Computer analysing and validating dataComputer analysing and validating data

R Module

R Module is an all-in-one resource that does not expect you have had any previous experience with R or programming/coding – we will show and teach you all you need to know. From the contents below, you can see how R Module shows you from how to install R and R Studio, all the way to advanced statistical analysis and graphing techniques. We will also be reviewing and adding content, both in R Module and also in the Blog section of this website, so make sure that you keep an eye out for those.

Abstract figure for decorative purpose

Outline

Section 1: Getting Functional in R

  1. Installing and setting up R and R Studio.
  2. Getting to know R and R Studio.
  3. How to start a project and save your work in R.
  4. Features in R.
  5. Data structures and entering data into R.
  6. Exporting output from R.

Section 2A: Basic Statistical Analysis

  1. Outlier detection.
  2. Calculating descriptive statistics.
  3. Calculating confidence intervals.

Section 2B: Basic Graphing - Data visualisation

  1. One-dimensional plots.
  2. Side-by-side plots.
  3. Scatter plots.

Section 2C: Significance Tests

  1. T-tests.
  2. F-test.
  3. ANOVA (Analysis of variance).

Section 2D: Regression Analysis

  1. Unweighted linear regression.
  2. Weighted linear regression.
  3. Linear model graphics.
  4. Non-linear regression.

Section 3A: Using R for Unsupervised Learning

  1. Data manipulation and large data set management.
  2. Hierarchical clusted analysis (HCA).
  3. Principal component cluster analysis (PCA).

Section 3B: Using R for Supervised Learning

  1. Creating training and test sets.
  2. Random forest models.
  3. kNN (k Nearest Neighbours) analysis.
  4. Discriminant analysis.

Section 4: Advanced Graphing - Visual Representation

  1. ggplot2 package - One-dimensional plots revisited.
  2. ggplot2 package - Side-by-side revisited.
  3. ggplot2 package - Regression revisited.
  4. factoextra package - PCA plots revisited.

Section 5A: Bringing it all Together

  1. Statistics workflows.
  2. Worked examples.

Section 5B: Moving Forward

  1. Debugging your code, interpreting errors.
  2. Online community - R help forums.
  3. Available data repositories - recommended data sets.