The Process of Statistical Analysis in Psychology
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The Process of Statistical Analysis in Psychology



September 2017 | 448 pages | SAGE Publications, Inc
The Process of Statistical Analysis in Psychology is the latest book by Dawn McBride, the best-selling author of The Process of Research in Psychology. This new text provides students with the background and the process of statistical analysis along with the nuts and bolts tools for applying specific statistical tools to data from research studies. While the two texts correspond closely in their use of research examples, they can also be used completely independently of one another. McBride will help students to understand that statistics can be applied and used in day to day life, and she will make a direct connection between the process of research design and the tools employed in statistical analysis.
 
Part I: Why Do We Use Statistics?
 
Chapter 1: Why Statistics?
A. What can statistics do for me?  
B. Research design and statistics  
 
Chapter 2: The Starting Place: Data and Distributions
A. Populations and samples  
B. Types of data collected in research in psychology  
C. Frequency distributions  
D. Frequency distributions in Excel  
E. Introduction to SPSS  
 
Chapter 3: Probability and sampling
A. Concepts of probability  
B. Sampling techniques  
C. Distribution of sample means introduction  
 
Part II: Descriptive Statistics
 
Chapter 4: Central Tendency
A. Central tendency in distributions  
B. Mean  
C. Median  
D. Mode  
E. Which measure of central tendency should I use?  
 
Chapter 5: Variability
A. Variability in distributions  
B. Range and Interquartile Range  
C. Standard deviation  
D. Which measure of variability should I use?  
 
Chapter 6: Presenting Descriptive Statistics
A. Descriptive statistics in graphs  
B. Descriptive statistics in tables  
C. APA style for graphs and tables  
 
Part III: Basics of Hypothesis Testing
 
Chapter 7: The Normal Distribution and z-Scores
A. The z-score transformation  
B. The normal distribution  
 
Chapter 8: Hypothesis Testing Logic
A. Using the normal distribution to test hypotheses  
B. Logic of hypothesis testing  
C. Types of hypothesis testing errors  
D. Statistical significance  
 
Part IV: The Nuts and Bolts of Statistical Tests
 
Chapter 9: The t-distribution
A. The t-distribution – when we don’t know the value of the population standard deviation  
B. One-sample t-test  
C. Using SPSS to conduct a one-sample t-test  
D. Test Assumptions  
 
Chapter 10: Related/paired samples t-test
A. Samples with related/paired data  
B. Calculating a related/paired samples t-test  
C. Using SPSS to conduct related/paired samples t-test  
D. Test Assumptions  
 
Chapter 11: Independent samples t-test
A. Independent samples  
B. Calculating independent samples t scores  
C. Using SPSS to Conduct an independent samples t-test  
D. Test Assumptions  
 
Chapter 12: One-way ANOVA
A. More than two independent samples  
B. Calculating the F score in an ANOVA  
C. Using SPSS to calculate One-way between-subjects ANOVA  
D. Test Assumptions  
 
Chapter 13: Two-way ANOVA
A. Factorial designs  
B. Calculating two-way F scores  
C. Using SPSS to calculate Two-way between-subjects ANOVA  
D. Test Assumptions  
E. Understanding interactions  
 
Chapter 14: One-way within-subjects ANOVA
A. Within-subjects designs  
B. Calculating one-way within-subjects F scores  
C. Using SPSS to calculate one-way repeated-measures ANOVA  
D. Test Assumptions  
E. More Complex Within-Subjects Designs  
 
Chapter 15: Correlation Tests and Simple linear regression
A. Correlation versus Causation  
B. Hypothesis Testing with Pearson r  
C. Using SPSS to conduct a Pearson r test  
D. Regression Analyses  
E. Non-Linear Relationships  
 
Chapter 16: Chi-square tests
A. Parametric versus non-parametric tests  
B. Observed versus expected frequencies  
C. Calculating Chi-Square by hand  
D. Calculating Chi-Square using SPSS  

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ISBN: 9781506325224