Project 1:
Descriptive Statistics in MINITAB
Directions: The goal of this project is simply to familiarize you with the MINITAB software and
learn how to do some basic descriptive statistics - producing several graphs, descriptive
statistics, etc. The instructions have been left sparse intentionally because figuring out how to
do things yourself is a better way to retain information. If you can't find out how to do
something, by all means come see me or ask a tutor (not all the tutors will necessarily know all
about MINITAB, but they should be able to help). At times I may ask for a response in addition
to the output, I'm not expecting anything extravagant here, just some very basic interpretation
/ analysis, no fluff or BSing. I want competent use of English - complete sentences, be specific
when you refer to output, but if a single sentence is all you need to answer sufficiently, that's
fine. As a rule, any output I ask you to create should be included in your project.
Import that Data: Download the project 1 dataset and load the Excel file into MINITAB (Use
Open Worksheet from the File menu, you'll need to change the "Type of File" to be able to see
Excel worksheets). The dataset should appear in the MINITAB spreadsheet with the variable
names bolded at the top of the columns.
(1.) Make a pie graph for the variable Seat, make the title read "Pie Chart for Seat", and have
MINITAB label and give percents for the slices. I'm not fully satisfied with the default pie graph
because the missing observations are included as a slice, and the group names are just
abbreviations. Create a new variable, say Seat2, that has the full words for the seat location
instead of just the letters. DON'T type them all out, use MINITAB's Data > Code menu to
automatically calculate a new variable. Once you've done this, make another pie graph. This
time make the title "Pie Chart for Seat2". Also, look through the options to uncheck including
missing data as a group.
Include both charts in your project. Depending on how you plan to print, you might want to
change the slice colors to be lighter, have more contrast, or change them to have hash marks
instead of color. Click on the pie, and then on the slice you want to edit (be careful with this - if
you don't do it just right you'll select the whole pie instead of just the slice).
(2.) Make side-by-side pie charts so that one can easily look at them and answer the question:
Where does each gender tend to sit? Don't include missing observations, and make the title
descriptive, something to the effect of "Pie Charts for Seating by Gender". For completeness,
you should also provide a table - also called a Cross Tabulation - for gender and seat preference.
Can you draw any initial conclusion(s) from these charts to compare seating preferences for
males vs. females?
(3.) Make comparison boxplots of ideal height with gender as groups. But before you do, think
about what sort of results you expect. What did you guess you'd see? Did the results agree?
Make a table of descriptive statistics to investigate the same question - ideal height with gender
as groups. Include the following statistics:
number of observations, mean, standard deviation, and the 5-number summary.
(4.) Make a histogram to show the distribution of how many alcoholic drinks per week were
consumed at UC Davis. Briefly comment on whether the result is surprising to you, given that it
comes from UC Davis. Why or why not? (there are arguments both ways, I'm just curious).
(5.) The variable is defined on a scale of 1-25 importance of personality (1) versus looks (25).
For fun, let's break this into three groups: Personality, Looks, and Both. Decide the cutoff
points for each, and again use the Data > Code menu to create a new variable, say, Looks2.
Use an appropriate graph to see whether or not girls really do care more about personality and
guys really do care more about looks. Comment on the result - is it what you expected, etc?
Congratulations! You've finished the project and also now know some basic MINITAB
functionality. Obtaining descriptive statistics, tables, and plots is an important part of any
statistical data analysis project.
DESCRIPTION OF THE DATASET:
Data from n=239 college students. The data were collected in the Fall quarter of 2000.
(Source: Jessica Utts, Robert Heckard via Mind on Statistics, Second Ed)
There are fourteen columns of data (variables):
Column Name
Description
C1
Sex
Male or Female
C2
GPA
Student's GPA
C3
Seat
Typical classroom seat location (Front Middle Back)
C4
alcohol
Number of alcoholic beverages consumed in typical week
C5
WtFeel
Does student feel he/she is Oveweight, Underweight, About Right?
C6
Height
Self-reported height, inches
C7
IdealHt
Student's choice of ideal height, inches
C8
momheight Mother's height, inches
C9
dadheight
Father's height, inches
C10
Hand
Are you Left-handed or Right-handed ?
C11
Looks
On a scale of 1-25 importance of personality (1) versus looks (25)
C12
Friends
Who is easiest to make friends with? (Opposite sex Same sex)
C13
Cheat
Would you tell the instructor if you saw somebody cheating on an exam?
C14
Smoke
Does student smoke at least one pack of cigarettes per week?