Data Analysis Project
Data Analysis Project:
brainstorm a question of interest to investigate (it can be silly – the idea is to have fun
practicing statistics!)
design your own study/experiment based on that question of interest
collect data by yourself
summarize your results with appropriate numerical and graphical methods
use appropriate inference procedures to make statements about the population of interest
given your sample results (choices below)
prepare a report of your project that conveys your data analysis process, results, and
conclusions
Ideally, you will be working in groups of 3-5 unless you have a very strong desire and question you want to
pursue on your own (sharing the workload, especially for data collection really helps!). Group choice is up to
you, but you should choose people from the same discussion class.
Choices for inference procedures and questions (should guide your brainstorming of questions). You may not use these
examples. Similar ones are fine but try to find something interesting you want to investigate
Estimate a population mean (how many hours students sleep, exercise, work etc.).
Take under consideration gender or year of study or students who live/don’t live on campus
Estimate a population proportion (political preference, proportion of students who work ,date…
Take under consideration gender or year of study or students who live/don’t live on campus
Regression – examining a relationship between two quantitative variables and model this relationship, for
instance, number of hours of working or studying and GPA.
Hypothesis testing for a population proportion, population mean, difference in two population
means or proportions.
Question Choice:
Your question of interest may or may not involve human subjects. There are some additional guidelines for
questions pertaining to studies involving human subjects that you are expected to follow if your question
does involve human subjects.
For the purposes of this project if your project involves human subjects:
Studies involving human subjects must focus on adults (college students are fine).
Questions CANNOT be sensitive questions (e.g., drug use, sexual behavior) or questions about
illegal behavior (e.g., drug use, underage alcohol) and cannot involve deception.
Data MUST be collected anonymously so that it cannot be traced back to the individuals who
provided the responses.
If you think your question may not meet these guidelines, pick another question that does.
Basically these guidelines will allow you to administer surveys to your fellow students or observe some
action undertaken by them so long as the questions are appropriate and you collect the data anonymously.
It also allows for observations of adults who are not college students (example: you observe how long
drivers stop at a stop sign and record their gender to test for differences in duration of average stop time).
Including Additional Tests or CIs:
- You can include additional tests or CIs, including results for proportions , means if you have
additional variables recorded, and you decide there is something you want to investigate - I do not need to see assumption/checks etc. for these, as they are “extra” stuff of interest, but you
should check assumptions before you run these. I.E. You may find that male drivers stop for a shorter length of time on average than females (actual test for project – I would need to see the
conditions, etc.) but also note that male drivers ran red lights more often than female drivers (extra
test comparing 2 proportions – don’t need to see the conditions, etc.).There will be some things not
covered in class and you will need to do some reading. You have also to use technology for your
project – Minitab Express.
Time Schedule and Deadlines: - March 18 (if you are in Stat240.2)or March 20 (if you are in Stat240.1) – deadline to submit
the group member names and proposal to your TA. - One page (maximum) description of project as a proposal is expected (Really
1-2 paragraphs will do – see example at end of this handout). Proposals should include your
proposed topic, choice of inference procedure, and some ideas on data collection, as well as group
member names (one copy per group). - You will have our feedback and can then start data collection. You should have your data
collected by April 15 .
(This is only a suggestion but would be a good pace, leaving you enough time for the analysis and
report writing). - Preliminary and formal analysis can be done any time after data has been collected. You can work
on writing up different parts (see below) as you do them as well. - Final reports are due – the day of the final exam. One copy per group. Please turn in a hard
copy of the final report to me.
Reports – should contain the following sections (at a minimum):
Introduction
o Introduce the problem
Methods
o Discuss the design of your study (what, why, how implemented)
o Describe the inference procedure that is appropriate for your question
o Discuss the assumptions that inference procedure has
o Discuss how you will check those assumptions (do not discuss results of the checks until results)
Results
o Preliminary Analysis
Graphical description of data
Numerical description of data
o Formal Analysis
Assumption checking – report on whether or not the conditions check out
Inference procedure test statistic , p-value, CI, decision
Conclusions
o Real world conclusion from inference procedure
o Suggestions/Cautions for future analysis – there is always something to improve!
Appendix
o Relevant graphs if not included above
o Inference output if not included above
o Usually we submit data set , but we are not going to do this (save paper)
You should include relevant graphs; you may put them with the related content or in the appendix and refer to them.
Resize graphs, shrink them substantially.
Length – No set limits but a 2-3 page report and appendix combined is perfectly reasonable. You do not need to have a
cover page.Example Proposal:
Group members:
Amy …….. , Stat 240.1, TA name
Herle …….. , Stat 240.1, TA name
Lacey…….. , Stat 240.2, TA name
As students living on a budget, and perhaps not always eating at campus, we’d like to study the prices of some common
grocery items at Big Y vs. Stop N Shop to see whether one store is cheaper to shop at on average. A quick Yahoo search
for “common grocery list” reveals many results. We may adapt a list of those items, but plan to obtain results for more
than 40 different items. To address “brand” issues, we will always compare store brands if available, and if not, at the
first store we go to, we will pick a brand (assuming fewer than 10 brands of most common items), and check for that
brand at the other store.
Our setup for this project is therefore a paired t-test for average price. The observations are paired because we get one
price from each observation at each store. (This project will require extra reading, so maybe you should choose
something less advanced).
I.E. our data set will look like:
BigY StopNShop
Flour
Water
Sugar
Yogurt
Cheese
etc.
Likely comments (what I might comment if you turned this in):
Might be more interesting to compare “snack” or “party” items, rather than an entire grocery list
Are you doing Big Y- Stop or Stop-Big Y? Be sure to specify. Do you have a direction picked?
What happens if the brand you chose because there was no store brand is not at the other store?
What happens if something is on sale when you check prices?
Are you counting “card” discounts (both stores have those in some fashion)?
What happens if the store brands are not the same size!?! Are you going to record units as well?
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