Essential Statistics For The Behavioral Sciences

by Heiman, Gary W.

• ISBN13: 9780618252008
• ISBN10: 0618252002
• Edition: 1st
• Format: Hardcover
• Copyright: 2003-07-28
• Publisher: Cengage Learning

Summary

This text uses the same conceptual, intuitive approach ofBasic Statistics for the Behavioral Sciences,but eliminates extensive reference material and advanced or obscure statistical methods.Essentialspresents only the procedures undergraduates need for reading research literature and conducting their own studies. New terms are integrated with more difficult concepts in an accessible, non-threatening format that provides concise explanations, creating a foundation and making further elaboration easier to understand. A Quick Reviewsections revisit concepts, provide worked-out examples, and help students check comprehension through review questions. Computational formulas appear in color throughout each chapter and key terms are highlighted, reviewed in the chapter summary, and listed in a key terms section.

Table of Contents

Preface	xiii
Introduction to Statistics and Research	1	(17)
Chapter Essentials	1	(1)
Why Is It Important to Learn About Statistics? (And How Do You Do That?)	1	(1)
The Logic of Research	2	(5)
Samples and Populations	2	(1)
Understanding Variables	3	(1)
Understanding Relationships	4	(1)
The Consistency of a Relationship	5	(1)
When No Relationship Is Present	6	(1)
A Quick Review	7	(1)
Applying Descriptive and Inferential Statistics	7	(1)
Statistics versus Parameters	8	(1)
Understanding Experiments and Correlational Studies	8	(3)
Experiments	9	(1)
The Independent Variable	9	(1)
Conditions of the Independent Variable	9	(1)
The Dependent Variable	9	(1)
Drawing Conclusions from an Experiment	10	(1)
Correlational Studies	10	(1)
A Quick Review	11	(1)
The Characteristics of the Scores	12	(2)
The Four Types of Measurement Scales	12	(1)
Continuous versus Discrete Scales	13	(1)
A Quick Review	14	(1)
Chapter Summary	14	(1)
Key Terms	15	(1)
Review Questions	15	(1)
Application Questions	16	(2)
Creating and Using Frequency Distributions	18	(19)
Chapter Essentials	18	(1)
Some New Symbols and Terminology	18	(1)
Understanding Frequency Distributions	19	(1)
Presenting Frequency in a Table	19	(1)
A Quick Review	20	(3)
Graphing a Frequency Distribution	21	(1)
Creating Bar Graphs	21	(1)
Creating Histograms	21	(2)
Creating Frequency Polygons	23	(1)
A Quick Review	23	(1)
Types of Frequency Distributions	24	(4)
The Normal Distribution	24	(2)
Skewed Distributions	26	(1)
Bimodal Distributions	26	(1)
How to Label Distributions	27	(1)
A Quick Review	28	(1)
Relative Frequency and the Normal Curve	29	(3)
Understanding Relative Frequency and Percent	29	(1)
Finding Relative Frequency Using the Normal Curve	30	(2)
A Quick Review	32	(1)
Understanding Percentile	32	(1)
Chapter Summary	33	(1)
Key Terms	34	(1)
Review Questions	34	(1)
Application Questions	34	(2)
Summary of Formulas	36	(1)
Summarizing Scores with Measures of Central Tendency	37	(19)
Chapter Essentials	37	(1)
Some New Symbols and Terminology	37	(1)
What Is Central Tendency?	38	(4)
The Mode	39	(1)
The Median	40	(2)
A Quick Review	42	(1)
The Mean	42	(1)
A Quick Review	43	(2)
Comparing the Mean, Median, and Mode	44	(1)
Applying the Mean to Research	45	(5)
Deviations Around the Mean	45	(2)
Summarizing an Experiment	47	(1)
Graphing the Results of an Experiment	48	(2)
A Quick Review	50	(2)
Describing the Population Mean	51	(1)
Chapter Summary	52	(1)
