Fundamental Statistics for the Behavioral Sciences

by Howell, David C.

• ISBN13: 9780534358211
• ISBN10: 0534358217
• Edition: CD
• Format: Hardcover
• Copyright: 1998-08-01
• Publisher: Wadsworth Publishing

Summary

With an emphasis on looking at data before jumping into a test, author David C. Howell's practical approach focuses on the context of statistics in behavioral research. This approach promotes an understanding of the logic behind the statistics: why and how certain methods are used, rather than just doing techniques by rote. Howell takes students beyond crunching numbers to discover the meaning of statistical results and how they relate to the research questions being asked. Howell uses real data and research studies as a basis and moves through an analysis of data. As FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES, Fourth Edition clearly demonstrates, it is not only important to concentrate on whether there is a difference between two groups but also to understand what the difference means.

Table of Contents

Introduction	1	(14)
The Importance of Context	3	(2)
Basic Terminology	5	(3)
Selection Among Statistical Procedures	8	(2)
Using Computers	10	(2)
Summary	12	(1)
Exercises	12	(3)
Basic Concepts	15	(15)
Scales of Measurement	16	(4)
Variables	20	(1)
Random Sampling	21	(1)
Notation	22	(2)
Summary	24	(1)
Exercises	25	(5)
Displaying Data	30	(24)
A First Look at the Data	31	(3)
Stem-and-Leaf Displays	34	(3)
Histograms	37	(3)
Alternative Methods of Plotting Data	40	(3)
Describing Distributions	43	(3)
Using Computer Programs to Display Data	46	(1)
Summary	47	(1)
Exercises	48	(6)
Measures of Central Tendency	54	(9)
The Mode	55	(1)
The Median	55	(1)
The Mean	56	(1)
Advantages and Disadvantages of the Mode, the Median, and the Mean	57	(2)
Obtaining Measures of Central Tendency Using Minitab	59	(1)
Summary	60	(1)
Exercises	61	(2)
Measures of Variability	63	(23)
Range	66	(1)
Interquartile Range and Other Range Statistics	67	(1)
The Average Deviation	67	(1)
The Variance	68	(1)
The Standard Deviation	69	(1)
Computational Formulae for the Variance and the Standard Deviation	70	(2)
The Mean and the Variance as Estimators	72	(2)
Boxplots: Graphical Representations of Dispersions and Extreme Scores	74	(4)
Obtaining Measures of Dispersion Using JMP	78	(2)
A Final Worked Example	80	(2)
Summary	82	(1)
Exercises	83	(3)
The Normal Distribution	86	(18)
The Normal Distribution	88	(4)
The Standard Normal Distribution	92	(6)
Setting Probable Limits on an Observation	98	(1)
Measures Related to z	99	(1)
Summary	100	(1)
Exercises	100	(4)
Basic Concepts of Probability	104	(14)
Probability	105	(2)
Basic Terminology and Rules	107	(4)
Discrete versus Continuous Variables	111	(1)
Probability Distributions for Discrete Variables	112	(1)
Probability Distributions for Continuous Variables	113	(2)
Summary	115	(1)
Exercises	116	(2)
Sampling Distributions and Hypothesis Testing	118	(23)
Two Simple Examples Involving Course Evaluations and Rude Motorists	120	(2)
Sampling Distributions	122	(1)
Hypothesis Testing	123	(2)
The Null Hypothesis	125	(1)
Test Statistics and Their Sampling Distributions	126	(1)
Using the Normal Distribution to Test Hypotheses	127	(3)
Type I and Type II Errors	130	(3)
One- and Two-Tailed Tests	133	(3)
A Final Worked Example	136	(1)
Back to Course Evaluations and Rude Motorists	137	(1)
Summary	138	(1)
Exercises	139	(2)
Correlation	141	(31)
Scatter Diagrams	142	(6)
An Example: The Relationship Between Speed and Accuracy	148	(3)
The Covariance	151	(1)
The Pearson Product-Moment Correlation Coefficient (r)	152	(2)
Correlations with Ranked Data	154	(1)
Factors That Affect the Correlation	155	(3)
If Something Looks Too Good to Be True, Perhaps It Is	158	(1)
Testing the Significance of a Correlation Coefficient	159	(2)
Intercorrelation Matrices	161	(2)
Other Correlation Coefficients	163	(1)
Using Minitab and SPSS to Obtain Correlation Coefficients	164	(2)
A Final Worked Example	166	(2)
Summary	168	(1)
Exercises	169	(3)
Regression	172	(25)
The Relationship Between Stress and Health	173	(2)
The Basic Data	175	(1)
The Regression Line	176	(4)
The Accuracy of Prediction	180	(6)
Hypothesis Testing in Regression	186	(1)
Computer Solution Using SPSS	187	(2)
A Final Worked Example	189	(2)
Summary	191	(1)
Exercises	192	(5)
