Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 533: Applied Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store wants a random sample performed on 50 customers based on location, income, family size, and credit. The information provided in this study is needed so that AJ Davis can have a clearer idea of their customers spending habits based on the variables that have been made available . The correlation coefficients of the variables reveal and identify direct relationships. In doing so we are able to clarify that there is an extremely low chance that credit balances are due to chance. We are also able to utilize independent variables of income and size as significant contributions. This also allows for the variable of Years to be discarded because it does not have a significant contribution.
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 536: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store wants a random sample performed on 50 customers based on location, income, family size, and credit. The information provided in this study is needed so that AJ Davis can have a clearer idea of their customers spending habits based on the variables that have been made available . The correlation coefficients of the variables reveal and identify direct relationships. In doing so we are able to clarify that there is an extremely low chance that credit balances are due to chance. We are also able to utilize independent variables of income and size as significant contributions. This also allows for the variable of Years to be discarded because it does not have a significant contribution. • •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 536: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 536: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 525: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 542: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 542: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 543: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 543: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 543: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • • •
• •
Application Managerial Statistics Essay Preview: Application Managerial StatisticsReport this essayGM 540: Application Managerial StatisticsFelix Fair12/17/2012Professor Charles TrinkelProject Part CSummary ReportAJ Davis Department Store needs to provide the following information… • •
•
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 512: Applied Managerial StatisticsFelix Fair12/17/2012Harvards D.M., Robert S. and James R.R. “The Effects of a Differential Sales Data Point on Customer and Partner Behavior”. Job Security Review, September 2012. http://jobsecurityreviews.org/#/jobs_in-security/report/2/The-effects-of-a-differential-sales-data-point-on-customer-behavior The relationship of the customer acquisition program: an experiment, “the first step in a better way: product design and customer service” The Journal of the Association of Software Engineers, November 2011. http://sas.nasa.gov/content/2011/11/29/312513 “There is some agreement on the value for money as a measurement of customer behavior. A ‘value for money’ method, for instance, would say the customer is giving out a purchase with a higher cost per unit, whereas ‘a value for money’ would say that in terms of ‘fees’ the customer is giving out a ‘value for money’. Although this is not the case for purchasing, a more accurate measurement may indicate that the customer is giving out more than is necessary to maintain the transaction for a purchase. Therefore, both a value for money and a higher revenue to be derived from selling or buying will need to be taken into consideration, as well as an assessment including the sales process and costs involved with maintaining and adjusting purchases at the store”. -Michael S. Martin, “Customer Acquisition Research: A Review of the Current Value for Money,” The Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312515 “Differential Sales: A Systematic Approach in Context” -R. and M. C. Stahl, coauthor, “Data From Differential Sales Is the Beginning of The Beginning of a Process of Improvement, by Joseph F. Rees and Richard H. Smith,” Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312517 “Applied Managerial Statistics Essay Preview: Applied Managerial StatisticsReport this essayGM 548: Applied Managerial StatisticsFelix Fair12/17/2012Paul L. Johnson, James J.R. SiskelDepartment Store wants a random sample performed on 50 customers based on location, income, family size, and credit. The information provided in this study is needed so that AJ Davis can have a clearer idea of their customers spending habits based on the variables that have been made available . The correlation coefficients of the variables reveal and identify direct relationships. In doing so we are able to clarify that there is an extremely low chance that credit balances are due to chance. We are also able to utilize independent variables of income and size as significant contributions. This also allows for the variable of Years to be discarded because it does not have a significant contribution.”
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 610: Applied Managerial StatisticsFelix Fair12/17/2012J.S. Smith-S.P. and Charles Reisch. “Profitability of Credit and Pay-Cards: Evidence from a Random Sample.” Business Review, February 2011. http://www.businessreview.com/article/2567/2214/profitability-and-pay-cards-evidence-from
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 512: Applied Managerial StatisticsFelix Fair12/17/2012Harvards D.M., Robert S. and James R.R. “The Effects of a Differential Sales Data Point on Customer and Partner Behavior”. Job Security Review, September 2012. http://jobsecurityreviews.org/#/jobs_in-security/report/2/The-effects-of-a-differential-sales-data-point-on-customer-behavior The relationship of the customer acquisition program: an experiment, “the first step in a better way: product design and customer service” The Journal of the Association of Software Engineers, November 2011. http://sas.nasa.gov/content/2011/11/29/312513 “There is some agreement on the value for money as a measurement of customer behavior. A ‘value for money’ method, for instance, would say the customer is giving out a purchase with a higher cost per unit, whereas ‘a value for money’ would say that in terms of ‘fees’ the customer is giving out a ‘value for money’. Although this is not the case for purchasing, a more accurate measurement may indicate that the customer is giving out more than is necessary to maintain the transaction for a purchase. Therefore, both a value for money and a higher revenue to be derived from selling or buying will need to be taken into consideration, as well as an assessment including the sales process and costs involved with maintaining and adjusting purchases at the store”. -Michael S. Martin, “Customer Acquisition Research: A Review of the Current Value for Money,” The Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312515 “Differential Sales: A Systematic Approach in Context” -R. and M. C. Stahl, coauthor, “Data From Differential Sales Is the Beginning of The Beginning of a Process of Improvement, by Joseph F. Rees and Richard H. Smith,” Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312517 “Applied Managerial Statistics Essay Preview: Applied Managerial StatisticsReport this essayGM 548: Applied Managerial StatisticsFelix Fair12/17/2012Paul L. Johnson, James J.R. SiskelDepartment Store wants a random sample performed on 50 customers based on location, income, family size, and credit. The information provided in this study is needed so that AJ Davis can have a clearer idea of their customers spending habits based on the variables that have been made available . The correlation coefficients of the variables reveal and identify direct relationships. In doing so we are able to clarify that there is an extremely low chance that credit balances are due to chance. We are also able to utilize independent variables of income and size as significant contributions. This also allows for the variable of Years to be discarded because it does not have a significant contribution.”
