Learning Statistics: Concepts and Applications in R

[01] How to Summarize Data with Statistics [02] Exploratory Data Visualization in R [03] Sampling and Probability [04] Discrete Distributions [05] Continuous and Normal Distributions [06] Covariance and Correlation [07] Validating Statistical Assumptions [08] Sample Size and Sampling Distributions [09] Point Estimates and Standard Error [10] Interval Estimates and Confidence Intervals [11] Hypothesis Testing: 1 Sample [12] Hypothesis Testing: 2 Samples, Paired Test [13] Linear Regression Models and Assumptions [14] Regression Predictions, Confidence Intervals [15] Multiple Linear Regression [16] Analysis of Variance: Comparing 3 Means [17] Analysis of Covariance and Multiple ANOVA [18] Statistical Design of Experiments [19] Regression Trees and Classification Trees [20] Polynomial and Logistic Regression [21] Spatial Statistics [22] Time Series Analysis [23] Prior Information and Bayesian Inference [24] Statistics Your Way with Custom Functions