Fundamental statistics for the behavioral sciences /

Fundamental statistics for the behavioral sciences /

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Bibliographic Details
Author / Creator:Howell, David C.
Edition:4th ed.
Imprint:Pacific Grove, CA : Duxbury Press, c1999.
Description:xvi, 494 p. : col. ill. ; 24 cm. + 1 computer laser optical disk (4/34 in.)
Language:English
Subject:
Social sciences -- Statistical methods.
Psychometrics.
Psychometrics.
Social sciences -- Statistical methods.
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/4429558
Hidden Bibliographic Details
Varying Form of Title:StatSource to accompany David C. Howell's Fundamental statistics for the behavioral sciences /
ISBN:0534358217
Notes:Includes bibliographical references (p. 465-469) and index.
System requirements: 68020 Macintosh running System 7.1 or 386/25 PC running Windows 3.1, 4 MB RAM, 4x CD-ROM drive, 800 x 600 monitor with thousands of colors.
Table of Contents:
  • 1. Introduction
  • The importance of Context
  • Basic Terminology
  • Selection among Statistical Procedures
  • Using Computers
  • Summary
  • Exercises
  • 2. Basic Concepts
  • Scales of Measurement
  • Variables
  • Random Sampling
  • Notation
  • Summary
  • Exercises
  • 3. Displaying Data
  • Plotting Data
  • Stem-and-Leaf Displays
  • Histograms
  • Reading Graphs
  • Alternative Methods of Plotting Data
  • Describing Distributions
  • Using Computer Programs to Display Data
  • Summary
  • Exercises
  • 4. Measures of Central Tendency
  • The Mode
  • The Median
  • The Mean
  • Relative Advantages of the Mode, the Median, and the Mean
  • Obtaining Measures of Central Tendency Using SPSS
  • A Simple Demonstration-Seeing Statistics
  • Summary
  • Exercises
  • 5. Measures of Variability
  • Range
  • Interquartile Range and Other Range Statistics
  • The Average Deviation
  • The Variance
  • The Standard Deviation
  • Computational Formulae for the Variance and the Standard eviation
  • The Mean and the Variance as Estimators
  • Boxplots: Graphical Representations of Dispersion and Extreme Scores
  • A Return to Trimming
  • Obtaining Measures of Dispersion Using SPSS
  • A Final Worked Example
  • Seeing Statistics
  • Summary
  • Exercises
  • 6. The Normal Distribution
  • The Normal Distribution
  • The Standard Normal Distribution
  • Setting Probable Limits on an Observations
  • Measures Related to z
  • Seeing Statistics
  • Summary
  • Exercises
  • 7. Basic Concepts of Probability
  • Probability
  • Basic Terminology and Rules
  • The Application of Probability to Controversial Issues
  • Writing Up the Results
  • Discrete versus Continuous Variables
  • Probability Distributions for Discrete Variables
  • Probability Distributions for Continuous Variables
  • Summary
  • Exercises
  • 8. Sampling Distributions and Hypothesis Testing
  • Two Simple Examples Involving Course Evaluations and Rude Motorists
  • Sampling Distributions
  • Hypothesis Testing
  • The Null Hypothesis
  • Test Statistics and Their Sampling Distributions
  • Using the Normal Distribution to Test Hypotheses
  • Type I and Type II Errors
  • One- and Two-Tailed Tests
  • Seeing Statistics
  • A Final Worked Example
  • Back to Course Evaluations and Rude Motorists
  • Summary
  • Exercises
  • 9. Correlation
  • Scatter Diagrams
  • The Relationship Between Pace of Life and Heart Disease
  • The Covariance
  • The Pearson Product-Moment Correlation Coefficient (r)
  • Correlations with Ranked Data
  • Factors that Affect the Correlation
  • Beware Extreme Observations
  • Correlation and Causation
  • If Something Looks Too Good to Be True, Perhaps It Is
  • Testing the Significance of a Correlation Coefficient
  • Intercorrelation Matrices
  • Other Correlation Coefficients
  • Using SPSS to Obtain Correlation Coefficients
  • Seeing Statistics
  • A Final Worked Example
  • Summary
  • Exercises
  • 10. Regression
  • The Relationship Between Stress and Health
  • The Basic Data
  • The Regression Line
  • The Accuracy of Prediction
  • The Influence of Extreme Values
  • Hypothesis Testing in Regression
  • Computer Solutions using SPSS
  • Seeing Statistics
  • Summary
  • Exercises
  • 11. Multiple Regression
  • Overview
  • A Different Data Set
  • Residuals
  • The Visual Representation of Multiple Regression
  • Hypothesis Testing
  • Refining the Regression Equation
  • A Second Example: Height and Weight
  • A Third Example: Psychological Symptoms in Cancer Patients
  • Summary
  • Exercises
  • 12. Hypothesis Testing Applied to Means: One Sample
  • Sampling Distribution of the Mean
  • Testing Hypotheses about Means When ?p is Known
  • Testing a Sample Mean When ?p is Unknown (The One-Sample t)
  • Factors that Affect the Magnitude of t and the Decision about H0
  • A Second Example: The Moon Illusion
  • How Large is Our Effect?
  • Confidence Limits on the Mean
  • Using SPSS to Run One-Sample t tests
  • A Final Worked Example
  • Seeing Statistics
  • Summary
  • Exercises
  • 13. Hypothesis Tests Applied to Means: Two Related Samples
  • Related Samples
  • Student's t Applied to Difference Scores
  • A Second Example: The Moon Illusion Again
  • Advantages and Disadvantages of Using Related Samples
  • How Large an Effect Have We Found?
  • Confidence Limits on Changes
  • Using SPSS for t Tests on Related Samples

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