Transcribed Text
Analyzing NBA Salaries Team Performance
You are tasked with analyzing NBA Player Salary data for the 2017- season as well as NBA team
performance 2016-1 season the QMB210N2- file The file consists of the two
worksheets describedbelow
.
PlayerSalories17-18
Provides contract data for 555 unique players for the 2017- 18 season obtained from
There
565
player
contract
rows
because ten players are with two teams each. The sheet alsocontains lookup table for
for
the
2016-17
based
on
data
obtained
from
2017.html
Miscellaneous
Part Data Preparation
In the PlayerSalaries1] sheet
1) Delete following columns: 2018- 19, 2019-20, 2020-21, 2021-22, 2012-23, Signed Using and
Guaranteed
2)
Insert blank column the right of the ContractTm column and label i ContractTn Name
Populate column with the full name of the team using the lookup table found in the sheet
and the /LOOKUP function Do quick check seel the column popul ated properly by turning
filters and browsir through the columi see ifall the teamnames are there.
3) Create a new column next the 2017 -18Salory column nd label i z-score. Calculate the -score
reach salary using Excel's STANDARDIZE function Make thecelli formatter correctly i.e.,
the numbers are displayed with2 decimals and
In the TeamStats16 17sheet
4) Playoff teams indicated asterisk (*)inthe Insert blank column
right of the Team column and label it Ployoff Team Eachteam with asterisk shoul receive the
value "Yes' inthe newly created Playoff Team column Provide the value "No" for the teams
that did not make playoffs
5) Insert blank column the right fthe Losses column and label Win% Use formula
to
compute the in percentage (as decimal, e.g., .63)for eachteam
Part 2 Data Analysis
Using the PlayerSalaries1 'worksheet
6) Compute the descriptive s statistics for the 2017 -18 Salary variable which should displayed a
worksheet
labeled
-SalaryDesc
riptives.
7) Create filter the z-score column and list only those players whose salaries are outliers Le
whose salary z-score exceeds 3. Copy these playen along with their data into new worksheet
labeled P-SalaryOutliers
8) Remove the filter from 7)so allthe player salaries shown i.e. 565 rows player contract data).
a) Create pivot table new sheet show average salary per team using the full team
name. The average salaries should shown with the sign, and without decimal places.
Label
this
newworksheet
-AvgSalaryByTear
b) Copy the Average 2016 Salary column from the TeamStats16- -17 sheet into the 3-
yTeam sheet from 8)a). Make sur teams match properly Create chart
from Chapter your text book effectively compare average team salaries for the 2016-
17 and 2017- seasons
9)
Construct 95% confidence interval estimate for the population characteristics for the variable
2017 Salary. The confidence interval results will appear on new worksheet which should be
renamed to I-ConfidencelntSalary.
10) Provide one-tail (upper)hypothesis test determine lithe average salary of the Golden State
Warriors
players
greater
Hop
Use
0.05
level
ofsignificance
The
will
worksheet
which
should
be named
Using the TeamStats16 sheet
11) Compute the descriptive statistics (mean, median, mode, variance, standard deviation and
kurtosis, range, max, count) the following variables: Average 2016-
17Sclary, ORtg, DRtg PTS, TotalPointsfrom2P, antsfrom3P, and TotalPaintsfromFT The
result should appear on a new worksheet that voulabel 6-TeamDescriptives
a) Organize the results the worksheet such that the name the statistics (mean median,
mode, appears column and the values of the statistic for each variable appear in
columns B
b)
values of all statistics must be in standard numeric format with two decimal places
displayed.
c)
Ensurethat the columns are wide enough to display all digits for your statistica values.
12) Create pivot table that shows average Age, Average 2016 17Salory, ORta. DRtq, PTS,
TotalPoi ntsfromFT teams
plavoffs versus those that did not. The results should appear on : new worksheet labeled 7
PlayOffTeams.
13) Create pivot table compare. Averoge 2016- 17Salan Plavoff Team and Conference riables.
Salary averages should shown with the sign, and without decimal places. Pick chart from
Chapter your text book effectively visualize the pivot table data Make sure your chart
shows data labels. Be sure follow the guidance for developing good graphs and tables with
propertitles and labels discussed ir class Your table and chart will appear onnew worksheets
that
should
labeled
SalaryComparisons
14) Analyze the normality Age, Averoge 2016 17Salary, and This can be done
by analyzing its box plot or evaluating the proximity ariables mean versus median
you create plots, plots appear ksheets rename the worksheets
to9-
AgeNormality, 9-Avg16 -17SalNormality, 9-PtsFrom3PNormality.
15) Copy TotalF intsfrom3Pand Win%into anew sheet. Computi correlation betwe thes two
variables create graph to show the relationship between these variables
Rename
sheet
Correl3P-
Win%.
16) Conduct simple linear regression determine Fthe Average 2016 -17 Solary i significant
predictor of the Win% Provide the regression line. The regression equation
scatterolo will appear on new worksheets Rename these worksheets -Regression and 11-
Scatterplot
17) Reorder spreadsheet such that they appear the following order
(from lef right):
TeamStats16
SalaryOutilers
AvgSalaryByTeam
4-ConfidenceIntSalo
5-HypothesisSalary
ayOffTeams
8-Salaro
9-Avg16
9-PtsFrom3PNormality
Correl3P- Win%
page
numbers
and
use
11-point
header
the
document,
and save
Project
F17.dock
of
your
analysis,
and
the
types
of
found
Chapter
in your
15)into
your
report
making
sure to
include summarizes what being illustrated Briefly
interpret
each
table/graph
findings
Interpret results fov from 6), 9), 10), 11) 14). and 16). Interprel the coefficients
and the meaning of R-squared nalysis from Task 16). the Average 2016- Salary a
statistically significant predictor ofthe Win%?
These solutions may offer step-by-step problem-solving explanations or good writing examples that include modern styles of formatting and construction
of bibliographies out of text citations and references. Students may use these solutions for personal skill-building and practice.
Unethical use is strictly forbidden.
Introduction
This report analyses the NBA salaries and the team performance of the NBA players using the data for the season 2016-17 and 2017-18. Various variables analyzed includes the age of the players, the total number of games won and games lost, the average salary of the players, offensive rating and defensive rating. The variable age is numerical, whereas the team name is categorical, the number of games won and lost is numerical whereas the salary is measured in dollars. The average salaries of the players are analyzed across the various teams with the win percentage compared. the correlation between the Total points from 3p and win percentage suggest that there is no direct correlation between these variables and the regression between the average 2016-17 salary and the win percentage indicates the fact that salary is one of the factors that affects the win percentage among the team players....