Desccriptive Stats

 Essay on Desccriptive Figures

QM2 Task

Case Study 1- Consumer Attributes

Index

Sno Title Page. no 0| Introduction| several

1| Outlining data employing Descriptive Statistics| 4-6

a couple of

2 . 1

2 . 2| Estimated regression equations.

Self-employed Variable- Annual rent.

Independent Variable- Household Size| 7

almost 8

9

3| Better predictor of annual credit card charges| 10

4| Independent variables- Annual income and Household size| 11| 5| Forecasting Gross annual Credit Charge| 12

6| Need for additional independent variables| 13

7| Test the significance of the overall regression model| 14| 8| Test the value of the individual regression coefficients| 15-16| 9| Relationship Matrix| 17

10

| Coefficient of Determination| 18

11| Quick Note| nineteen

Introduction

The project is done in Multiple Regression for the situation study Client Characteristics. Multiple Regressions is simply a record tool accustomed to predict the values of one variable which is dependent on the values of two or more variables. In the case examine Future View”, Inc., is usually an independent agency that conducts research on the consumer thinking for a selection of firms. Factors such as the consumer characteristics are taken into account forecast the amount incurred by visa or mastercard users. Data was also collected about annual income, home size and annual visa or mastercard charges for the sample of 50 consumers.

1-Summarizing data applying Descriptive Statistics

Descriptive figures enlightens us with basic summaries regarding the declaration and samples that have been completed. This method can either be done on a population or for a sample. In the case research of buyer characteristics, data on the 3 variables offered here are the income annual income, household size, and total annual credit card fees for a test of 50 customers. With the help of APPLE SPSS the descriptive figures for these 3 variables will be as follows-

Descriptive brief summary for Annual rent

INCOME| Statistic| Std. Mistake

| Mean| 43. 48| 2 . 058

| 95% Confidence Period

| Lower Bound| 39. 34|

| | Upper Bound| 47. 62|

| 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

Descriptive Statistics pertaining to Household Size

Household Size| Statistic| Std. Error

| Mean| 3. 42|. 246

| 95% Confidence Period for Mean| Lower Bound| 2 . 93| | | | Top Bound| a few. 91|

| 5% Trimmed Mean| 3. 36|

| Median| three or more. 00|

| Variance| 3. 024|

| Std. Deviation| 1 . 739|

| Minimum| 1|

| Maximum| 7|

| Range| 6|

| Interquartile Range| 3|

| Skewness|. 528|. 337

| Kurtosis| -. 723|. 662

Detailed statistics intended for Annual Credit rating Charged

Total annual Credit Charged| Statistic| An std. Error

| Mean| 3964. 06| 132. 016

| 95% Confidence Interval for Mean| Decrease Bound| 3698. 76| | | | Upper Bound| 4229. 36|

| 5% Trimmed Mean| 3971. 48|

| Median| 4090. 00|

| Variance| 871411. 200|

| An std. Deviation| 933. 494|

| Minimum| 1864|

| Maximum| 5678|

| Range| 3814|

| Interquartile Range| 1638|

| Skewness| --. 130|. 337

| Kurtosis| -. 742|. 662

To sum up 3 dining tables we get to know that the typical annual income of the households is usually 43. forty eight and the average household size is 3. 40 along with the normal amount recharged as 3964. With the 95% confidence period the suggest for all the three variables actually is easily predicted and the interval is definitely narrower. The variability from the indicate in the annual income is 211. 724 which tell us the risk received in the total annual...

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