Halifax, Nova Scotia retrieved from the CREA website in December 2010. (The listings
are in close proximity to St. Mary’s University and Dalhousie University.) The variables
are: list price, type of dwelling (apartment, townhouse or house), number of bedrooms,
number of full baths, number of half baths, and total number of square feet.
I have prepared two versions of the spreadsheet to save you the time required to reformat
and sort the data so that you can work on the statistical issues.
= one combined set of data for all 98 listings, sorted from
highest to lowest list price
= separate data for each of the three types of dwellings. Variables
are list price, bedrooms and total area; variables called full baths and half baths
For parts a), b) and c), use
a) Create a histogram for the list price
of the combined set all 98 listings.
b) For the list price
, compute the mean, standard deviation, median, minimum and
maximum of the combined set. What do you notice about the relative values of the mean
and median? What is the reason for this difference?
c) For the list price
, compute the lower and upper quartiles of the combined set. Identify
any outliers (i.e. points above the upper inner fence or below the lower inner fence).
For parts d), e), f), and g) use
d) For list price
, compute the mean, standard deviation, median, minimum and maximum
for each type of dwelling. Report the data in table format, with three rows corresponding
to the dwellings and five columns corresponding to the numerical summaries.
e) Repeat part d), for total area
f) Create side-by-side box plots of list price
only for the three types of dwellings. You
may use an Excel macro or a hand-drawn plot if it is neatly drawn!
g) Create a table of Type of Dwelling as the row variable by Number of Bedrooms as the
column variable, with the frequencies (i.e. counts) as the cell entries. Convert this table to
a table of percentages; it is up to you to decide which is the more relevant – row or
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