`library( dataWorkshop)`

`## Loading required package: maps`

`## Loading required package: fields`

`## Loading required package: spam`

`## Loading required package: grid`

```
## Spam version 1.4-0 (2016-08-29) is loaded.
## Type 'help( Spam)' or 'demo( spam)' for a short introduction
## and overview of this package.
## Help for individual functions is also obtained by adding the
## suffix '.spam' to the function name, e.g. 'help( chol.spam)'.
```

```
##
## Attaching package: 'spam'
```

```
## The following objects are masked from 'package:base':
##
## backsolve, forwardsolve
```

```
# fine tuning HW Quiz submission. Use APPM2720 to begin subject line
# name on html/pdf/Rscript
# listing data sets.
# comments on for loops and not using loops from Quiz1
# e.g. converting temperatures=, converting dates.
# trick using reshaping as a matrix to get a column of years.
# Intro to least squares
# as an example work with the AudiA4 data
#
data( AudiA4)
Y<- AudiA4$price
X<- AudiA4$mileage
# finding the mean price the hard way!
# look at a sequence of points (a) from 2000 to 40000
# analysis find out where the minimum is
plot( X,Y)
```

```
# a linear relationship might more sense for mileage in the range [20K, 75K]
# Subset the data to work with this example
# brute force
# this is also incldued as a more substantial program and
# and an example of the image format
# vary slope b0 and intercept b1 over 20K to 40K and -.4 to 0 50 points each and
# store the sum of squares in the matrix S
# take a look at the surface
# add another contour close to the minimum
# the solution "by hand" using the LS formula -- see ISLR
# b1Hat
# b0Hat
# the solution using lm
# or fit$lsfit( X1,Y1)
#Q2 plot the data and add the least squares line.
```