Multiple Regression	197	(26)
Course Evaluations Again	200	(5)
Residuals	205	(2)
The Visual Representation of Multiple Regression	207	(1)
Hypothesis Testing	208	(2)
Refining the Regression Equation	210	(1)
A Second Example: Height and Weight	211	(3)
A Third Example: Psychological Symptoms in Cancer Patients	214	(4)
Summary	218	(1)
Exercises	219	(4)
Hypothesis Tests Applied to Means: One Sample	223	(24)
Sampling Distribution of the Mean	225	(2)
Testing Hypotheses About Means When σ is Known	227	(3)
Testing a Sample Mean When σ Is Unknown (One-Sample t Test)	230	(6)
Factors That Affect the Magnitude of t and the Decision About H0	236	(1)
A Second Example: The Moon Illusion	237	(1)
Confidence Limits on the Mean	238	(3)
Using a Computer Program to Run One-Sample t Tests	241	(1)
A Final Worked Example	242	(1)
Summary	243	(1)
Exercises	244	(3)
Hypothesis Tests Applied to Means: Two Related Samples	247	(12)
Related Samples	248	(1)
Student's t Applied to Difference Scores	249	(3)
A Second Example: The Moon Illusion Again	252	(1)
Advantages and Disadvantages of Using Related Samples	253	(1)
Using Computer Software for t Tests on Related Samples	254	(1)
Summary	255	(1)
Exercises	256	(3)
Hypothesis Tests Applied to Means: Two Independent Samples	259	(20)
Distribution of Differences Between Means	260	(7)
Heterogeneity of Variance	267	(1)
Nonnormality of Distributions	268	(1)
A Second Example with Two Independent Samples	269	(1)
Confidence Limits on μ1 -- μ2	270	(1)
Use of Computer Programs for Analysis of Two Independent Sample Means	271	(3)
A Final Worked Example	274	(2)
Summary	276	(1)
Exercises	276	(3)
Power	279	(20)
The Basic Concept	281	(1)
Factors That Affect the Powr of a Test	282	(2)
Effect Size	284	(2)
Power Calculations for the One-Sample t Test	286	(3)
Power Calculations for Differences Between Two Independent Means	289	(3)
Power Calculations for the t Test for Related Samples	292	(2)
Power Considerations in Terms of Sample Size	294	(1)
You Don't Have to Do It by Hand	295	(1)
Summary	296	(1)
Exercises	296	(3)
One-way Analysis of Variance	299	(36)
The General Approach	300	(3)
The Logic of the Analysis of Variance	303	(5)
Calculations for the Analysis of Variance	308	(7)
Unequal Sample Sizes	315	(1)
Multiple Comparison Procedures	316	(8)
Violations of Assumptions	324	(1)
Magnitude of Effect	325	(1)
Using JMP for a One-Way Analysis of Variance	326	(1)
A Final Worked Example	326	(4)
Summary	330	(1)
Exercises	331	(4)
Factorial Analysis of Variance	335	(22)
Factorial Designs	336	(2)
The Extension of the Eysenck Study	338	(5)
Interactions	343	(2)
Simple Effects	345	(3)
Unequal Sample Sizes	348	(1)
Magnitude of Effect	348	(1)
A Final Example: Maternal Adaptation Revisited	349	(2)
Using SPSS for Factorial Analysis of Variance	351	(1)
Summary	352	(1)
Exercises	353	(4)
Repeated-Measures Analysis of Variance	357	(14)
An Example: The Treatment of Migraine Headaches	358	(2)
Multiple Comparisons	360	(2)
Assumptions Involved in Repeated-Measures Designs	362	(1)
Advantages and Diadvantages of Repeated-Measures Designs	362	(1)
Using BMDP to Analyze Data in a Repeated-Measures Design	363	(3)
A Final Worked Example	366	(2)
Summary	368	(1)
Exercises	368	(3)
Chi-Square	371	(22)
One Classification Variable: The Chi-Square Goodness-of-Fit Test	373	(5)
Two Classification Variables: Contingency Table Analysis	378	(2)
Correction for Continuity	380	(1)
Chi-Square for Larger Contingency Tables	381	(1)
The Problem of Small Expected Frequencies	382	(1)
The Use of Chi-Square as a Test on Proportions	383	(2)
Nonindependent Observations	385	(1)
Minitab Analysis of Contingency Tables	386	(1)
A Final Worked Example	386	(2)
Summary	388	(1)
Exercises	389	(4)
Nonparametric and Distribution-Free Statistical Tests	393	(22)
The Mann--Whitney Test	395	(6)
Wilcoxon's Matched-Pairs Signed-Ranks Test	401	(4)
Kruskal--Wallis One-Way Analysis of Variance	405	(1)
Friedman's Rank Test for k Correlated Samples	406	(3)
Summary	409	(1)
Exercises	409	(6)
Choosing the Appropriate Analysis	415	(8)
Exercises and Examples	417	(6)
Appendix A Arithmetic Review	423	(6)
Appendix B Symbols and Notation	429	(3)
Appendix C Basic Statistical Formulae	432	(4)
Appendix D Dataset	436	(2)
Appendix E Statistical Tables	438	(19)
Glossary	457	(8)
References	465	(6)
Answers to Selected Exercises	471	(16)
Index	487