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Statistics One
Andrew Conway
Statistics One is a comprehensive yet friendly introduction to statistics.
Workload: 5-8 hours/week
Watch intro video
Sessions:
Sep 22nd 2013 (12 weeks long)
https://www.coursera.org/course/stats1
Course Syllabus
Lecture Topics
Lecture 1: Experimental research
Lecture 2: Correlational research
Lecture 3: Variables and distributions
Lecture 4: Summary statistics
Lecture 5: Correlation
Lecture 6: Measurement
Lecture 7: Introduction to regression
Lecture 8: Null Hypothesis Significance Tests (NHST)
Lecture 9: Central limit theorem
Lecture 10: Confidence intervals
Lecture 11: Multiple regression
Lecture 12: Multiple regression continued
Lecture 13: Moderation
Lecture 14: Mediation
Lecture 15: Group comparisons (t-tests)
Lecture 16: Group comparisons (ANOVA)
Lecture 17: Factorial ANOVA
Lecture 18: Repeated measures ANOVA
Lecture 19: Chi-square
Lecture 20 Binary logistic regression
Lecture 21: Assumptions revisited (correlation and regression)
Lecture 22: Generalized Linear Model
Lecture 23: Assumptions revisited (t-tests and ANOVA)
Lecture 24: Non-parametrics (Mann-Whitney U, Kruskal-Wallis)
Lab Topics:
Lab 1: Download and install R
Lab 2: Histograms and summary statistics
Lab 3: Scatterplots and correlations
Lab 4: Regression
Lab 5: Confidence intervals
Lab 6: Multiple regression
Lab 7: Moderation and mediation
Lab 8: Group comparisons (t-tests, ANOVA, post-hoc tests)
Lab 9: Factorial ANOVA
Lab 10: Chi-square
Lab 11: Non-linear regression (Binary logistic and Poisson)
Lab 12: Non-parametrics (Mann-Whitney U and Kruskal-Wallis)
Также на R. Хочу некоторые вещи по стат.анализу у себя довести до автоматизма.