Editing Statistics and Statistical Programming (Spring 2019)/Problem Set: Week 3
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:'''PC0.''' Create a new project and RMarkdown script for this week's problem set (as usual). | :'''PC0.''' Create a new project and RMarkdown script for this week's problem set (as usual). | ||
:'''PC1.''' Revisit your code from last week and recall what group number you were in (should be an integer between 1-20). Navigate to the [https://communitydata.cc/~ads/teaching/2019/stats/data data repository for the course] and download the .csv file in the <code>week_03</code> subdirectory with your group number from PC1 last week associated with it (e.g., <code>group_<output>.csv</code>). Note that it is a .csv file and not an .RData file. | :'''PC1.''' Revisit your code from last week and recall what group number you were in (should be an integer between 1-20). Navigate to the [https://communitydata.cc/~ads/teaching/2019/stats/data data repository for the course] and download the .csv file in the <code>week_03</code> subdirectory with your group number from PC1 last week associated with it (e.g., <code>group_<output>.csv</code>). Note that it is a .csv file and not an .RData file. | ||
::'''PC1.5''' Open the dataset and take a look at it! You might use spreadsheet software (e.g., Google docs, LibreOffice, Excel, etc.) to do this, or it is a good idea to open it in a text editor (e.g., NotePad) so you can inspect the structure of the "raw data." Manually inspecting the raw data is common and useful since it can help you figure out how best to read it into R. I won't ask about this | ::'''PC1.5''' Open the dataset and take a look at it! You might use spreadsheet software (e.g., Google docs, LibreOffice, Excel, etc.) to do this, or it is a good idea to open it in a text editor (e.g., NotePad) so you can inspect the structure of the "raw data." Manually inspecting the raw data is common and useful since it can help you figure out how best to read it into R. I won't ask about this is class, but I do recommend it. | ||
:'''PC2.''' Read the CSV file into R using the <code>read.csv()</code> command. | :'''PC2.''' Read the CSV file into R using the <code>read.csv()</code> command. | ||
:'''PC3.''' Get to know your data! Do whatever is necessary to summarize the new dataset. How many columns and rows are there? Report appropriate summary statistics for each variable (e.g., what are the ranges, minimums, maximums, means, medians, and standard deviations of the continuous variables?). Plot histograms for each of the variables to get a sense of what they look like. | :'''PC3.''' Get to know your data! Do whatever is necessary to summarize the new dataset. How many columns and rows are there? Report appropriate summary statistics for each variable (e.g., what are the ranges, minimums, maximums, means, medians, and standard deviations of the continuous variables?). Plot histograms for each of the variables to get a sense of what they look like. | ||
