Explore statistical analysis within R to perform descriptive and inferential statistics, understand probability distributions, and conduct hypothesis testing.
Overview
Syllabus
- Lesson 1: Descriptive Statistics with R: Understanding Measures of Central Tendency
- Central Tendency Analysis in R
- Exploring Central Tendency: Adjusting the Age Dataset
- Astronomical Camp Ages: Computing Mean, Median, and Mode in R
- Lesson 2: Descriptive Statistics in R: Diving Into Measures of Dispersion
- Measuring Dispersion in Math Scores
- Analyzing Measures of Dispersion for English Marks
- Debugging Measures of Dispersion in R
- Exploring Dispersion in Educational Data
- Analyzing Student Mathematics Scores Using Measures of Dispersion in R
- Lesson 3: Quantiles and Interquartile Range Analysis with R
- Understanding Student Grade Distribution with IQR
- Calculating Lower Outlier Bound in R Using IQR Method
- Debugging Interquartile Range Calculation in R
- Calculating the Interquartile Range of Student Math Scores
- Calculating the Median and Interquartile Range in R
- Lesson 4: Understanding Skewness and Kurtosis in R
- Assessing Weather Trends with Skewness and Kurtosis in R
- Fine-Tuning Temperature Data Simulation in R
- Calculating Skewness and Kurtosis in R
- Analyzing Hypothetical City Temperature Data with R
- Lesson 5: Exploring Probability Distributions with R: Uniform and Normal Distributions
- Visualizing Binomial Distribution of Card Game Wins
- Drawing and Visualizing 14 Cards with Uniform Distribution
- Exploring Uniform Distribution in R
- Simulating Standardized Test Score Distributions in R
