Fundamental Statistics for the Behavioral Sciences

Name: Fundamental Statistics for the Behavioral Sciences
Price: 8.15 USD
Availability: InStock
ISBN: 9780495099000

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.

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…




Introduction


The importance of Context


Basic Terminology


Selection among Statistical Procedures


Using Computers


Summary


Exercises



Basic Concepts


Scales of Measurement


Variables


Random Sampling


Notation


Summary


Exercises



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



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



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



The Normal Distribution


The Normal Distribution


The Standard Normal Distribution


Setting Probable Limits on an Observations


Measures Related to z


Seeing Statistics


Summary


Exercises



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



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



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



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



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



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



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