STATISTICS 3N03/3J04
This test is to be written in the BSB Student Technology Centre. The duration of the test is 2 hours.
Any calculators and one sheet of notes (8.5" x 11", one side only) are permitted.
You may consult any of the web pages for this course, but you may not look at any other web pages, use e-mail or communicate with anyone else.
Use R to do your analyses and draw graphs. Your response to each question should be in the form of a report. Prepare the report in a word processor, integrating graphics and discussion. Include your R code as an appendix at the end of each question. Print out and submit your report at the end of the test period.
Only printed reports will be accepted. Electronic submissions will not be accepted.
Do an exploratory graphical analysis of the Whiteside dataset, found in the MASS library in R. Mr Derek Whiteside of the UK Building Research Station recorded the weekly gas consumption and average external temperature at his own house in south-east England for two heating seasons, one of 26 weeks before, and one of 30 weeks after cavity-wall insulation was installed. The object of the exercise was to assess the effect of the insulation on gas consumption.
Attach the library with library(MASS) and you will be able to use the whiteside data frame. Plot a graph to compare the temperature-gas consumption relationship before and after insulating. It might be interesting to analyse these data as time series; why can't we do that?
Question 2
A study was done to determine the effects of type of water (tap or de-ionized) and glycerol (present or absent) on the latherability of soap. The outcome measured was the amount of foam produced (in mL). The experiment was repeated three times for each combination of the factors. Analyse the data graphically.
| water type | |||
| de-ionized | tap | ||
| glycerol | absent | 168, 178, 168 | 152, 142, 142 |
| present | 160, 197, 200 | 139, 160, 160 |
The file series.txt includes three artificially generated time series. Plot the series with and without smoothing. Using graphical methods, determine for each series if it is independent observations, autocorrelated with lag 1, or autocorrelated with lag > 1. Was smoothing useful in this example?