Course Description

Topics Covered during the weeks

Lecture/Lab Date Topic Resources/ Data R codes
Lecture 1 24 Sep
  • Scatter Plots: Mechanics of drawing a scatter plot, summarising the scatter plot
  • Computing correlation coefficient
Lab 1 7 Oct
  • Galton’s Heights: Visualizing and Predicting Traits
Lecture 2 8 Oct
  • More about correlation
  • Changing SDs
  • Some exceptional cases
  • Ecological correlations
  • Association is not causation
Lecture 3 9 Oct
  • Regression
  • General regression model and special cases
  • Questions to ask
  • Fitting a line using least squares (visual)
Lab 2 14 Oct
  • Galton Data – From Correlation to Regression
Lecture 4 16 Oct
  • Finding the intercept and slope using least squares
  • Matrix notation
  • Multiple linear regression
Lab 3 21 Oct
  • Shot Put and Straight Lines
shotput.csv