Project Instructions – Part I
Data Analysis Project
The primary objective of the project is for you to apply what you are learning in R and what you have
learned (or are learning) in your introductory statistics course, to data of interest to you.
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You should begin by exploring the datasets I provided on course works and the links to other data
sources under Files->Project. Alternatively, you can search for datasets from other sources. Open and
browse the variables in the datasets while thinking about the potential relationships between them. For
example, the relationship between height and weight variables, or comparing height or salary amount
across position title. Part I of your project will entail completing statistical analysis of relationships
between variables in the data, so it is important to think about relationships you potentially want to
explore before you make a final decision on what datasets you want to work with for your project.
You will be expected to complete an exploratory analysis (summary statistics and data visualizations)
and statistical analysis (confidence intervals and hypothesis testing) on at least 12 different variables
You will need to choose a mix of both categorical and quantitative variables in order to complete 6
statistical analyzes – two comparison of means across groups, two comparison of proportions across
groups and two linear regression analysis. The more variables you include in your project; the more
choices of statistical analysis vou will have for part Il of our project.
Part I of Project: Due on March 30th
For part I of your project you will submit an R program that demonstrates the use of the data
manipulation techniques, functions and data visualization coding techniques you will learn in class up to
the midterm exam. Second, you will write up a report based on the exploratory analysis you completed.
1. Applying your new Coding Skills
Don’t start your project thinking I simply have to demonstrate the use of the coding skills I am learning
in class. Start your project by thinking about what are my (research) hypothesis of interest. What are the
potential relationships in the data I want to explore in part Il of the project? What is the overall
objective of my research? The coding skills you learn provide you with the tools to complete that
objective. They enable you to load your datasets into dataframes; create new variables; select variables
you want to analyze; subset observations from datasets you want to analyze; merge (or join) two
datasets with variables you want to look at the relationship between; calculate summary statistics and
create data visualizations. Be clear on the objective of our research and you will naturallv make use of
your new coding skills to obtain that objective.
You R program should begin with a title and description box describing what the program is for and
what is doing. It should be clear from anyone reading the description what is the purpose of the
program. Always remember that your aim is to write readable, re-useable code. So an initial description
of what is the purpose of the program is very important to provide to the reader.
Each subsequent piece of code should have an clear explanation as to what the piece of code is doing
and why you are doing it. For example, don’t join two datasets to simply demonstrate joining two
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