Statistical data analysis foundations using R

Key learning outcomes

• Install and navigate R and RStudio, understanding their key functionalities.
• Install essential packages for statistical analyses
• Import and clean data from Excel or CSV files into R for analysis.
• Summarize categorical data using frequency tables and visualize it with bar charts.
• Calculate descriptive statistics (mean, median, standard deviation) for continuous data and create histograms.
• Perform basic statistical tests, such as t-tests, to compare means between groups.
• Interpret and report summary statistics effectively for decision-making.

Course Outline

Introduction and Setup

1. What is R and RStudio?
2. Installing R and RStudio
3. Introduction to the RStudio Interface
4. Installing and loading packages

2. A Primer on Statistics

1. What is Statistics?
2. Types of Data
3. Branches of Statistics

3. Getting Data into R

1. Importing Data from Excel or CSV Files
2. Basic Data Cleaning

4. Summarizing Categorical Variables

1. Frequency Tables
2. Bar Charts

5. Summarizing Continuous Variables

1. Measures of Central Tendency
2. Measures of Dispersion
3. Histograms
4. Summary Statistics

6. Comparing Means

1. Group-wise Comparisons with dplyr

Who should attend

• Absolute beginners who have no prior experience with R or statistics but want to get started with data analysis.
• Students in any discipline looking to enhance their data analysis skills for coursework or research projects.
• Professionals in fields like business, marketing, healthcare, or social sciences who need to understand and work with data but have little to no coding experience.
• Anyone curious about data science and looking for a hands-on introduction to statistical analysis using R..