Communication Research StatisticsWhile most books on statistics seem to be written as though targeting other statistics professors, John Reinard's Communication Research Statistics is especially impressive because it is clearly intended for the student reader, filled with unusually clear explanations and with illustrations on the use of SPSS. I enjoyed reading this lucid, student-friendly book and expect students will benefit enormously from its content and presentation. Well done!" --John C. Pollock, The College of New Jersey Written in an accessible style using straightforward and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research undertaken in communication studies. This introductory textbook is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel XP. |
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Contents
Central Tendency | 45 |
Looking at Variability and Dispersion | 61 |
Correlations | 87 |
Ensuring Reliability and Validity | 117 |
Statistical Significance Hypothesis | 145 |
OneWay Analysis of Variance | 179 |
Factorial Analysis of Variance | 213 |
Nonparametric Tests for Categorical Variables | 249 |
Extensions of Multiple Regression Correlation | 381 |
Exploratory Factor Analysis | 403 |
Confirmatory Factor Analysis Through the Amos Program | 427 |
Modeling Communication Behavior | 451 |
Using Excel XP to Analyze Data | 489 |
Using SPSS 12 for Windows | 503 |
References | 553 |
569 | |
Nonparametric Tests for Rank Order Dependent Variables | 281 |
MetaAnalysis | 315 |
Multiple Regression Correlation | 345 |
About the Author 583 | |
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Common terms and phrases
actually addition alpha risk analysis of variance approach assumptions button called cell Chapter chi-square clicks coefficient column communication comparisons completed computed confidence Continue contrast correlation covariance critical degrees of freedom dependent variable dialog box distribution effect equal error estimate evidence examine example expected factor analysis formula frequency groups Help Hence identify independent indicate instance interaction interest interpretation interval involves levels Limit linear look mean measures menu method multiple normal null hypothesis observed options output population positive predicted predictor variables probability proportion random range ranks ratings reason regression relationship reliability represent researcher residuals sample sizes scale scores shows sometimes SPSS square standard deviation statistically significant studies Table term Type validity variance weights