(NN quetions1) Below is the result of the str() function on…
(NN quetions1) Below is the result of the str() function on the creditscore data. The dependent variable is Sales. Refer to this and answer the questions below. > str(df) ‘data.frame’: 400 obs. of 11 variables: $ CompPrice : int 138 111 113 117 141 124 115 136 132 132 … $ Income : int 73 48 35 100 64 113 105 81 110 113 … $ Advertising: int 11 16 10 4 3 13 0 15 0 0 … $ Population : int 276 260 269 466 340 501 45 425 108 131 … $ Price : int 120 83 80 97 128 72 108 120 124 124 … $ ShelfLoc : chr “Bad” “Good” “Medium” “Medium” … $ Age : int 42 65 59 55 38 78 71 67 76 76 … $ Education : int 17 10 12 14 13 16 15 10 10 17 … $ Urban : chr “Yes” “Yes” “Yes” “Yes” … $ US : chr “Yes” “Yes” “Yes” “Yes” … $ Sales : num 9.5 11.22 10.06 7.4 4.15 … Below is the R code for neural network analysis. When you run the code below, a syntax error occurs. (Assume the data is imported normally and libraries are loaded normally.) 1) Please modify, add, or delete the part(s) where the syntax error occurs and upload the modified code.
Read Details(Linear Regression1) Use the attached data for the following…
(Linear Regression1) Use the attached data for the following problem.residual_dataset.xlsx The attached data contains variables X1, X2, and Y. X1 and X2 are independent variables, and Y is the dependent variable. Please conduct a multiple regression using these variables. Then, using the results of residuals, find an optimal regression model that best fits the attached data (i.e., the optimal model has a good result for residual test we studied). You must do everything using Excel. Then, save the entire process and submit it. The first tab of the Excel file to be submitted should contain the regression model that best fits the data you found.
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