Embark on a comprehensive 10-hour video series exploring statistics using the R programming language. Learn fundamental statistical concepts followed by practical implementation in R. Cover topics from introductory to intermediate statistics, including boxplots, histograms, probability distributions, hypothesis testing, ANOVA, and regression analysis. Follow along with step-by-step tutorials, downloadable datasets, and R scripts for hands-on practice. Gain a solid foundation in statistical theory and its application using R, suitable for students, researchers, and data enthusiasts looking to enhance their analytical skills.
Overview
Syllabus
Boxplots in Statistics | Statistics Tutorial | MarinStatsLectures.
Boxplots and Grouped Boxplots in R | R Tutorial 2.2 | MarinStatsLectures.
Box Plots with Two Factors (Stratified Boxplots) in R | R Tutorial 2.3 | MarinStatsLectures.
Histograms and Density Plots for Numeric Variables | Statistics Tutorial | MarinStatsLectures.
Histograms in R | R Tutorial 2.4 | MarinStatsLectures.
Bar Chart, Pie Chart, Frequency Tables | Statistics Tutorial | MarinStatsLectures.
Bar Charts and Pie Charts in R | R Tutorial 2.1 | MarinStatsLectures.
Mean, Median and Mode in Statistics | Statistics Tutorial | MarinStatsLectures.
Standard Deviation & Degrees of Freedom Explained | Statistics Tutorial | MarinStatsLectures.
Calculating Mean, Standard Deviation, Frequencies and More in R | R Tutorial 2.8| MarinStatsLectures.
Sample and Population in Statistics | Statistics Tutorial | MarinStatsLectures.
Binomial Distribution in R | R Tutorial 3.1| MarinStatsLectures.
Normal Distribution, Z-Scores & Empirical Rule | Statistics Tutorial #3 | MarinStatsLectures.
Normal Distribution, Z Scores, and Normal Probabilities in R | R Tutorial 3.3| MarinStatslectures.
Samples from a Normal Distribution | Statistics Tutorial #4 | MarinStatsLectures.
Central Limit Theorem & Sampling Distribution Concepts | Statistics Tutorial | MarinStatsLectures.
Standard Error of the Mean: Concept and Formula | Statistics Tutorial #6 | MarinStatsLectures.
Confidence Interval Concept Explained | Statistics Tutorial #7 | MarinStatsLectures.
Hypothesis Testing Explained | Statistics Tutorial | MarinStatsLectures.
t-distribution in Statistics and Probability | Statistics Tutorial #9 | MarinStatsLectures.
t Distribution and t Scores in R | R Tutorial 3.4 | MarinStatsLectures.
Confidence Interval for Mean with Example | Statistics Tutorial #10 | MarinStatsLectures.
Margin of Error & Sample Size for Confidence Interval | Statistics Tutorial #11| MarinStatsLectures.
Bootstrapping and Resampling in Statistics with Example| Statistics Tutorial #12 |MarinStatsLectures.
Hypothesis Testing: Calculations and Interpretations| Statistics Tutorial #13 | MarinStatsLectures.
Hypothesis Testing: One Sided vs Two Sided Alternative | Statistics Tutorial #14 |MarinStatsLectures.
One-Sample t Test & Confidence Interval in R with Example | R Tutorial 4.1| MarinStatsLectures.
Hypothesis Test vs. Confidence Interval | Statistics Tutorial #15 | MarinStatsLectures.
Errors and Power in Hypothesis Testing | Statistics Tutorial #16 | MarinStatsLectures.
Power Calculations in Hypothesis Testing | Statistics Tutorial #17 | MarinStatsLectures.
Statistical Inference Definition with Example | Statistics Tutorial #18 | MarinStatsLectures.
Bivariate Analysis Meaning | Statistics Tutorial #19 | MarinStatsLectures.
Bivariate Analysis for Categorical & Numerical | Statistics Tutorial #20 | MarinStatsLectures.
Paired t Test | Statistics Tutorial #21| MarinStatsLectures.
Wilcoxon Signed Rank Test | Statistics Tutorial #22 | MarinStatsLectures.
Paired t-Test in R with Examples | R Tutorial 4.7 | MarinStatsLectures.
Wilcoxon Signed Rank Test in R with Example | R Tutorial 4.8 | MarinStatsLectures.
Two Sample t-test for Independent Groups | Statistics Tutorial #23| MarinStatsLectures.
Two Sample t-Test:Equal vs Unequal Variance Assumption| Statistics Tutorial #24| MarinStatsLectures.
Two-Sample t Test in R (Independent Groups) with Example | R Tutorial 4.2 | MarinStatsLectures.
Mann Whitney U / Wilcoxon Rank-Sum Test in R | R Tutorial 4.3 | MarinStatsLectures.
Bootstrap Hypothesis Testing in Statistics with Example |Statistics Tutorial #35 |MarinStatsLectures.
Bootstrap Hypothesis Testing in R with Example | R Video Tutorial 4.4 | MarinStatsLecutres.
Bootstrap Confidence Interval with Examples | Statistics Tutorial #36 | MarinStatsLectures.
Bootstrap Confidence Interval with R | R Video Tutorial 4.5 | MarinStatsLectures.
Permutation Hypothesis Testing with Example | Statistics Tutorial # 37 | MarinStatsLectures.
Permutation Hypothesis Test in R with Examples | R Tutorial 4.6 | MarinStatsLectures.
One Way ANOVA (Analysis of Variance): Introduction | Statistics Tutorial #25 | MarinStatsLectures.
ANOVA (Analysis of Variance) and Sum of Squares | Statistics Tutorial #26 | MarinStatsLectures.
ANOVA Part III: F Statistic and P Value | Statistics Tutorial #27 | MarinStatsLectures.
ANOVA Part IV: Bonferroni Correction | Statistics Tutorial #28 | MarinStatsLectures.
ANOVA, ANOVA Multiple Comparisons & Kruskal Wallis in R | R Tutorial 4.9 | MarinStatsLectures|.
Chi Square Test of Independence | Statistics Tutorial #29| MarinStatsLectures.
Chi-Square Test, Fisher’s Exact Test, & Cross Tabulations in R | R Tutorial 4.10| MarinStatsLectures.
Odds Ratio, Relative Risk, Risk Difference | Statistics Tutorial #30| MarinStatsLectures.
Odds Ratio, Relative Risk & Risk Difference with R | R Tutorial 4.11| MarinStatsLectures.
Case-Control Study and Odds Ratio | Statistics Tutorial #31| MarinStatsLectures.
Simple Linear Regression Concept | Statistics Tutorial #32 | MarinStatsLectures.
Polynomial Regression in R | R Tutorial 5.12 | MarinStatsLectures.
Correlations and Covariance in R with Example | R Tutorial 4.12 | MarinStatsLectures.
Simple Linear Regression in R | R Tutorial 5.1 | MarinStatsLectures.
Linearity and Nonlinearity in Linear Regression | Statistics Tutorial #33 | MarinStatsLectures.
Taught by
MarinStatsLectures-R Programming & Statistics