Key Terms	52	(1)
Review Questions	53	(1)
Application Questions	53	(2)
Summary of Formulas	55	(1)
Summarizing Scores with Measures of Variability	56	(20)
Chapter Essentials	56	(1)
Understanding Variability	56	(2)
The Range	58	(1)
The Variance and Standard Deviation	58	(5)
Understanding the Sample Variance	59	(1)
Understanding the Sample Standard Deviation	60	(3)
A Quick Review	63	(1)
Computing the Sample Variance and Sample Standard Deviation	63	(3)
Computing the Sample Variance	64	(1)
Computing the Sample Standard Deviation	65	(1)
A Quick Review	66	(1)
The Population Variance and the Population Standard Deviation	66	(4)
Estimating the Population Variance and Population Standard Deviation	67	(1)
Computing the Estimated Population Variance and Standard Deviation	68	(1)
Interpreting the Estimated Population Variance and Standard Deviation	69	(1)
A Quick Review	70	(1)
Summary of the Variance and Standard Deviation	71	(1)
Statistics in the Research Literature: Reporting Means and Variability	71	(1)
Chapter Summary	72	(1)
Key Terms	73	(1)
Review Questions	73	(1)
Application Questions	74	(1)
Summary of Formulas	75	(1)
Describing Data with z-Scores and the Normal Curve	76	(22)
Chapter Essentials	76	(1)
Understanding z-Scores	76	(4)
Describing a Score's Relative Location as a z-Score	77	(1)
Computing z-Scores	78	(1)
Computing a Raw Score When z is Known	79	(1)
A Quick Review	80	(1)
Using z-Scores to Describe Raw Scores	80	(7)
Using z-Scores to Describe Relative Standing	81	(1)
Using z-Scores to Compare Variables	82	(1)
Using z-Scores to Compute Relative Frequency	83	(1)
The Standard Normal Curve	83	(2)
Using the z-Tables	85	(2)
A Quick Review	87	(1)
Using z-Scores to Describe Sample Means	88	(6)
The Sampling Distribution of Means	88	(2)
The Standard Error of the Mean	90	(1)
Computing a z-Score for a Sample Mean	91	(1)
Describing the Relative Frequency of Sample Means	92	(1)
Summary of Describing a Sample Mean with a z-Score	93	(1)
A Quick Review	94	(1)
Chapter Summary	94	(1)
Key Terms	95	(1)
Review Questions	95	(1)
Application Questions	96	(1)
Summary of Formulas	97	(1)
Using Probability to Make Decisions about Data	98	(19)
Chapter Essentials	98	(1)
Understanding Probability	98	(2)
Probability Distributions	100	(1)
A Quick Review	101	(1)
Obtaining Probability from the Standard Normal Curve	101	(3)
Determining the Probability of Sample Means	102	(2)
A Quick Review	104	(1)
Random Sampling and Sampling Error	105	(1)
Deciding Whether a Sample Represents a Population	106	(2)
A Quick Review	108	(4)
Setting Up the Sampling Distribution	108	(1)
Identifying the Critical Value	109	(1)
Deciding whether the Sample Represents a Population	110	(1)
Summary of How to Decide About the Population Being Represented	111	(1)
A Quick Review	112	(1)
Other Ways to Set Up the Sampling Distribution	112	(2)
Chapter Summary	114	(1)
Key Terms	114	(1)
Review Questions	114	(1)
Application Questions	115	(1)
Summary of Formulas	116	(1)
Overview of Statistical Hypothesis Testing: The z-Test	117	(21)
Chapter Essentials	117	(1)
The Role of Inferential Statistics in Research	117	(1)
Setting Up Inferential Procedures	118	(4)
Creating the Experimental Hypotheses	119	(1)
Designing a One-Sample Experiment	119	(1)
Creating the Statistical Hypotheses	120	(1)
The Alternative Hypothesis	120	(1)
The Null Hypothesis	121	(1)
A Quick Review	122	(1)
The Logic of Statistical Hypothesis Testing	122	(1)
Performing the z-Test	123	(3)
