Dex Research Limited conducted a research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers. a. Complete the missing entries from A to H in this output b. Estimate the annual credit card charges for a three-person household with an annual income of $40,000. c. Did the estimated regression equation provide a good fit to the data? Explain
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Dex Research Limited conducted a research to investigate consumer characteristics that can be used to
predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers.
a. Complete the missing entries from A to H in this output
b. Estimate the annual credit card charges for a three-person household with an annual income of $40,000.
c. Did the estimated regression equation provide a good fit to the data? Explain
![Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
0.9086
A
0.8181
398.0910
ANOVA
df
SS
MS
F
Significance F
1.50876E-18
Regression
Residual
2
D
G
7448393.148
Total
49
42699148.82
Coefficients Standard Error
t Stat
P-value
Intercept
1304.9048
197.6548
6.6019
3.28664E-08
Income ($1000s)
33.1330
3.9679
H
7.68206E-11
Household Size
356.2959
33.2009
10.7315
3.12342E-14](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4ffab345-9f37-498c-9725-ab284b6957d1%2F3d598e49-aac7-420f-bca3-699862226826%2Frgaeaun_processed.png&w=3840&q=75)
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