In paulemms/datamining: Data mining

Introduction

This is Lab 14 on Data Mining. It is a lab exam.

First we load the datamining package and the data for the lab.

devtools::load_all()
load('Credit.rda')

The data set

source("lab14.r"') This defines a data frame x which contains the population of the United States (in millions) as recorded by the census every ten years from 1790-1970. 1. Plot the population versus time, with trend curve overlaid. What anomalous years do you see! 2. (a) Define a matrix x1 which contains only the data up to and including 1860. (b) Transform the series appropriately so that the pre-1860 population can be predicted by a linear function of time. Fit a linear model and give a plot or two to argue that the model fits well. State the model as a formula for (untransformed) uspop. (c) Plot the residuals for your pre-1860 model. Which two years pre-1860 are most unlike the others (have the largest residuals)? 3. (a) Define a matrix x2 which contains only the data after 1860. (b) Transform the series appropriately so that the post-1860 population can be predicted by a linear function of time. Fit a linear model and give a plot or two to argue that the model fits well. State the model as a formula for (untransformed) uspop. (c) Plot the residuals for your post-1860 model. Two years are outliers. Which are they? (d) Remove the outlier years. You can remove a year as follows: x2 = x2[(x2[,"time"] != year),] Rent the model and plot residuals. One year should be unusually high. Which one? (ec) What does your refitted model predict for the population in year 2000?

paulemms/datamining documentation built on March 1, 2023, 4:01 p.m.