I. Scientific research

1. Science    [pdf]	3
Science 4 Single instances vs. general patterns 5 Three assumptions of science 6 A scientific approach to communication research 8 Theory 8 Constructing theory 10 Verifying theoretical explanations 11 Research design 12

2. Conceptualizing	17
Concepts and constructs 17 Variables 18 Research questions 18 The problem statement 19 Assessing problem statements 19 Defining the terms in problem statements 20 Conceptual definitions 21 Assessing conceptual definitions 21

3. Operationalizing	23
Operational definitions 23  Measurement 23  Scaling 25  Levels of scaling 25  Which level of scaling to use? 27

4. Validity and reliability	29
Face validity 29  Criterion/pragmatic/predictive validity 29  Construct validity 30  Internal and External validity 30  Measurement Error 30

5. Sampling	35
Sample designs 36 Non-probability samples 36 Accidental or convenience samples 37 Purposive samples 37 Quota or proportionate sample 37 Probability samples 37 Simple random samples 37 Systematic samples 38 Stratified random sample 39 Cluster samples 39

II. Univariate Statistics

6. Univariate descriptive statistics    [pdf]

45

Descriptive and inferential statistics 45 Descriptive statistics 46 Central Tendency 46 The mode 46 The median 47 The mean 47 Dispersion 48 The range 49 The interquartile range (IQR) 49 Variance 49 Standard deviation 50 Standard scores (or "z-scores") 51 Calculating standard deviation 52 Sample or population? 53 The uses of the standard deviation 53 How to calculate standard deviation: original method 55 How to calculate standard deviation: computational method 56

7. Distributions	59
The normal distribution 62 Table 1: Areas under the normal curve 64 Examples 65

8. The normal curve and samples: sampling distributions [pdf]	69
Sampling distributions 70 Standard errors: standard deviations of sampling distributions 72

9. Inferential statistics: from samples to populations	75
Standard Errors 77 The standard error of the mean 77 The standard error of proportions 77 The standard error of the difference between means 77

10. Univariate inferential statistics	79
Estimating confidence intervals 79 How to do it 80 Z-test of a single mean 82

III. Bivariate Descriptive Statistics

11. Crosstabulation	87
How to read a crosstabulation 88 How to interpret the table 91

12. Strength of relationships: Discrete data	93
Measures of strength of association 93 Level of scaling 93 Symmetric vs. asymmetric measures 93 "Standard" vs. "nonstandard" measures 94 Nominal data 94 Lambda 95 Yule's Q 96 Pearson's phi coefficient ( ) 98 The PRE interpretation of Pearson's 99 Ordinal data 99 Goodman and Kruskal's gamma 99 How to interpret gamma 101 Problems with gamma 101 Somer's d 102 Spearman's rho 102 Summary 104

13. Strength of relationships: Continuous data [pdf]	107
The first change: covariance 107 An easier way to calculate covariance 109 The second change: correlation 110 Why correlation is better than covariance 111 Calculating r 111 r based on z-scores 111 r based on deviation scores 112 The computational equation for r 112 A gallery of correlations 113

14. Regression	115
The regression line 115 Regression equation 116 Residuals 116 Explained variance 117 Correlation and residuals 118 Multiple regression 119 Linear vs curvilinear regression 119

IV. Hypothesis testing

15. Statistical significance	123
Sampling variability . . . or not? 123 The null hypothesis 124 Let's take a chance 125 Testing the null hypothesis 125 Critical values 125 If you reject the null hypothesis . . . 126

16. Chi-squared	127
Observed vs expected 127 How to calculate the expected values 128 Calculating chi-squared 128 How big is the difference? 129 Summary of the procedure 130

17. z-test for differences between means	135
Hypotheses about differences 135 One or two tails? 138 Undirected hypotheses 139 Directed hypotheses 139 Common critical values of z 139 Examples 140 Procedure 142

18. Tests for correlations	145
Significance of Pearson's r 145 Difference between two rs 146 Significance of Spearman's rho 148 Difference between two rhos 149

19. More mean differences: z, t, and F	151
Critical ratios 151 Variance accounted for 152 z-test for difference between means 153 How to do it 153 Requirements 153 t-test for difference between two means 153 How to do it 154 Requirements 154 ANOVA — analysis of variance 156 ANOVA in detail 157 Sources or types of variance 157 ANOVA: an eight-step plan 158 Summary 160

V. Research approaches

20. Experiments	163
The stereotypical laboratory experiment 163 Not-quite experiments 164 Two-group designs 165 Four-group designs 166 Experimental controls and comparisons 166 The Experimental method reviewed 168 Advantages of the experimental method 168 Disadvantages of the experimental method 169

21. Survey research

171

The nature of survey research 171 Surveys and time 172 Selecting a representative sample 172 Define your population 173 Specify your sampling elements 173 Secure a sampling frame 173 Choose a sampling method 174 The survey questionnaire 175 Types of questions 176 Closed questions 176 Composite measures 177 Multiple-choice questions 179 Open-ended questions 179 Criteria for evaluating survey questions 180 Order of questions in surveys 180 Administering the survey questionnaire 181 Self-administered methods  181 Oral interview methods  182 Response rate problems  183 Total nonresponse  183 Item nonresponse  184

VI. Appendices

A. Equations

189

B. Tables	193
1. Areas under the normal curve 193 2. Critical values of Student's t 197 3. Critical values of chi-squared 198 4. Critical values of F 201 5. Pearson's r to Fisher's Z 207 6. Critical values of r 208 7. Random numbers 210

C. Glossary

215

D. Exercises

223

References	257
Index	259