Setting Up the Sampling Distribution for a Two-Tailed Test	124	(1)
Computing z	125	(1)
Comparing the Obtained z to the Critical Value	125	(1)
Interpreting Significant Results	126	(1)
Interpreting Nonsignificant Results	127	(1)
Summary of the z-Test	128	(1)
A Quick Review	129	(1)
Statistics in the Research Literature: Reporting z	129	(1)
The One-Tailed Test	130	(2)
The One-Tailed Test for Increasing Scores	130	(1)
The One-Tailed Test for Decreasing Scores	131	(1)
A Quick Review	132	(1)
Errors in Statistical Decision Making	132	(2)
Type I Errors	132	(1)
Type II Errors and Power	133	(1)
Chapter Summary	134	(1)
Key Terms	135	(1)
Review Questions	135	(1)
Application Questions	136	(1)
Summary of Formulas	137	(1)
Hypothesis Testing Using the One-Sample t-Test	138	(16)
Chapter Essentials	138	(1)
Understanding the One-Sample t-Test	138	(2)
Performing the One-Sample t-Test	140	(1)
A Quick Review	141	(4)
The t-Distribution and df	142	(2)
Using the t-Tables	144	(1)
Interpreting the t-Test	145	(1)
Performing One-Tailed Tests	145	(1)
Summary of the One-Sample t-Test	146	(1)
A Quick Review	147	(1)
Estimating μ by Computing a Confidence Interval	147	(3)
Computing the Confidence Interval	148	(2)
A Quick Review	150	(1)
Statistics in the Research Literature: Reporting t	150	(1)
Chapter Summary	151	(1)
Key Terms	151	(1)
Review Questions	151	(1)
Application Questions	152	(1)
Summary of Formulas	153	(1)
Hypothesis Testing Using the Two-Sample t-Test	154	(24)
Chapter Essentials	154	(1)
Understanding the Two-Sample Experiment	154	(1)
The Independent-Samples t-Test	155	(6)
Statistical Hypotheses for the Independent-Samples t-Test	156	(1)
The Sampling Distribution for the Independent-Samples t-Test	157	(1)
Computing the Independent-Samples t-Test	158	(3)
A Quick Review	161	(2)
Interpreting the Independent-Samples t-Test	161	(2)
Performing One-Tailed Tests on Independent Samples	163	(1)
Summary of the Independent-Samples t-Test	163	(1)
A Quick Review	164	(1)
The Related-Samples t-Test	164	(6)
The Logic of the Related-Samples t-Test	165	(1)
Statistical Hypotheses for the Related-Samples t-Test	166	(1)
Computing the Related-Samples t-Test	167	(2)
Interpreting the Related-Samples t-Test	169	(1)
One-Tailed Hypotheses with the Related-Samples t-Test	170	(1)
Summary of the Related-Samples t-Test	170	(1)
A Quick Review	170	(1)
Statistics in the Research Literature: Reporting a Two-Sample Study	171	(1)
A Word About Effect Size: The Proportion of Variance Accounted For	171	(2)
Chapter Summary	173	(1)
Key Terms	174	(1)
Review Questions	174	(1)
Application Questions	174	(3)
Summary of Formulas	177	(1)
Describing Relationships Using Correlation and Regression	178	(23)
Chapter Essentials	178	(1)
Understanding Correlations	178	(8)
Distinguishing Characteristics of Correlational Analysis	179	(1)
Types of Relationships	180	(1)
Linear Relationships	180	(1)
Nonlinear Relationships	181	(1)
How the Coefficient Describes the Type of Relationship	182	(1)
Strength of the Relationship	183	(1)
The Perfect Correlation	183	(1)
Intermediate Strength	184	(1)
Zero Correlation	185	(1)
A Quick Review	186	(1)
The Pearson Correlation Coefficient	187	(2)
Computing the Pearson Correlation Coefficient	187	(2)
A Quick Review	189	(5)
Significance Testing of the Pearson r	190	(1)
The Sampling Distribution of r	191	(1)
Drawing Conclusions About r	192	(1)
One-Tailed Tests of r	193	(1)
Summary of the Pearson Correlation Coefficient	194	(1)
A Quick Review	194	(1)
