Regression Analysis of Relationship between Annual Income and Credit Card Charges

Quantitative Methods

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
Developing regression equation with annual income as independent factor and household size
as well.........................................................................................................................................3
Developing regression equation with help of both as independent variable...............................4
Need for other independent variable which can be added..........................................................5
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................7

INTRODUCTION
Quantitative method involves the statistical tools and techniques which is existed in
interpreting the data relating to the research. The present report will focus on using the statistical
tool of regression for analysing the relationship between the two variables. With the help of the
regression analysis the relationship between variables like annual income size and the amount
charged on credit card will be analysed.
MAIN BODY
Developing regression equation with annual income as independent factor and household size as
well
Annual income as independent factor
Regression
Statistics
Multiple R 0.29154
R Square 0.08499
Adjusted R
Square 0.03416
Standard Error 1162.97
Observations 20
ANOVA
df SS MS F
Significance
F
Regression 1 2261393 2261393 1.672 0.21
Residual 18 2.4E+07 1352506
Total 19 2.7E+07
Coefficients
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 2741.39 893.483 3.06821 0.00662 864.252 4618.53 864.252 4618.53
Income
($1000s) 23.7446 18.3631 1.29306 0.21234 -14.835 62.324 -14.835 62.324
Regression equation Y= 23.7446 X + 2741.39