I. Scientific research
1. Science 3 [pdf]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 122. 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 213. Operationalizing 23
Operational definitions 23
Measurement 23
Scaling 25
Levels of scaling 25
Which level of scaling to use? 274. Validity and reliability 29
Face validity 29
Criterion/pragmatic/predictive validity 29
Construct validity 30
Internal and External validity 30
Measurement Error 305. 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 45 [pdf]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 567. Distributions 59
The normal distribution 62
Table 1: Areas under the normal curve 64
Examples 658. The normal curve and samples: sampling distributions 69 [pdf]
Sampling distributions 70
Standard errors: standard deviations of sampling distributions 729. 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 7710. 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 87How to read a crosstabulation 88
How to interpret the table 9112. 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 10413. Strength of relationships: Continuous data 107 [pdf]
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 11314. 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 123Sampling 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 . . . 12616. 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 13017. 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 14218. 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 14919. 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 154
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 163The 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 16921. 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 1931. 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 210C. Glossary 215
D. Exercises 233References 257
Index 259