companies, Inc. All Rights Reserved Chapter 2 Describing and Presenting a Distribution of Scores.
Criminal Justice and Criminology Research Methods, Second Edition Kraska / Neuman © 2012 by Pearson Higher Education, Inc Upper Saddle River, New Jersey.
Chapter 3 Designing Research Concepts, Hypotheses, and Measurement.
Chapter 11 Summarizing & Reporting Descriptive Data.
Outline Sampling Measurement Descriptive Statistics:
CHAPTER 4 Research in Psychology: Methods & Design
Chapter 5 Conceptualization, Operationalization, and Measurement
Introduction to Statistics
Basic Statistical Terms
Introduction to Course, Book, and SPSS
Introduction to Course, Book, and SPSS
The Nature of Probability and Statistics
Review for Exam 1 Ch 1-5 Ch 1-3 Descriptive Statistics
Chapter Nine: Using Statistics to Answer Questions
Presentation transcript:

Sources of Data Levin and Fox Ch. 1: The Experiment The Survey Content Analysis Participant Observation Secondary Analysis 1

2 Using numbers to do research 1.Classify, categorize – Gender, race, religion 2.Rank or Order – Ideology, policy preferences 3.Score – Tests, scales

3 Four Levels of Measurement 1.Nominal - offer names for labels for characteristics (gender, birthplace). 2.Ordinal - variables with attributes we can logically rank and order.

4 Four Levels of Measurement 3.Interval - distances separating variables (temperature scale). 4.Ratio - attributes composing a variable are based on a true zero point (age). Beware not to treat ordinal measures like interval (although it is done quite frequently).

5 Uses of Statistics 1.Description 2.Decision-making – Hypothesis testing – Should we prescribe this drug (Does this drug work)? – Does this policy intervention have an impact?

6 Organizing and Summarizing Data 1.Frequency distributions 2.Cumulative distributions 3.Proportions/Percentages 4.Ratios and Rates 5.Percentile Ranks 6.Cross-tabulations 7.Graphic presentations

Fundamental Concepts of Statistics Measurement - any result from any procedure that assigns a value to an observable phenomenon. Problems: our observations are based on our ability to observe, count, etc. Accuracy is always an issue. It is virtually impossible to achieve the same measurement twice. Variation - this brings us to the idea of variation. Statistics is based on the idea that almost everything varies in someway or has variation. Two reasons for variation: 1.measurement inaccuracies or error 2. true differences b/w observations, measurement and groups Error - is always present even when our measures are reliable and valid since our statistical tests are based on samples. Probabilistic causation - because of this property we can only deal with probabilities of being correct or incorrect in our determination of differences in crime rates. 7

Three Types of Statistics Descriptive - Techniques employed in the presentation of collected data. Tables, charts, graphs and the formulation of quantities that indicate concise information about our data. Inferential -Linked with the concept of probability. Statistical methods that permit us to infer (probabilistically) something about the real world and about the "true" population from knowledge derived from only part of that population. Methods that allow us to specify how likely we will be in error. Predictive- Deals with relationships and the idea that knowing information about on characteristic or variable can help us predict the behavior of another variable. Methods and tools that help predict future observations in other populations or time periods. 8

Descriptive: Central Tendency Mode - The most frequent observation. Usually used with nominal data to describe data. Limitation - limited information - could be multi-modal. Cannot be arithmetically manipulated Median - the middle observation. Usually used with ordinal level data. Relatively stable. Limitations - must have ordinal data or higher. Cannot be arithmetically manipulated Mean - Most widely used measure in statistics (i.e., most statistical tests are built around the mean). Can be arithmetically manipulated (calculated). Limitations - must have either interval or ration data, sensitive to outliers Formula: ∑x / n 9

10 Let’s play with some data 1.Open up the gss.save data file – On WebCampus or –

BASIC ALGEGRA CONCEPTS AND NOTATIONS Definition of Subtraction: a - b = a + (-b) Multiplicative Inverse: a * (1/a) = 1 (a≠0) Multiplication times 0: a * 0 = 0 Associative of Multiplication: (a * b) * c = a * (b * c) Commutative of Multiplication: a * b = b * a Distributive Law: a(b + c) = ab + ac Definition of Division: a / b = a(1/b) 11

Polynomial Identities (a+b) 2 = a 2 + 2ab + b 2 (a+b)(c+d) = ac + ad + bc + bd a 2 - b 2 = (a+b)(a-b) (Difference of squares) (x + a)(x + b) = x 2 + ax + bx + ab ax 2 + bx + c = 0 (Quadratic Formula) 12

Powers x a x b = x (a + b) x a y a = (xy) a (x a ) b = x (ab) x (a/b) = bth root of (x a ): Example X (1/2) = √X x (-a) = 1 / x a x (a - b) = x a / x b 13