Points to note
Assessment The assignment will contribute 20% to the final mark for the course. For each task,
marks will be given for correctly using Excel to carry out the task and for your interpretation and comments
about the results. For each task and each question, a specific Excel worksheet should be created in order
to reorganise the information needed to carry out the task.
General style The report should contain only one pdf file, which will contain your main report (giving
the results, and commenting them), and an appendix (explaining how to carry out the tasks with Excel
commands, and containing the Excel worksheets saved in pdf format).
The pdf file should be created from a word processing package such as Microsoft Word. There should
be a header page that includes your name and matriculation number.
Content The main part of your assignment should give the results for each task that you carry out and
your comments on and conclusions from these results. Excel graphical output must be included in the
main report.
Appendix The main report should not contain Excel commands, but there must be an Appendix which
specifies briefly how the results for each section were obtained using Excel. The specification can include
menu commands and/or screen shots.
The full Excel worksheets should be included in the Appendix in a pdf format.
Length Your assignment should be NOT more than five sides of A4 including graphs and tables,
but not including the title page or the Appendix.
Submission The assignment should be submitted through Vision. It should not be submitted by email
or handed in as a paper copy.
Collaboration Students are encouraged to discuss the methods used with other students, but your submitted assignment must be all your own work. In particular, copying a section of your assignment, either
plots or commentary, from another student is a serious disciplinary offence. It is also an offence to allow
another student to copy your work, so your assignment files should not be made available to other students.
Deadline The deadline for submission is 5pm on Friday 9
th April; assignments may be submitted
Late submissions Any assignment that is submitted after the submission deadline but within 5 working
days of the deadline will be penalised by a 30%. reduction in the mark. Assignments that are submitted
more than 5 working days past the deadline will not be marked.
Background to the assignment
In this assignment you will be investigating pulse rate data collected by a sports science researcher who
was interested in the effects of various factors on pulse rates at rest and after a short burst of exercise.
The data was collected from 91 undergraduate volunteers as follows: The researcher began by recording
the height, weight, gender, smoking habits (i.e. smoker or non-smoker), daily activity level, and resting
pulse rate of the volunteers. The researcher then divided the volunteers at random into two groups. The
first group ran in place for a minute while the other group stood still. Then, the volunteers in each group
recorded their pulse rates once more.
The data is contained in the Excel worksheet “pulse rate data” from the file pulserates.xlxs, and contains
8 columns:
Column Name Description
A Pulse1 Resting Pulse
B Pulse2 Pulse after running or not running
C Ran Whether student ran or not (‘Yes’ or ‘No’)
D Smokes Whether student smokes (‘Yes’ or ‘No’)
E Gender Gender of student: M or F
F Height Student’s height in inches
G Weight Student’s weight in pounds
H Activity Daily activity level (Slight, Moderate, or A Lot)
The Excel file pulserates.xlxs can be found on the Vision page in the Assignment folder under Assessment.
The Excel file pulserates.xlxs also contains a worksheet per task and question of the assignment. These
worksheets must be used to answer the questions, and will be part of your report (see Section Points
to note – General style).
Assignment Tasks
Task 1 – Investigation of resting pulse

  1. To investigate differences between resting pulse rate for smokers and non-smokers, calculate
    summary statistics for resting pulse for smokers and non-smokers and produce boxplots for resting
    pulse for smokers and non-smokers.
    Comment on these statistics and plots.
    (2 marks)
  2. Investigate differences between resting pulse rate for men and women by calculating summary
    statistics for resting pulse for each group and producing boxplots for resting pulse for each group.
    Comment on these statistics and plots.
    (2 marks)
  3. Investigate whether there is a statistically significant difference between the mean resting pulse
    for men and women by carrying out an appropriate 2-sided t-test on the difference in the mean
    pulse rates for the two groups (set the confidence level at 95%).
    Clearly state your hypotheses and the assumptions needed for the test, and interpret the result.
    (3 marks)
    Task 2 – Investigation of runners/non-runners
  4. Create a new column called Differences containing the difference between pulse after running/not
    running and resting pulse. These values should be reported in the appendix.
    Split the column Differences in two new columns, whether the student ran or didn’t run. Produce
    dotplots of the differences for the runners and the non-runners.
    Comment on the dotplots.
    (3 marks)
  5. For the group that ran, carry out an appropriate 1-sided t-test for the mean difference between the
    first pulse measurement and the second pulse measurement (set the confidence level at 95%).
    Clearly state your hypotheses and the assumptions of the test, and interpret the result.
    (3 marks)
    Task 3 – Relationship between height and weight
    The two following sub-tasks can be performed in the same Excel worksheet (Task 3 – Q1&2)
  6. Using the regression tool, plot weight against height and comment on the plot. Use the method
    of least squares regression to obtain an equation for weight in terms of height (i.e. find α and β
    such that Weight=α+βHeight.
    (3 marks)
  7. Use the residuals from the regression to comment on whether the assumptions of the regression
    model are justified. Support your commentary with appropriate plots.