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 610: Applied Managerial StatisticsFelix Fair12/17/2012J.S. Smith-S.P. and Charles Reisch. “Profitability of Credit and Pay-Cards: Evidence from a Random Sample.” Business Review, February 2011. http://www.businessreview.com/article/2567/2214/profitability-and-pay-cards-evidence-from
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 512: Applied Managerial StatisticsFelix Fair12/17/2012Harvards D.M., Robert S. and James R.R. “The Effects of a Differential Sales Data Point on Customer and Partner Behavior”. Job Security Review, September 2012. http://jobsecurityreviews.org/#/jobs_in-security/report/2/The-effects-of-a-differential-sales-data-point-on-customer-behavior The relationship of the customer acquisition program: an experiment, “the first step in a better way: product design and customer service” The Journal of the Association of Software Engineers, November 2011. http://sas.nasa.gov/content/2011/11/29/312513 “There is some agreement on the value for money as a measurement of customer behavior. A ‘value for money’ method, for instance, would say the customer is giving out a purchase with a higher cost per unit, whereas ‘a value for money’ would say that in terms of ‘fees’ the customer is giving out a ‘value for money’. Although this is not the case for purchasing, a more accurate measurement may indicate that the customer is giving out more than is necessary to maintain the transaction for a purchase. Therefore, both a value for money and a higher revenue to be derived from selling or buying will need to be taken into consideration, as well as an assessment including the sales process and costs involved with maintaining and adjusting purchases at the store”. -Michael S. Martin, “Customer Acquisition Research: A Review of the Current Value for Money,” The Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312515 “Differential Sales: A Systematic Approach in Context” -R. and M. C. Stahl, coauthor, “Data From Differential Sales Is the Beginning of The Beginning of a Process of Improvement, by Joseph F. Rees and Richard H. Smith,” Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312517 “Applied Managerial Statistics Essay Preview: Applied Managerial StatisticsReport this essayGM 548: Applied Managerial StatisticsFelix Fair12/17/2012Paul L. Johnson, James J.R. SiskelDepartment Store wants a random sample performed on 50 customers based on location, income, family size, and credit. The information provided in this study is needed so that AJ Davis can have a clearer idea of their customers spending habits based on the variables that have been made available . The correlation coefficients of the variables reveal and identify direct relationships. In doing so we are able to clarify that there is an extremely low chance that credit balances are due to chance. We are also able to utilize independent variables of income and size as significant contributions. This also allows for the variable of Years to be discarded because it does not have a significant contribution.”
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 610: Applied Managerial StatisticsFelix Fair12/17/2012J.S. Smith-S.P. and Charles Reisch. “Profitability of Credit and Pay-Cards: Evidence from a Random Sample.” Business Review, February 2011. http://www.businessreview.com/article/2567/2214/profitability-and-pay-cards-evidence-from
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 512: Applied Managerial StatisticsFelix Fair12/17/2012Harvards D.M., Robert S. and James R.R. “The Effects of a Differential Sales Data Point on Customer and Partner Behavior”. Job Security Review, September 2012. http://jobsecurityreviews.org/#/jobs_in-security/report/2/The-effects-of-a-differential-sales-data-point-on-customer-behavior The relationship of the customer acquisition program: an experiment, “the first step in a better way: product design and customer service” The Journal of the Association of Software Engineers, November 2011. http://sas.nasa.gov/content/2011/11/29/312513 “There is some agreement on the value for money as a measurement of customer behavior. A ‘value for money’ method, for instance, would say the customer is giving out a purchase with a higher cost per unit, whereas ‘a value for money’ would say that in terms of ‘fees’ the customer is giving out a ‘value for money’. Although this is not the case for purchasing, a more accurate measurement may indicate that the customer is giving out more than is necessary to maintain the transaction for a purchase. Therefore, both a value for money and a higher revenue to be derived from selling or buying will need to be taken into consideration, as well as an assessment including the sales process and costs involved with maintaining and adjusting purchases at the store”. -Michael S. Martin, “Customer Acquisition Research: A Review of the Current Value for Money,” The Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312515 “Differential Sales: A Systematic Approach in Context” -R. and M. C. Stahl, coauthor, “Data From Differential Sales Is the Beginning of The Beginning of a Process of Improvement, by Joseph F. Rees and Richard H. Smith,” Journal of the Association of Software Engineers, December 2012. http://sas.nasa.gov/content/2012/11/29/312517 “Applied Managerial Statistics Essay Preview: Applied Managerial StatisticsReport this essayGM 548: Applied Managerial StatisticsFelix Fair12/17/2012Paul L. Johnson, James J.R. SiskelDepartment Store wants a random sample performed on 50 customers based on location, income, family size, and credit. The information provided in this study is needed so that AJ Davis can have a clearer idea of their customers spending habits based on the variables that have been made available . The correlation coefficients of the variables reveal and identify direct relationships. In doing so we are able to clarify that there is an extremely low chance that credit balances are due to chance. We are also able to utilize independent variables of income and size as significant contributions. This also allows for the variable of Years to be discarded because it does not have a significant contribution.”
