Price: The price the house sold for
Square Feet: The size of the house in square feet
Beds: The number of bedrooms in the house
Baths: The number of bathrooms in the house
Year Built: The year in which the house was built
Age: The age of the house in years
Pool: Does the house have a pool (yes/no)
Fireplace: Does the house have a fireplace (yes/no)
Waterfront: Is the house on the waterfront (yes/no)
Days on Market: How many days the house spent on the market before it was
ultimately sold
Occupancy: Is the house occupied by the owner, a tenant, or is it vacant
Style: What is the architectural style of the house?



Problem 1.1

Use the house price data to do the following:

(a) Which of the variables are categorical and which are numerical?
(b) Which of the categorical variables are nominal and which are ordinal?
(c) Which of the numerical variables are ratio and which are interval?

Problem 1.2

Use the house price data to do the following:

(a) Create a summary table and an ordered summary table of the architectural
styles of the homes sold.
(b) Construct a bar chart, a pie chart, and a Pareto diagram.
(c) Which graphical method do you think is best to portray these data?
(d) Based on this data, what conclusions can you make about architectural styles
in Baton Rouge?

Problem 1.3

Use the house price data to do the following:

(a) Construct a frequency distribution and a percentage distribution of the
number of bedrooms in the sold houses.
(b) Construct a histogram and a percentage polygon.
(c) Plot a cumulative percentage polygon.

Problem 1.4

Use the price data to do the following:

(a) Compute the mean, median, first quartile, and third quartile for the price
variable.

(b) Compute the variance, standard deviation, range, interquartile range,
coefficient of variation, skewness, and Z scores for the price variable.
(c) Are the data skewed? If so, how?
(d) Based on the results of (a) through (c), what conclusions can you reach
concerning price?
(e) Calculate the proportion of house prices that are +/- 1, +/- 2, and +/- 3
standard deviations of the mean.
(f) Compare and contrast your findings with what would be expected on the basis
of the empirical rule.

Problem 1.5

Use the house price data to do the following:

(a) Compute the covariance between house price and house size.
(b) Compute the coefficient of correlation between house price and house size.
(c) Construct a scatterplot between house price and house size with house price
on the Y-Axis.
(d) Which of (a)-(c) do you think is the most valuable means to understand the
relationship between house price and house size?
(e) What conclusions can you reach about the relationship between house price
and house size?

(d) Which of (a)-(c) do you think is the most valuable means to understand the relationship between house price and house size?

We can note from the scatter plot that as the size of house increases the price of house increases.

(e) What conclusions can you reach about the relationship between house price and house size?

There is a strong positive relationship between house size and house price.

Price: $19.48

Solution: The downloadable solution consists of 10 pages, 948 words and 7 charts.
Deliverable: Word Document