Explore a comprehensive 7-hour video series on statistics and data analysis from the University of California, Santa Cruz's EART125 class. Dive into fundamental concepts like central tendency, data dispersion, and confidence intervals. Master various statistical testing procedures, including t-tests, F-tests, ANOVA, and non-parametric tests. Learn about categorical data analysis, correlation techniques, and regression models. Advance to more complex topics such as MANOVA, linear mixed effects models, resampling methods, and principal component analysis. Gain practical skills in time series analysis, statistical power, and specialized regression techniques for count data. Equip yourself with a comprehensive toolkit for statistical analysis across diverse scientific disciplines.
Earth - Stats and Data Analysis
Matthew E. Clapham and University of California, Santa Cruz via YouTube
Overview
Syllabus
1: Central tendency (mean and median).
2: Data dispersion.
3: Standard error/confidence intervals.
Statistical testing procedures and the p value.
6: The t test.
7: the F test.
8: ANOVA.
Shapiro-Wilk test.
10: Kolmogorov-Smirnov test.
11: Mann-Whitney U test.
12: Kruskal-Wallis test.
13: Levene's Test.
14: Categorical data (intro and test choice).
15: Exact binomial test/exact multinomial test.
16: Fisher's exact test.
17: Chi-squared test.
18: Pearson product-moment correlation.
19: Non-parametric correlation.
Linear regression.
21: ANCOVA.
22: Logistic regression.
23: Mahalanobis distance.
24: Hotelling T2 test.
25: MANOVA.
Linear mixed effects models.
26: Resampling methods (bootstrapping).
27: Resampling (two-sample tests).
28: Principal Component Analysis.
29: Non-Metric Multidimensional Scaling (NMDS).
30: Maximum likelihood estimation.
Multiple regression.
Partial and semipartial correlation.
Generalized least squares regression.
Factorial ANOVA.
Nested ANOVA.
Time series and first differences.
Statistical power.
Regression with Count Data: Poisson and Negative Binomial.
Taught by
Matthew E. Clapham
