Statistics

Many governments throughout the world are participating in​ “Open Data” initiatives. Open Data are data​ collected, usually at taxpayer​ expense, to help inform policy and decision making. Once you have identified a government with open​ data, find an area or theme that interests you. For​ example, you might be interested in response times of the fire​ department, crimes, how much government employees are​ paid, or the health ratings of restaurants. Some cities organize data by​ theme, such as​ Finance, Public​ Safety, and so on. You might have to do some poking around to find a data set that is interesting.
Your goal is to download a data file. But not just any data​ file; we need one that your statistical software will understand. To do​ this, you will want to look for some sort of option to​ “Export” or​ “Download” a file. In some​ cases, these words might not be used and you are expected to simply click on a link.
There are three things you need to pay attention​ to: the​ format, the​ structure, and the existence of metadata.
Format refers to the types of files provided and the software that can open them. For​ example, files that end in
“.txt” or “.csv” are text files and can usually be open by many types of​software. StatCrunch wants files that end in​ .xlsx, .xls​ (Excel spreadsheets), .ods​ (OpenOffice​spreadsheet), or​ .csv, .txt, or .tsc​ (text files).
Data files often use a delimiter to determine where one entry ends and another begins. For​ example, if a data file contains the text string​ “1345” you do not know whether it is the number one thousand three hundred​ forty-five or the four digits​ 1, 3,​ 4, 5 or the two numbers 13 and 45 or anything else. A delimiter tells you when one value ends and the next begins. A​ comma-delimited file, which usually ends in the extension​ .csv, uses commas to display​ “1, 34,​ 5” for the values​ one, thirty-four, and five. A​ tab-delimited file​ (.tsv or​ .txt) uses tabs as shown.
1 34 5
Metadata is documentation that helps you understand the data. Sometimes it is called a​ “codebook” or​ “data dictionary.” It should answer the​ who, what,​ when, where,​ why, and how of the data. But most​ important, it should tell you what the variable names mean and what the values mean. With any​ luck, it will also tell you the data type​ (for example, whether it is a number or a​ character).
​Warning: you might have to look at a great many data files before you find one that is useful.
How to Submit
Put your answers to the following questions and upload the document here.

What is the URL of the page from which you downloaded your​ data?
How many variables are​ there? How many​ observations?
Do you have 2 categorical and 2 quantitative variables in your data set? If so, please choose two each and list them.
What does a row in the data set​ represent? In other​ words, what is an​ observation or case in context?
Why were these data​ collected? What is their​ purpose? How were they​ collected? Why were you interested in this data​ set? Give some examples of what you want to know from these data.
Try to upload the data to StatCrunch. Describe what happens. Did you get what you​ expected? Did you get an​ error? Describe the outcome. If you succeed in uploading the data set, please share in our class StatCrunch group.