```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# Instructions:

1. Update your name in the header block, example: `author: "Alex Fout" `
1. Select `File > Save as` and save the file by adding your last name at the beginning with an underscore, example: `fout_assignment_4.rmd`
1. Follow the instructions below to fill in the assignment.
1. Be sure to _run your code chunks when you make them_, to make sure everything works!
1. When you've completed the assignment, __knit__ the document and make sure the resulting HTML or PDF file looks alright.
1. Upload the PDF or HTML file to Canvas (Don't upload the Rmd document).


# Assignment

This assignment will explore real estate prices using another [data set from Kaggle](https://www.kaggle.com/c/house-prices-advanced-regression-techniques/).
You should download the data from [here](https://github.com/CSU-R/Module1/raw/master/data_raw/housing.csv) and place it in your data_raw folder.

## Problem 1. 

Read the dataset into R to an object called `housing` and print the shape of the data frame

```{r}
```

## Problem 2

Below is some incomplete code that you must finish.
The purpose of the code is to loop through each column in the data frame and determine how many columns have type "numeric".
Replace both sets of `...` below to accomplish the task
Don't change any other code.

```{r}
is_quant <- 0  # counter
for(...){
  col <- housing[,i]
  if(...){
    # increase counter by 1
    is_quant <- is_quant + 1
  }
}
```


## Problem 3

Below is a list of some of the quantitative variables.
Write a for loop which iterates through the list and prints the range (maximum minus minimum). 
Remember, you may have to use `na.rm=T` if you encounter `NA` values.

```{r}
qvs <- list(housing$LotFrontage, housing$LotArea, housing$SalePrice, housing$Fireplaces)
```


## Problem 4

Write code that computes the average sale price for houses, split by number of Fireplaces


## Problem 5

How many houses have a garage built after 1995?

## Problem 6

Find two quantitative variables in the data set, and create a plot between them. 
Make an observation about the relationship between the two variables.
If no relationship is clear, try two other quantitative variables.

## Problem 7

What was the most valuable thing you got from this course?


## Problem 8

What was the least valuable part of the course? 


## Problem 9

What is one thing that could be improved about the course?

## Problem 10

Anything else you'd like to share?


## End

This is the end of the assignment!
You can knit the document and upload it to Canvas


