Voting Data

Go to your text book p 124. Complete Exercise #1. Files are attached. You will need to preprocess the data before you do the homework. The Voting Behavior Data Specs PDF tells you what preprocessing you need to do. But, you need to make more columns to prep the data. I made new columns (inserted after Column D) that determined if they were mostly against using a =IF() function to give me a 1 or 0. I copied that column and pasted it with values only as column F. The formula can get in the way. NOTE: You can’t do anything in Tableau with the percentages so I also created new columns with actual numbers based off of the percentages for Whites, Blacks, Other, Males, Females. You should use the =ROUND(formula ,0) function to get this column. If you do these things, you’ll have preprocessed the data. • Go to your textbook p 124. Complete Exercise #1. Files are attached. o Variables for testing are: 1. 1. 1. The role of unemployment rate 2. Population density 3. The number of children living at home 1. Formulas that might be useful: 1. % = Y2/J2 2. Clean out the data … some big %ages: =IF(Z2<0.45, Z2, “”) 3. Rank the data: =IF(AA2>=0.3,3,IF(AA2>=0.25,2,1)) • Research the variables above to determine what you can learn about the relationship of these variables to a favorable vote on gambling. Are women more likely to vote for/against a gambling question? Do the number of children at home determine how parents vote on a gambling question? Find credible sources to support the development of your hypotheses. • You will need to preprocess the data before you do the homework. • Deliverables: 1. Executive Summary as a word doc (see example of Executive Summary) with your hypotheses and referencing your Tableau results, which should be included as visible screen shots. NOTE: Make sure your screen shots show columns, rows, filters, etc. 2. Excel file Upload a word doc (EXECUTIVE SUMMARY) with visible screen shots and the Tableau and Excel files as your deliverables. Download Tableau at Click on FREE STUDENT License and follow the instructions at the sight. Remember: You are checking reference VOTING for or against Gambling … not anything else! PLEASE NOTE: Make your screen shots showing Columns, Rows, Filters, etc. Follow my example. Good v Bad Hypotheses.docx Executive Summary Chapter 2 EXAMPLE.pdf Ref Chapter 2 Data Set – an explanation of the data.mp4 Voting Behavior Data Set.xls XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Professor’s notes for home work: Make sure you are using the correct three hypothesis. Don’t deviate. If you want to do extra for your own edification, that is fine … but make sure you do the three that are listed in the homework. Make sure you are making good hypotheses that the dataset will support. She my earlier announcement/ email. Make sure you are using the correct metric. If you are summing (ex. SUM(Unemployment Rate)) – you are going to get it wrong. You’d need to AVG(Unemployement Rate) unless you do some more preprocessing of the data and multiply that times Population. The problem with doing that, however, is that you get a number – without the percentage, how do you know if it is bad or good? So, I’d stick with the AVG …That brings up another point. For that one, you’d need to know what is considered Bad or Good. Another quick online reference is required. Also, don’t be shy about putting in multiple figures to support your claim. One figure typically isn’t enough and this exercise is designed to get you to play with Tableau. Enjoy it! Have fun! XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Example of Homework #2 p 124 Executive Summary (Week 2 Homework) Narrative: Data was provided on the voting behavior of 18 states regarding gambling. A complete breakdown of variables is found in the Gaming Ballot Data Description. Specific hypotheses (Ho) were created regarding the data that was then tested using Tableau. Ho 1 tested to see if states with larger populations would be more likely to vote for gambling. It was thought that this would be true. However, as shown in Figures 1 – 3, this Ho was incorrect. A complete description of the hypothesis and test can be found in Procedures and Evidence in the body of this document. Ho 2 tested … (etc.) Procedures and Evidence: 1. Data Set: Preprocessing was required to conduct analysis on the data set provided for Voting on Gaming Ballot Data. Specifically the following steps were taken: a. New columns (inserted after Column D) that determined if they were mostly against using a =IF() function to give me a 1 or 0. b. Columns with percentages were converted to actual numbers for [STATE WHICH COLUMS] c. I verified that percentages [STATE WHICH] equaled 1. [STATE ANY DISCREPANCIES] Do this if needed. d. I verified that the sum of …. Equaled the total population. Do this if needed. e. ETC. 2. The following Hypotheses were tested based on the voting data. Conclusions are listed after each hypothesis (note: I had to do a little independent research!). a. Hypothesis 1: States with larger populations will be more likely to vote for gambling. According to a Pew Research Center Poll ( trends/2018/05/22/urban-suburban-and-rural-residents-views-on-key-social-and- political-issues/) concerning Urban, suburban and rural residents’ views on key social and political issues, urban areas tend to be more liberal in all areas. Additionally, larger populated states tend to be more urban than rural in nature. Testing the hypothesis follows below XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX Good v. Bad Hypotheses Examples: Bad Hypothesis: More older women voted for gambling. Reason: No way of knowing how many women or older or otherwise voted for or against gambling based off the dataet provided. Really Bad Hypothesis: States with large numbers of older women are more economically depressed. Reasons: 1) No way of know how many older women are in the state. 2) This data is about gambling, not economics – even though there are some demographic and economic data in the dataset. Good Hypothesis: States where women outnumber men tended to vote against gambling. Reason: The dataset allows for this type of anaylsis. Make sure you back up your hypotheses with some type of internet research. Remember: your hypotheses can be right, wrong, or inconlusive … Use the template provided XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX 

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