Statistics in the Research Literature: Reporting r	194	(1)
A Word About Linear Regression	195	(1)
A Word About the Proportion of Variance Accounted For: r2	196	(1)
Chapter Summary	197	(1)
Key Terms	198	(1)
Review Questions	198	(1)
Application Questions	199	(1)
Summary of Formulas	200	(1)
Hypothesis Testing Using the One-Way Analysis of Variance	201	(22)
Chapter Essentials	201	(1)
An Overview of the Analysis of Variance	201	(4)
Controlling the Experiment-Wise Error Rate	203	(1)
Statistical Hypotheses in ANOVA	203	(1)
The F Statistic and Post Hoc Comparisons	204	(1)
A Quick Review	205	(1)
Components of the ANOVA	205	(2)
The Mean Square Within Groups	205	(1)
The Mean Square Between Groups	206	(1)
Comparing the Mean Squares: The Logic of the F-Ratio	206	(1)
Performing the ANOVA	207	(6)
Computing Fobt	208	(1)
Computing the Sums of Squares	208	(2)
Computing the Degrees of Freedom	210	(1)
Computing the Mean Squares	210	(1)
Computing the F	211	(1)
Interpreting Fobt	211	(2)
A Quick Review	213	(1)
Tukey Post Hoc Comparisons	214	(2)
A Quick Review	216	(1)
Summary of the One-Way ANOVA	216	(1)
Statistics in the Research Literature: Reporting ANOVA	217	(1)
A Word about Effect Size and Eta2	217	(1)
Chapter Summary	218	(1)
Key Terms	219	(1)
Review Questions	219	(1)
Application Questions	220	(2)
Summary of Formulas	222	(1)
A Brief Introduction to the Logic of the Two-Way Analysis of Variance	223	(16)
Chapter Essentials	223	(1)
Understanding the Two-Way ANOVA	223	(3)
The Main Effect of Factor A	225	(1)
The Main Effect of Factor B	226	(1)
A Quick Review	226	(3)
The Interaction Effect	227	(2)
A Quick Review	229	(1)
Interpreting the Two-Way Experiment	230	(4)
Completing the Main Effects	230	(1)
Graphing the Interaction Effect	231	(1)
Performing Unconfounded Post Hoc Comparisons on the Interaction	232	(1)
Interpreting the Experiment	233	(1)
Chapter Summary	234	(1)
Key Terms	235	(1)
Review Questions	235	(1)
Application Questions	236	(3)
Chi Square and Nonparametric Procedures	239	(19)
Chapter Essentials	239	(1)
Parametric versus Nonparametric Statistics	239	(1)
Chi Square Procedures	240	(1)
One-Way Chi Square: The Goodness of Fit Test	241	(4)
Hypotheses and Assumptions for the One-Way Chi Square	241	(1)
Computing the One-Way χ2	242	(1)
Interpreting the One-Way χ2	243	(2)
A Quick Review	245	(1)
The Two-Way Chi Square: The Test of Independence	246	(4)
Logic of the Two-Way Chi Square	246	(2)
Computing the Two-Way Chi Square	248	(2)
A Quick Review	250	(2)
Describing the Relationship in a Two-Way Chi Square	251	(1)
Statistics in the Research Literature: Reporting χ2	252	(1)
A Word about Nonparametric Procedures for Ordinal Scores	252	(1)
Chapter Summary	253	(1)
Key Terms	254	(1)
Review Questions	254	(1)
Application Questions	255	(2)
Summary of Formulas	257	(1)
Appendixes	258	(34)
A Additional Statistical Formulas	258	(13)
A.1: Confidence Intervals for the Two-Sample t-Test	258	(2)
A.2: Computing the Two-Way, Between-Subjects ANOVA	260	(11)
B Statistical Tables	271	(13)
Table 1 Proportions of Area Under the Standard Normal Curve: The z-Tables	272	(4)
Table 2 Critical Values of t: The t-Tables	276	(1)
Table 3 Critical Values of the Pearson Correlation Coefficient: The r-Tables	277	(1)
Table 4 Critical Values of F: The F-Tables	278	(3)
Table 5 Values of Studentized Range Statistic, qk	281	(2)
Table 6 Critical Values of Chi Square: The χ2-Tables	283	(1)
C Answers to Odd-Numbered Questions	284	(8)
Glossary	292	(6)
Index	298