You have been given data on height and weight of NBA basketball players: NBA_Wei

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You have been given data on
height and weight of NBA basketball players: NBA_Weight_Data_Student.xlsx
Save the file as “Last_First_ExcelStatistics.xlsx”.
Create a new tab called “working data” and place the Master tab
information here. This should prevent
you from deleting or altering the core master data tab.
Your job is to complete an analysis similar to the ones
seen in lecture by answering the below 10 questions. The data is not in
analyzable format yet as you need to create dummy variables in order to
complete a regression using categorical variables..
You will export your results of the various tests/analyses
to a word document and submit the word document for grading. You will do this
by copying and pasting the statistical result output and pasting it as an image
into a word document. Please make sure you paste the image such that all of the
results are visible. You may need to resize the image or copy a portion of the
excel workbook for this to work properly. You will also need to have your excel
sheet available if the instructor requests it. Please place each numbered item
in its own worksheet.
As part of your deliverable you must submit answers to the
following:
1. Are there duplicates in this dataset? Why or why not?
Discuss the data you are given.
2. Run descriptive statistics for height and weight for the
entire data set.
3. Create a histogram for each, height and weight, to check
for normality. (Remove the legend and give your histogram a title for the
variable it is charting) Are the heights and weights normally distributed? What
could we do to this data to try and make it more normal if it isn’t already?
4. Apply a z-score correctly and find the x value needed to
be in the 90th percentile of the distribution for height. Type out your answer
in Word’s equation editor with the equation you used and describe what a
z-score is telling us generally in statistics and specifically as it applies to
this data.
5. Using a z-score correctly, In what percentile is a
player who is 75.086 inches tall. Type
out this equation in equation editor as well.
6. Run a regression to predict weight by height. Describe
in detail what the regression report tells us. There should be a discussion of
r^2, the coefficients and the significance of each predictor.
7. Run a regression to predict weight by height and
position. Describe in detail what the regression report tells us. There should
be a discussion of r^2, the coefficients and the significance of each
predictor. Is this a better model that 6)? What could be done to improve this
model further?
8. Run an ANOVA to see if there are differences between
weights of players at different positions. Report your findings and describe
ways to proceed in further analysis.
9. Conduct a T test to see if there is a difference in
height between G-F and F-C.
10. Finally, do players, grouping in five-year buckets for
their draft year, appear to weigh more and are they taller using a box and
whisker plot? What if anything does this say about athletes over time?

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