Mean and Household Size

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Statistics Course Project Part 1

Student: Zissis Koukoutaris
Course : Statistics
Professor: Dimitrios Fotiadis
Semester: Fall-2012

Introduction
This report is written by Koukoutaris Zissis a student from Northeastern University. Mr Fotiadis my professor of the MGSC 23021 assigned me the task.

1. Use methods of descriptive statistics to summarize the data. Comment on the findings

2. Develop estimated regression equations, first using annual income as the independent variable and then using household size as the independent variable. Which variable is the better predictor of the annual credit card charges? Discuss your findings.

3. Develop an estimated regression equation with annual income and household size as the independent variables. Discuss your findings.

4. 4.What is the predicted annual credit card charge for a three-person household with an annual income of $40,000?

5. Discuss the need for other independent variables that could be added to the model.. What additional variables might be helpful?

Project Description:

Consumer Research Inc., is an independent agency that conducts research on consumer attitudes and behaviors for a variety of firms. In one study , a client asked for an investigation of consumer characteristics that can be used to predict the amount charged by credit card users. Data were collected on annual income, household size, and annual credit card charges for a sample of 50 consumers. The data at the end of this document ( consumer )are contained in the file consumer ( Chapter 15 of the book Statistics for business & Economics 11e, By Anderson, Sweeney and Williams) and is also provided on Bb.

Input file: See Appendix 1

Question 1:

Use methods of descriptive statistics to summarize the data. Comment on the findings:

Descriptives

Case Processing Summary|
| Cases|
| Valid| Missing| Total|
| N| Percent| N| Percent| N| Percent|
Income| 50| 100.0%| 0| .0%| 50| 100.0%|
HouseholdSize| 50| 100.0%| 0| .0%| 50| 100.0%|
AmountCharged| 50| 100.0%| 0| .0%| 50| 100.0%|

Descriptives|
| Statistic| Std. Error|
Income| Mean| 43.48| 2.058|
| 99% Confidence Interval for Mean| Lower Bound| 37.97| | | | Upper Bound| 48.99| |
| 5% Trimmed Mean| 43.42| |
| Median| 42.00| |
| Variance| 211.724| |
| Std. Deviation| 14.551| |
| Minimum| 21| |
| Maximum| 67| |
| Range| 46| |
| Interquartile Range| 25| |
| Skewness| .096| .337|
| Kurtosis| -1.248| .662|
HouseholdSize| Mean| 3.42| .246|
| 99% Confidence Interval for Mean| Lower Bound| 2.76| | | | Upper Bound| 4.08| |
| 5% Trimmed Mean| 3.36| |
| Median| 3.00| |
| Variance| 3.024| |
| Std. Deviation| 1.739| |
| Minimum| 1| |
| Maximum| 7| |
| Range| 6| |
| Interquartile Range| 3| |
| Skewness| .528| .337|
| Kurtosis| -.723| .662|
AmountCharged| Mean| 3964.06| 132.016|
| 99% Confidence Interval for Mean| Lower Bound| 3610.26| | | | Upper Bound| 4317.86| |
| 5% Trimmed Mean| 3971.48| |
| Median| 4090.00| |
| Variance| 871411.200| |
| Std. Deviation| 933.494| |
| Minimum| 1864| |
| Maximum| 5678| |
| Range| 3814| |
| Interquartile Range| 1638| |
| Skewness| -.130| .337|
| Kurtosis| -.742| .662|

Percentiles|
| Percentiles|
| 5| 10| 25| 50| 75| 90| 95|
Weighted Average(Definition 1)| Income| 21.55| 23.20| 30.00| 42.00| 55.00| 64.90| 66.45| | HouseholdSize| 1.00| 1.10| 2.00| 3.00| 5.00| 6.00| 7.00| | AmountCharged| 2463.95| 2597.80| 3109.25| 4090.00| 4747.50| 5285.80| 5461.35| Tukey's Hinges| Income| | | 30.00| 42.00| 55.00| | | | HouseholdSize| | | 2.00| 3.00| 5.00| | |

| AmountCharged| | | 3121.00| 4090.00| 4742.00| | |

Income| a)Mean =$43.48...
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