This document outlines an analysis of sales records between TVS SFI and Bosch for the years 2011-2013. It includes importing data on part numbers, prices, and quantities from Excel files, merging the files, and performing statistical analyses including frequency tables, means, regression, and ANOVA to determine the most frequently ordered material part number, average order quantity, and most influencing variable for order quantity.

1. Professor – Dr. P James Daniel Paul
By,
G Pavithraa
13MBA1047

2.  The Sales records of TVS SFI to Bosch for 2
years (2011-13).
 The Prices of every part that was ordered
during this period.

3.  Frequency in the data in terms of the material
part no.
 Average order placed during the period.
 Most influencing variable for the quantity of
order placed.
 Regression Model.

4.  Import of Data:
proc import datafile = "C:UsersacerDesktopBOSCH
OUTPUTTVSBOSCHBosch TRANS.xls" out=Work.BoschTrans;
run;
proc import datafile = "C:UsersacerDesktopBOSCH
OUTPUTTVSBOSCHPrice of Bosch.xls" out=Work.BoschPrices;
run;
 Merging the files
proc sql;
create table work.col as select*
from work.Boschtrans,work.Boschprices where
Boschtrans.SFL_Part_No=Boschprices.SFL_Part_No
order by Boschtrans.S_no;
quit;
 Converting the output to pdf file
ODS pdf file = 'C:UsersacerDesktopBOSCH OUTPUTfinal.pdf';

5.  Frequency Table
proc freq data=work.col;
tables SFL_Part_No;
run;
 Average:
Proc means data=work.col;
var Quantity;
run;
 Regression
proc reg data=work.col;
model Var_ =Quantity;
run;
quit;
 Anova
proc anova data=work.col;
class sub;
model Var_ =sub;
run;
ODS pdf close;
run;

6.  MA3380-0101 – is the material that was
ordered most no. of times (using frequency
table)
 Average frequency of order in quantity is 985
 Bosch in Jaipur was the plant which ordered
more in quantity and more frequently as well.
(using anova)
 Estimation of quantity in terms of Part no.
was not significant. (using regression)