A clear and comprehensive introduction to Statistics with step by step guidance on using SPSS to carry out statistical analysis. Understanding Statistics in Psychology with SPSSa is geared towards helping students to properly understand statistical techniques so gaining the confidence to apply them with the help of SPSS. The full text downloaded to your computer With eBooks you can: O search for key concepts, words and phrases O make highlights and notes as you study O share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit TheaeBooks products do not have an expiry date. You will continue to access youradigitalaebookaproducts whilst you have youraBookshelf installed.
Chapter 1 Why statistics? Chapter 2 Some basics: Variability and measurement Chapter 3 Describing variables: Tables and diagrams Chapter 4 Describing variables numerically: Averages, variation and spread Chapter 5 Shapes of distributions of scores Chapter 6 Standard deviation and z-scores: Standard unit of measurement in statistics Chapter 7 Relationships between two or more variables: Diagrams and tables Chapter 8 Correlation coefficients: Pearson's correlation and Spearman's rho Chapter 9 Regression: Prediction with precision Chapter 10 Samples from populations Chapter 11 Statistical significance for the correlation coefficient: A practical introduction to statistical inference Chapter 12 Standard error: Standard deviation of the means of samples Chapter 13 Related t-test: Comparing two samples of related/correlated/paired scores Chapter 14 Unrelated t-test: Comparing two samples of unrelated/uncorrelated/ independent scores Chapter 15 What you need to write about your statistical analysis Chapter 16 Confidence intervals Chapter 17 Effect size in statistical analysis: Do my findings matter? Chapter 18 Chi-square: Differences between samples of frequency data Chapter 19 Probability Chapter 20 One-tailed versus two-tailed significance testing Chapter 21 Ranking tests: Nonparametric statistics Chapter 22 Variance ratio test: F-ratio to compare two variances Chapter 23 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA Chapter 24 ANOVA for correlated scores or repeated measures Chapter 25 Two-way or factorial ANOVA for unrelated/uncorrelated scores: Two studies for the price of one? Chapter 26 Multiple comparisons with in ANOVA: A priori and post hoc tests Chapter 27 Mixed-design ANOVA: Related and unrelated variables together Chapter 28 Analysis of covariance (ANCOVA): Controlling for additional variables Chapter 29 Multivariate analysis of variance (MANOVA) Chapter 30 Discriminant (function) analysis - especially in MANOVA Chapter 31 Statistics and analysis of experiments Chapter 32 Partial correlation: Spurious correlation, third or confounding variables, suppressor variables Chapter 33 Factor analysis: Simplifying complex data Chapter 34 Multiple regression and multiple correlation Chapter 35 Path analysis Chapter 36 Meta-analysis: Combining and exploring statistical findings from previous research Chapter 37 Reliability in scales and measurement: Consistency and agreement Chapter 38 Influence of moderator variables on relationships between two variables Chapter 39 Statistical power analysis: Getting the sample size right Chapter 40 Log-linear methods: Analysis of complex contingency tables Chapter 41 Multinomial logistic regression: Distinguishing between several different categories or groups Chapter 42 Binomial logistic regression Chapter 43 Data mining and big data
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