Applied Managerial StatisticsEssay Preview: Applied Managerial StatisticsReport this essayGM 610: Applied Managerial StatisticsFelix Fair12/17/2012J.S. Smith-S.P. and Charles Reisch. “Profitability of Credit and Pay-Cards: Evidence from a Random Sample.” Business Review, February 2011. http://www.businessreview.com/article/2567/2214/profitability-and-pay-cards-evidence-from
The conclusion that was determined along with and because of the analysis, Is summarized that income and size are good predictors that credit balances will increase. This information and the identification of these relationships are important to AJ Davis Department Store and enhance their ability to improve their current model. The following statistics show how AJ Davis Department store will be able to thrive..
Using MINITAB perform the regression and correlation analysis for the data on CREDITBALANCE (Y) and SIZE (X) by answering the following.1. Generate a scatterplot for CREDIT BALANCE vs. SIZE, including the graph of the best fit line. Interpret.From the scatter plot it is evident that the slope of the best fit line is positive, which indicates that Credit Balance varies directly with Size. As Size increases, Credit Balance increases and vice versa.
MINITAB OUTPUT:Regression Analysis: Credit Balance($) versus SizeThe regression equation isCredit Balance($) = 2591 + 403 SizePredictor Coef SE Coef T PConstant 2591.4 195.113.290.000Size 403.22 51.00 7.910.000S = 620.162 R-Sq = 56.6% R-Sq(adj) = 55.7%Analysis of VarianceSource DF SS MS F PRegression 1 24092210 2409221062.640.000Residual Error 48 18460853384601Total 49 42553062Predicted Values for New ObservationsNew Obs Fit SE Fit 95% CI 95% PI1 4607.5119.0 (4368, 4846.9) (3337.9, 5877.2)Values of Predictors for New ObservationsNew Obs Size1 5.002. Determine the equation of the best fit line, which describes the relationship between CREDIT BALANCE and SIZE.The equation of the best fit line or the regression equation isCredit Balance ($) = 2591 + 403.2 Size3. Determine the coefficient of correlation. Interpret.The coefficient of correlation is given as r = 0.752. The positive sign of the correlation coefficient indicates a positive or direct relationship between the variables. The correlation coefficient is far from the P-Value of 0.000, P-Value of 0.000 is low. This means that there is an extremely low chance that Credit Balance and Size results are due to chance.
MINITAB OUTPUT:Pearson correlation of Credit Balance ($) and Size = 0.752. P-Value = 0.0004. Determine the index of determination. Interpret.The index of determination, r-square = 0.566. The proportion of variability in a dataset that is accounted for by the regression model is given by the coefficient of determination R^2, which for this regression model is 56.6%.
MINITAB OUTPUT;S = 620.162 R-SQ = 56.6% R-SQ(adj)= 55.7%5. Test the utility of this regression model (use a two tail test with α =.05). Interpret your results, including the p-value.The null hypothesis,H_0 states that there is no significant correlation, or the correlation coefficientρ=0.Significance Level, α = 0.05Decision Rule: RejectH_0 ifthep-value< 0.05 (significancelevel,alpha) From the ANOVA table, we find that the p-value 0.000is much less than 0.05. Therefore, we reject the null hypothesis that there is no significant correlation and conclude that, according to the overall test of significance, the regression model is valid. MINITAB OUTPUT: Analysis of variance Source DF SS MS F P Regression 1 24092210 24092210 62.64 0.000 Residual Error 48 18460853 384601 Total 49 42553062 6. Based on your findings in 1-5, what is your opinion about using SIZE to predict CREDIT BALANCE? Explain. Size is a very good predictor of Credit Balance. As Size increase Credit Balance increases and they are correlated. Therefore, as the Size of the household grows so does the Credit Balance of those households. 7. Compute the 95% confidence interval for β. Interpret this interval. The 95% confidence interval for β is given as (301.59, 506.67). If repeated observations