Regression Analysis on Facebook Ad Data R Codes and Regression Results: “` # Load necessary packages library(dplyr) library(esquisse) # Import Facebook ad data facebook_data <- read.csv("facebook_data.csv") # Attach dataset

1) Download Facebook Data Download Facebook Data. Download and Install R. 
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Read Regression Analysis in R.
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Perform a regression analysis on how spending, impressions, and clicks influence sales (Total_Conversion ~ Spent + Impressions + Clicks) on R. Screenshot the regression results and your codes. 
Think of codes as logical flow. You will need to attach() the dataset first to run a model (m1=lm()) on it. You will have to run the model (m1=lm()) to see the summary(m1) of the results. Run the codes in that order. 
Make sure that names of variables match those in the dataset exactly. Codes are case sensitive. 
[Optional – data visualization] Generate a plot (Y-axis: Total_Conversion, X-axis: Clicks) on ‘esquisser’ and color the graph by Impressions. Is there a linear relationship between the number of clicks and customer conversion?
Submit the screenshot with your interpretation of the results based on coefficients, p-values, and R-squared. (10 pts) 
(2) Use Excel for a regression analysis on Facebook Data Download Facebook Data. Read Statistical Analysis in Excel (Facebook)
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In Excel, the number of rows for all columns should be identical.