---
title: "Cars.com (part 1)"
author: "XX ADD NAMES HERE"
date: ''
output:
  pdf_document:
    fig_height: 3
    fig_width: 5
  html_document:
    fig_height: 3
    fig_width: 5
  word_document:
    fig_height: 3
    fig_width: 5
---


```{r include=FALSE}
# Don't delete this chunk if you are using the mosaic package
# This loads the mosaic and dplyr packages
require(mosaic)
```

```{r include=FALSE}
# Some customization.  You can alter or delete as desired (if you know what you are doing).

# This changes the default colors in lattice plots.
trellis.par.set(theme=theme.mosaic())  

# knitr settings to control how R chunks work.
require(knitr)
opts_chunk$set(
  tidy=FALSE,     # display code as typed
  size="small"    # slightly smaller font for code
)
```

### PART 1: A SUMMARY OF WHAT WE FOUND: 

SOLUTION:

```{r}
# be sure to upload cars.csv to RStudio in the same folder as this file
ds <- read.csv("http://nhorton.people.amherst.edu/workshop/carscollated2017.csv")
names(ds)
```

```{r}
# summary statistics (please delete those that you are not using)
tally(~ car, data=ds)
tally(~ model, data=ds)
tally(~ year, data=ds)
tally(~ location, data=ds)
favstats(~ price, data=ds)
favstats(~ mileage, data=ds)
```

### PART 2: AN INTERESTING PLOT (WITH INTERPRETATION)
```{r}
# here are some of my ideas: please explore and elaborate using some different plots
# hint: use the | or group= operator
bwplot(price ~ as.factor(year), data=ds)
bwplot(mileage ~ as.factor(year), data=ds)
xyplot(price ~ mileage, type=c("p", "r", "smooth"), data=ds)
xyplot(price ~ year, type=c("p", "r"), data=ds)
```

SOLUTION:

```{r}
# your new plot goes here

```


### PART 3: RESULTS FROM YOUR MULTIPLE REGRESSION MODEL

along with interpretation of the coefficients

```{r}
# here's my example (with just one predictor)
lm1 <- lm(price ~ year, data=ds)
coef(lm1)
# your model should have at least two predictors
```

SOLUTION: