This document discusses analyzing box office data using SAS. It imports box office data from Excel files, combines the data sets, and performs various analyses including calculating means, correlations, frequencies, creating bar charts and scatter plots to examine the relationships between collections and numbers of various distributors. It also uses logistic regression and ANOVA to model relationships and test variables.

1. Boxoffice analysis
Vignesh.M
13MBA1021

2. Box office analysis
• proc import datafile="C:UsersAdministartorDownloadsboxoffice.xls"
out=work.distri;
• run;
• proc import datafile="C:UsersAdministartorDownloadsboxoffice2.xls"
out=work.scale;
• run;
• proc sql;
• create table work.distributors as
• select *
• from work.distri, work.scale
• where distri.Distributors = scale.Distributors
• order by distri.SNo;
• quit;

3. proc means data=work.distributors;
tables Distributors;
run;

5. Graph for correlation
proc corr data=work.distributors;
var Collections Numbers;
run;
proc freq data=work.distributors;
tables collections Numbers;
run;
PROC GCHART DATA=distributors;
VBAR collections Numbers/LEVELS=7;
RUN;
proc means data =work.distributors;
var collections Numbers;
run;

6. Box office vertical bar chart

7. Collection and numbers analysis

8. Plots on data
• TITLE 'Scatterplot - Two Variables';
• PROC GPLOT DATA=distributors;
• PLOT collections*numbers ;
• RUN;
• SYMBOL1 V=circle C=black I=none;
• SYMBOL2 V=star C=red I=none;

10. The LOGISTIC Procedure
Probability modeled is use=1.
Model Information
Data Set WORK.MODEL
Response Variable use use
Number of Response
Levels
2
Number of
Observations
26
Model binary logit
Optimization
Technique
Fisher's scoring

11. Regression and anova
• proc reg data =work.distributors;
• model boxoffice reg collections= numbers;
• run;
• proc anova data =work.distributors;
• class exp;
• model data emp tot = collections;
• run;