John is a new college graduate working at his first job. After years of living in an apartment he has decided to purchase a home. He has found a great neighborhood from which he can walk to work. Before buying a home in the area he has decided to collect some data on the homes in this neighborhood. A data set has been compiled that represents a sample of 100 homes in the neighborhood he is considering. The variables included in this data set include: Value: the current value of the home as determined by the county tax assessor.
Size: the size of the home in square feet.
Year: the year the homes were built.
Basement: does the home have a basement (y=yes, n=no).
Fireplace: does the home have a fireplace (y=yes, n=no).
Type: the structure a single family house or a townhouse. (house or townhouse).
This problem uses StatCrunch.
You will be working with these data.
Open the data in Statcrunch. Create histograms for each of the numeric variables and create bar charts for each of the categorical variables. When creating the histogram for the "value" variable use bin width of 20000. Use these variables to explore the data and determine which of the following best fits this situation:
A. The histogram for value is basically symmetric with one large outlier. This is probably because the neighborhood was built more recently around an older estate home that is very large and very expensive.
B. The histogram for value is basically symmetric with one large outlier. This is probably because there the majority of the homes in the neighborhood are townhouses with only one large single family home.
C. The histogram for value is basically symmetric with one large outlier. This is probably because it is the only home in the neighborhood that has a fireplace and that substantially increases its value.
D. The histogram for value is basically symmetric with one large outlier. This is probably because one home is very new while all of the others are about 50 years old. The histogram for value is clearly bimodal.
E. The reason it is bimodal appears to be because the homes in the neighborhood have higher priced single family houses and lower priced town homes. The histogram for value is clearly bimodal.
F. The reason it is bimodal appears to be because the neighborhood was built in two phases, the newer phase consists of larger more expensive homes and the older phase consists of smaller less expensive homes. The histogram for value is clearly bimodal.
G. The reason it is bimodal appears to be because the neighborhood was built in two phases, the older phase consists of larger more expensive homes and the newer phase consists of smaller less expensive homes. The histogram for value is clearly bimodal.
H. The reason it is bimodal appears to be because the neighborhood has some homes that have basements that tend to be larger in size with another group of homes that do not have basements and tend to be smaller.