Fundamental Statistics for the Behavioral Sciences

ISBN-10: 0495099007

ISBN-13: 9780495099000

Edition: 6th 2008 (Revised)

Authors: David C. Howell

List price: $253.95
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David Howell's practical approach focuses on the context of statistics in behavioral research, with an emphasis on looking before leaping; investigating the data before jumping into a test. This provides you with an understanding of the logic behind the statistics: why and how certain methods are used rather than just doing techniques by rote. Learn faster and understand more because Howell's texts moves you beyond number crunching, allowing you to discover the meaning of statistical results and how they relate to the research questions being asked.
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Book details

List price: $253.95
Edition: 6th
Copyright year: 2008
Publisher: Wadsworth
Publication date: 2/1/2007
Binding: Hardcover
Pages: 608
Size: 7.75" wide x 9.50" long x 1.25" tall
Weight: 2.332
Language: English

David C. Howell is a professor emeritus and former chair of the psychology department at the University of Vermont. Professor Howell's primary area of research is in statistics and experimental methods. He is also the author of STATISTICS FOR THE BEHAVIORAL SCIENCES, currently in a Seventh Edition (Wadsworth, 2010), and the ENCYCLOPEDIA OF STATISTICS IN BEHAVIOR SCIENCE (2005) with Brian Everitt. Before retiring he frequently served as consultant with other faculty, both in the psychology department and in departments as disparate as Geology and Animal Sciences, and brings those experiences to this endeavor. Professor Howell's other interests include computing and the World Wide Web, and how technology affects communication, teaching, and research.

The importance of Context
Basic Terminology
Selection among Statistical Procedures
Using Computers
Basic Concepts
Scales of Measurement
Random Sampling
Displaying Data
Plotting Data
Stem-and-Leaf Displays
Reading Graphs
Alternative Methods of Plotting Data
Describing Distributions
Using Computer Programs to Display Data
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
Measures of Variability
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
The Normal Distribution
The Normal Distribution
The Standard Normal Distribution
Setting Probable Limits on an Observations
Measures Related to z
Seeing Statistics
Basic Concepts of 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
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
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
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
Multiple Regression
A Different Data Set
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
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
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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