How many variables are there? How many observations? What is the unit of observation for the data set (person-year, state, month)?

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

R data project

You can work in groups of three. Please turn in one assignment with all names at the top, in bold.

Often data comes unstructured. There is a bit of work to do before you can readily apply the concepts learned in this course. To receive credit for a project you will complete the following.

1)Load a data set into R.

The dataset is from the 2016 American Community Survey from colorado. It is located on the desire to learn as “ACS_2016_CO.csv” with an accompanying codebook describing the variable values. NOTE: the default data set is nice to have, but lot of the variables are top coded as 9999* because the information is missing. This isn’t valuable data when calculating statistics or creating plots and should not be used! (the command subset(-) in R is helpful for dealing with this)

2) Describe the data set with words.

How many variables are there? How many observations?

What is the unit of observation for the data set (person-year, state, month)? Is this a cross-section, or multiple observations over time? Do we have repeated observations for the same subject? Describe a few key variables that you will use in your data set including their units (feet, miles, $).

3)Summarize one of the quantitative variables for the full sample using sample statistics. 

Then, summarize the same quantitative variable for a subset of the observations that meet a  specific condition. (e.g. report the average, and standard deviation, monthly price of avocados in 20 major cities in the US from 2010 to 2015, then summarize the avocado price for all 20 cities only in the month of February). Try to choose the subsample in a way that is meaningful. How do the summary statistics compare and what do you learn from them? Include R code and output here, along with your interpretation.

4) Create a histogram of the variable that you summarize in part 3 with a properly labeled axis and title. (Bonus points if you can create two histograms of the same variable, split by some other variable, that are strikingly different). Include R output here, along with your interpretation.

5)Calculate a confidence interval

You can choose to calculate a confidence interval of one variable of a difference of means confidence interval. Pick something interesting to you and interpret your findings. Include your R code here and output here, along with your interpretation.

Attachments:

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