MATH 533 Week 7 Course Project Part C Regression and Correlation
Analysis (SALESCALL Project)
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Math 533
Course Project Part C
April 18, 2015
Scatter Plot
1. Generate a scatterplot for income ($1,000) versus credit balance ($), including
the graph of the best fit line. Interpret.
2. Determine the equation of the best fit line, which describes the relationship
between income and credit balance
The regression equation is
Income ($1,000) = - 3.52 + 0.0119 Credit Balance ($)
3. Determine the coefficient of correlation. Interpret.
Correlations: Income ($1,000), Credit Balance ($)
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, MATH 533 Week 7 Course Project Part C Regression and Correlation
Analysis (SALESCALL Project)
Thanks for rating! Rate 1 more document to earn a free unlock.
Pearson correlation of Income ($1,000) and Credit Balance ($) = 0.801
P-Value = 0.000. Since Income and Credit balance have a strong positive linear correlation, r is
close to +1 the correlation indicates an almost perfect positive fit. Positive values indicate a
relationship between Income and Credit Balance variables such that as values for Income
increases, values for Credit Balances also increase.
4. Determine the coefficient of determination. Interpret.
R-Squared = 64.1%, we can determine how accurate we are with the data given on the
scatterplot above.
5. Test the utility of this regression model (use a two tail test with α =.05).
Interpret your results, including the p-value.
DF SS MS F P
Regression 1 6052.7 6052.7 85.65 0.000
6. Based on your findings in 1–5, what is your opinion about using credit balance
to predict income? Explain.
Based on our findings we can say that we have enough data evidence to say that Income
and Credit Balance have a decent linear relationship.
7. Computing the 95% confidence interval for beta-1 (the population slope).
Interpret this interval.
(14.94, 26.86), we can be 95% sure beta -1 falls within the range.
8. Using an interval, estimate the average income for customers that have
credit balance of $4,000. Interpret this interval.
(41.77, 46.61), the average mean income is between $41,770 and $46,610 that have a
balance of $4,000.
9. Using an interval, predict the income for a customer that has a credit balance of
$4,000. Interpret this interval.
This study source was downloaded by 100000848900824 from CourseHero.com on 09-23-2022 00:51:22 GMT -05:00
https://www.coursehero.com/file/13896534/MATH-533-COURSE-PROJECT-PART-C/
Analysis (SALESCALL Project)
Thanks for rating! Rate 1 more document to earn a free unlock.
Math 533
Course Project Part C
April 18, 2015
Scatter Plot
1. Generate a scatterplot for income ($1,000) versus credit balance ($), including
the graph of the best fit line. Interpret.
2. Determine the equation of the best fit line, which describes the relationship
between income and credit balance
The regression equation is
Income ($1,000) = - 3.52 + 0.0119 Credit Balance ($)
3. Determine the coefficient of correlation. Interpret.
Correlations: Income ($1,000), Credit Balance ($)
This study source was downloaded by 100000848900824 from CourseHero.com on 09-23-2022 00:51:22 GMT -05:00
https://www.coursehero.com/file/13896534/MATH-533-COURSE-PROJECT-PART-C/
, MATH 533 Week 7 Course Project Part C Regression and Correlation
Analysis (SALESCALL Project)
Thanks for rating! Rate 1 more document to earn a free unlock.
Pearson correlation of Income ($1,000) and Credit Balance ($) = 0.801
P-Value = 0.000. Since Income and Credit balance have a strong positive linear correlation, r is
close to +1 the correlation indicates an almost perfect positive fit. Positive values indicate a
relationship between Income and Credit Balance variables such that as values for Income
increases, values for Credit Balances also increase.
4. Determine the coefficient of determination. Interpret.
R-Squared = 64.1%, we can determine how accurate we are with the data given on the
scatterplot above.
5. Test the utility of this regression model (use a two tail test with α =.05).
Interpret your results, including the p-value.
DF SS MS F P
Regression 1 6052.7 6052.7 85.65 0.000
6. Based on your findings in 1–5, what is your opinion about using credit balance
to predict income? Explain.
Based on our findings we can say that we have enough data evidence to say that Income
and Credit Balance have a decent linear relationship.
7. Computing the 95% confidence interval for beta-1 (the population slope).
Interpret this interval.
(14.94, 26.86), we can be 95% sure beta -1 falls within the range.
8. Using an interval, estimate the average income for customers that have
credit balance of $4,000. Interpret this interval.
(41.77, 46.61), the average mean income is between $41,770 and $46,610 that have a
balance of $4,000.
9. Using an interval, predict the income for a customer that has a credit balance of
$4,000. Interpret this interval.
This study source was downloaded by 100000848900824 from CourseHero.com on 09-23-2022 00:51:22 GMT -05:00
https://www.coursehero.com/file/13896534/MATH-533-COURSE-PROJECT-PART-C/
