Linear Transformations (in a Descriptive Statistics Setting)

I discuss linear transformations, in the context of descriptive statistics. I discuss what a linear transformation is, give an example, discuss the effect of the linear transformation on various summary statistics, and work through a numerical example. The temperature data is from here: https://climate.weather.gc.ca/climate_data/daily_data_e.html?StationID=51459&timeframe=2&StartYear=1840&EndYear=2021&Day=22&Year=2020&Month=7# (The original data was given in Celsius, but I converted it to Fahrenheit for use in this video.) 0:00 Introduction and example 1:36 Illustration of the effect of the additive constant on measures of central tendency and variability. 3:58 Illustration of the effect of the multiplicative constant on measures of central tendency and variability. 6:52 Formulas for the new mean, standard deviation, and variance after the linear transformation. 7:50 A numerical example of the effect of a linear transformation on the mean, median, standard deviation, and variance (converting temperatures from Fahrenheit to Celsius). R code to calculate the mean and standard deviation for the examples: mean(c(3,4,5)) [1] 4 sd(c(3,4,5)) [1] 1