Analyzing Data

Option 1: For anyone new to Excel 1. Complete this screenshot tutorial  introductory_excel.pdf   using this sample data:  data.xlsx . NOTE: There’s been some confusion in the past because the first few pages of the PDF document are all explainer, without directions. Keep reading and at page 6, it will start having directions for things you should do in the Excel file. 2. Save your Excel sheet and submit your work. 3. Submit a brief reflection. I haven’t used this assignment before and I want to know what you thought of it – was it easy/hard? What aspects of it were useful? What aspects of it were not? What pieces needed more explanation? Were there pieces that felt too basic? Do you feel like you will use what you learned here? Approximately how long did it take you? Any thoughts you have on it, please share them.  Note: I’ve provided what I hope are helpful comments throughout on the PDF in blue. Some of them are general; some of them are specifically to redirect Mac users, since this guide was created from a PC.  If you are using a ChromeBook, and therefore Google Sheets, several elements of this assignment won’t work for you. Contact me for an alternative. Option 2: Some experience with Excel This option is intended for folks who have a little experience with excel. If you are already comfortable with basic excel navigation  this option takes you into a little more detail – not just the mechanics of where to click, but also thinking about why you do what calculations when (and how). It provides two data from which to chose to analyze, guided by the questions provided on a worksheet. 1. Read  Herzog – Analyzing Data.pdf  and  Herzog – Visualizing Data.pdf   Note: If you’d like to work along with the readings, the data sets being used can be found here: https://study.sagepub.com/herzog 2. Select which of these sample data sets you’d like to work with:   2018 NCAAF Coach and Asst. Coach Salaries.xlsx  federalelections2016.xlsx   If you’d like to use a different data set, let me know. 3. Download the  Data Analysis & Visualization Worksheet.docx   4. Work through the questions on the worksheet for your analysis. Submit your completed worksheet & the spreadsheet with your analysis via Blackboard. 5. Also submit a brief reflection on your experience with this assignment. I’m always playing with this assignment to figure out what works best so I want your feedback! What aspects of it were useful? What aspects of it were not? What pieces needed more explanation? Were there pieces that felt too basic? Do you feel like you will use what you learned here? Approximately how long did it take you? Any thoughts you have on it, please share them. Option 3: For anyone who is a pro in Excel, or who wants more experience and practice coding There are several coding languages that are frequently used for data analysis. If you are already a pro in Excel, or just interested in getting some more experience with coding, you can use this option to learn R for data analysis. Python is another frequently used language for data analysis, but it requires a little more work to get situated, so I’ve opted for R here. If you are curious, here is an infographic about Python vs. R. If Python is it for you, talk to me and we can discuss what that option might look like.  There are several steps to this assignment 1. Complete lessons 1 & 2 of the R codecademy course. (Note, there are Pro/paid elements – skip those).  2. Download RStudio, and R.  A few notes about these steps: For RStudio, I did Desktop because I didn’t notice Server. I can’t speak to how Server is different. Just make sure you are using the open source one, not one of the paid options) For downloading R: yes, I realize the site looks like a strange relic of the 90s, but don’t let that cause dismay. It’s legit. 3. Watch the three BasicBasics Videos from R-Ladies Sydney (in BasicBasics 1, BasicBasics2, and BasicBasics 3), to get to know RStudio, and get up and running. (I recommend you follow along with her to import the packages. Everything else is up to you if you want to just watch or work with her. Note: The first half of the third video is really important, but the second half isn’t as relevant to what we are doing so you don’t have to keep watching.  4. Download the DiscoveryTechnologyR Zip folder below. In this folder you’ll find an R Studio project, a data set and a script file. Open the project file in RStudio and complete the directions provided in the script as #comments with your code. 5. Save the project, zip your project folder and upload it to Blackboard.  6. Submit a brief reflection on your experience with this assignment. This is a new option for this assignment so I want your feedback! What the documentation provided sufficient to accomplish the assignment? Approximately how long did it take you? Would you have liked to see more covered (like data visualization)? Would you have liked to see less covered? Any thoughts you have on it, please share them  DiscoveryTechnologyR.zip A few notes: I am new to R too, which means that any challenges you encounter, I probably encountered them too while getting situated, so ask for help!  Many many times the reason my code didn’t work was because of a typo I struggled with piping cause I was doing it wrong. To save you from the trouble I had let me share what I figured out now:   When they teach variable naming it’s always at the beginning. I put it after the piping but that doesn’t work, you gotta do it before the piping. For example chosen_cols <- artists %>% select(-country,-year_founded,-albums) head(chosen_cols)

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