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Introduction | p. xi |
The Scientific Foundations of Statistical Analysis | |
Scientific Method: The Language of Statistical Studies | p. 3 |
Science as a Universal Language | p. 5 |
The Attributes of Scientific Method | p. 8 |
Science Is Open-Minded | p. 8 |
Science Is Free of Values | p. 9 |
Science Is Thoughtful | p. 10 |
Science Is Reproducible | p. 11 |
Science Is Honest | p. 13 |
The Attributes of a Scientific Report | p. 14 |
Abstract | p. 15 |
Introduction and Problem Statement | p. 16 |
Review of Literature | p. 17 |
Methods (Methodology) | p. 18 |
Data | p. 19 |
Results and Discussion | p. 20 |
Experimentation: The Foundation of Scientific Studies | p. 23 |
What Is an Experiment? | p. 24 |
The Hypothesis | p. 26 |
The Experiment | p. 28 |
Randomly Select the Study Sample from the Population | p. 29 |
Randomly Assign the Study Sample to Experimental and Control Groups | p. 31 |
Establish Pretest (Baseline) Measures for Experimental and Control Groups | p. 32 |
Administer an Experimental Effect to an Experimental Group Only | p. 33 |
Establish Posttest Measures for Experimental and Control Groups | p. 33 |
Analyze Experimental Data for Statistical Significance | p. 33 |
Evaluation Studies | p. 34 |
The Fundamental Importance of Data | |
Numbers Good and Bad: How to Judge the Quality of Data | p. 39 |
Letting the Numbers Speak for Themselves | p. 40 |
What Are Data? | p. 42 |
Validity | p. 43 |
Reliability | p. 45 |
Location Bias | p. 46 |
Sex Sampling Bias | p. 47 |
Dollar Measurement Bias | p. 47 |
Counting Error | p. 49 |
Definitional Error | p. 49 |
Adjustment Error | p. 49 |
Time Measurement Error | p. 50 |
Types and Levels of Measurement | p. 52 |
Parametric Data | p. 53 |
Nonparametric Data | p. 54 |
Samples and Surveys: How Numbers Should Be Collected | p. 57 |
Sample Selection | p. 57 |
Sample Size | p. 58 |
Response Rate | p. 62 |
Information Systems | p. 64 |
Survey Research | p. 65 |
Survey Bias | p. 66 |
Respondent Objectivity | p. 67 |
Survey Format | p. 69 |
Data Extraction | p. 71 |
The Different Types of Statistics | |
Descriptive Statistics: The Foundation of Comparisons | p. 77 |
The First Step: What Have We Here? | p. 78 |
Descriptive Analysis | p. 78 |
Range | p. 80 |
Measures of Central Tendency | p. 83 |
Median | p. 84 |
Mode | p. 84 |
Mean | p. 87 |
Measures of Dispersion | p. 89 |
Overview | p. 89 |
Standard Deviation | p. 91 |
Inferential Statistics: Studies of Differences | p. 97 |
The Normal Distribution | p. 98 |
The Central Limit Theorem | p. 103 |
Standard Error (of the Mean) | p. 104 |
Quick Review | p. 106 |
Hypothesis Testing | p. 106 |
Accepting the Null Hypothesis | p. 111 |
Rejecting the Null Hypothesis | p. 111 |
Test Statistics | p. 114 |
t Test | p. 116 |
F Test (Analysis of Variance) | p. 116 |
Chi-Square Test | p. 119 |
The End of the Tunnel | p. 123 |
Relational Statistics: Studies of Relationships | p. 125 |
Direction of Relationships | p. 126 |
Strength of Relationships | p. 127 |
Test Statistics | p. 130 |
Parametric Correlation | p. 130 |
Nonparametric Correlation | p. 132 |
Linear versus Nonlinear Relationships | p. 132 |
Correlation and Causality | p. 134 |
Explanatory Statistics: Studies of Causality | p. 137 |
Statistical Models | p. 138 |
The Basic Equation of Multivariate Linear Regression Model | p. 140 |
Specifying the Model | p. 141 |
Evaluating a Multivariate Linear Regression Model | p. 144 |
Refining Regression Models | p. 150 |
Applications of Explanatory Statistics | p. 150 |
Postscript: Statistics in Perspective | p. 153 |
Index | p. 155 |
About the Author | p. 157 |
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