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## UCLA ?Campaign Funding and Election Outcomes R studio Exercise

### Question Description

Help me study for my Economics class. I’m stuck and don’t understand.

`rm(list=ls()) #rm(list of objects) removes all objects from workspacegraphics.off() #Closing all previously open graphs#****************************************************************************************#                  Campaign Funding and Election Outcomes                               *#****************************************************************************************# To study the relationship between campaign spending and congressional elections # outcomes, you use data on 173 congressional elections, each involving two candidates# (A and B), and their campaign costs. # # Key variables:# shareA - share (in %) of total campaign spending by candidate A.  # voteA  - percentage of total votes for candidate A. # democA - indicator of democratic party (1 if A is democrat, 0 otherwise)# 1. Load the data lacated at# #    "http://online.sfsu.edu/mbar/ECON312_files/vote1.csv" # #    into data.frame "vote". If the above link is not working, use this link instead:# #    https://faculty.sfsu.edu/sites/default/files/facul...# Complete the code between the lines:#________________________________________________________________________________________#________________________________________________________________________________________# 2. Present summary statistics of key variables.# Complete the code between the lines:#________________________________________________________________________________________#________________________________________________________________________________________# 3. Plot a scatter diagram of voteA against shareA. # Instructions:# (a). Add main title: "Share of votes vs. share of campaign spending".# (b). Beautify your figure by changing colors and font sizes, based on examples at#      http://online.sfsu.edu/mbar/ECON312_files/Plotting...#      # Complete the code between the lines:#________________________________________________________________________________________#________________________________________________________________________________________# 4. Estimate the linear model of voteA ~ shareA. Store the results in "model1", #    and present the summary of model1.# Complete the code between the lines:#________________________________________________________________________________________#________________________________________________________________________________________# 5. Add the fitted equation to your previous plot from Q-3. Add a legend to your graph.# Complete the code between the lines:#________________________________________________________________________________________#________________________________________________________________________________________# 6. Predict the % votes for candidate A, when candidate A spends [10,20,...,90] percent# of total campaign spending (by both candidates).# Complete the code between the lines:#________________________________________________________________________________________mydata <- data.frame('shareA' = seq(from =  , to =  , by = ))mydata\$pred_voteA <- mydata#________________________________________________________________________________________`

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