Sas Case Studies
A FEW CASE STUDIES SOLVED
(Internal document of BusinessAnalytics.in)
BusinessAnalytics.in
#146, Ramaiah Street, 1st & 2nd Floor, Gopal Towers, Near Anjenaya Tech Park, Airport Road, Kodihalli, Bangalore - 560008
A Few Case Studies Solved
Case study 1. Correlation and Regression
Description of the Problem The owner of pizza corner, Bangalore would like to build a regression model consisting of six factors, to predict the sales of pizza. Data for past month sales and six different factors were collected for the purpose. Data description The variables for which the data have been collected are as follows: Dependent variable Y= monthly sales (in Rs.000’s) Independent variables X1= Number of delivery boys X2 = Cost of advertisement in Rs. 000’s X3 = Number of outlets X4 = Varieties of pizza X5 = Competitors activities index X6 = Number of existing customers (‘000) Data
Sl.no 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Sales 81 23 18 8 16 4 29 22 15 6 45 11 20 60 5 Boys 15 10 7 2 4 1 4 7 5 3 13 2 5 12 1 Adcosts 20 12 11 6 10 5 14 12 10 5 17 9 12 18 5 Outlets 35 10 14 9 11 6 15 16 18 8 20 10 15 30 6 Varieties 17 13 14 13 12 12 15 16 15 13 14 12 12 15 12 Competitor 4 4 3 3 4 5 2 3 4 2 2 3 3 4 5 Custmer 70 43 31 10 17 8 39 40 30 16 30 20 25 50 20
(Marketing Research by Rajendra Nargundkar page no. 272-278)
1. Importing the file This code is for importing the file from the source. The source is e:\regression and the file is named pizza.csv. libname bas "E:\regression"; run; proc import datafile ="E:\regression\pizza.csv" out = bas.pizza dbms= csv replace; run;
A Few Case Studies Solved
Page # 2
A Few Case Studies Solved
2. Checking for correlation ods html; /*codes for correlation*/ SAS output for correlation Variable Sales Boys Adcosts Outlets Varieties Competitor Custmer N 15 15 15 15 15 15 15 Mean 24.20000 6.06667 11.06667 14.86667 13.66667 3.40000 29.93333 Simple Statistics Std Dev Sum 21.91281 363.00000 4.51136 91.00000 4.75795 166.00000
(Internal document of BusinessAnalytics.in)
BusinessAnalytics.in
#146, Ramaiah Street, 1st & 2nd Floor, Gopal Towers, Near Anjenaya Tech Park, Airport Road, Kodihalli, Bangalore - 560008
A Few Case Studies Solved
Case study 1. Correlation and Regression
Description of the Problem The owner of pizza corner, Bangalore would like to build a regression model consisting of six factors, to predict the sales of pizza. Data for past month sales and six different factors were collected for the purpose. Data description The variables for which the data have been collected are as follows: Dependent variable Y= monthly sales (in Rs.000’s) Independent variables X1= Number of delivery boys X2 = Cost of advertisement in Rs. 000’s X3 = Number of outlets X4 = Varieties of pizza X5 = Competitors activities index X6 = Number of existing customers (‘000) Data
Sl.no 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Sales 81 23 18 8 16 4 29 22 15 6 45 11 20 60 5 Boys 15 10 7 2 4 1 4 7 5 3 13 2 5 12 1 Adcosts 20 12 11 6 10 5 14 12 10 5 17 9 12 18 5 Outlets 35 10 14 9 11 6 15 16 18 8 20 10 15 30 6 Varieties 17 13 14 13 12 12 15 16 15 13 14 12 12 15 12 Competitor 4 4 3 3 4 5 2 3 4 2 2 3 3 4 5 Custmer 70 43 31 10 17 8 39 40 30 16 30 20 25 50 20
(Marketing Research by Rajendra Nargundkar page no. 272-278)
1. Importing the file This code is for importing the file from the source. The source is e:\regression and the file is named pizza.csv. libname bas "E:\regression"; run; proc import datafile ="E:\regression\pizza.csv" out = bas.pizza dbms= csv replace; run;
A Few Case Studies Solved
Page # 2
A Few Case Studies Solved
2. Checking for correlation ods html; /*codes for correlation*/ SAS output for correlation Variable Sales Boys Adcosts Outlets Varieties Competitor Custmer N 15 15 15 15 15 15 15 Mean 24.20000 6.06667 11.06667 14.86667 13.66667 3.40000 29.93333 Simple Statistics Std Dev Sum 21.91281 363.00000 4.51136 91.00000 4.75795 166.00000