956 Words4 Pages

Overview I
This paper will evaluate a sample of 50 AJ DAVIS department store chain credit customers using statistical analysis. Four quantitative methods: household size, income, years and credit balance along with one qualitative method: location will be used. Individual Variables II
Location is a categorical variable and it consists of three (3) subcategories: Rural, Suburban and Urban. The below frequency distribution and bar graft indicates that the highest member of AJ DAVIS department store chain consumes resides in urban areas accounting for 44% of the sample, the second highest member of AJ DAVIS department store chain consumes resides in Suburban areas and accounts for 30% of the sample while the smallest number*…show more content…*

Descriptive Statistics: Income ($1000), Size, Credit Balance ($) Variable Mean StDev Minimum Median Maximum Range Mode Income ($1000) 43.74 14.64 21.00 43.00 67.00 46.00 55 Size 3.420 1.739 1.000 3.000 7.000 6.000 2 Credit Balance($) 3976 932 1864 4090 5678 3814 3890 Variable Mode Skewness Kurtosis Income ($1000) 4 0.05 -1.29 Size 15 0.53 -0.72 Credit Balance($) 2 -0.14 -0.74 The statistics indicates that the mean income is 43.74; the median income is 43.00 and the mode income is 55. The standard deviation is given approximately as 1.74. Maximum income is 67,000 and the minimum income is 21,000 and a Standard Deviation of 14.64. The second individual variable is household size the mean household size of the sample is 3.42, the median household size of the sample is 3 and the mode household size of the sample is 2 and the standard deviation is 1.739. The maximum household size is 7 and the minimum household size is*…show more content…*

The standard deviation is 932 and minimum and maximum credit balances are 1864 and 5678 respectively. Relationships III The four more significant relationships from this sample are: Income and Credit Balance, Income and Household Size along with Years and Credit Balance. The bivariate relationship between income and credit balance is reflected in the below scatter gram /scatterplot that reflects a clear and definite linear positive relationship/correlation between income and credit balance, indicating that the higher the income, the higher the credit balance will be and vice versa. The below scatterplot indicates that there is no definite relationship between Income and household size. The points on the scatter plot seems random and do not reflect a clear pattern indicating that there is no correlation among the variables Income and Size The below scatter plot indicates that there is no relationship between years and credit balance, the scatter plot does not reflect a clear pattern indicating that there is there is correlation among the variables Years and Credit

Descriptive Statistics: Income ($1000), Size, Credit Balance ($) Variable Mean StDev Minimum Median Maximum Range Mode Income ($1000) 43.74 14.64 21.00 43.00 67.00 46.00 55 Size 3.420 1.739 1.000 3.000 7.000 6.000 2 Credit Balance($) 3976 932 1864 4090 5678 3814 3890 Variable Mode Skewness Kurtosis Income ($1000) 4 0.05 -1.29 Size 15 0.53 -0.72 Credit Balance($) 2 -0.14 -0.74 The statistics indicates that the mean income is 43.74; the median income is 43.00 and the mode income is 55. The standard deviation is given approximately as 1.74. Maximum income is 67,000 and the minimum income is 21,000 and a Standard Deviation of 14.64. The second individual variable is household size the mean household size of the sample is 3.42, the median household size of the sample is 3 and the mode household size of the sample is 2 and the standard deviation is 1.739. The maximum household size is 7 and the minimum household size is

The standard deviation is 932 and minimum and maximum credit balances are 1864 and 5678 respectively. Relationships III The four more significant relationships from this sample are: Income and Credit Balance, Income and Household Size along with Years and Credit Balance. The bivariate relationship between income and credit balance is reflected in the below scatter gram /scatterplot that reflects a clear and definite linear positive relationship/correlation between income and credit balance, indicating that the higher the income, the higher the credit balance will be and vice versa. The below scatterplot indicates that there is no definite relationship between Income and household size. The points on the scatter plot seems random and do not reflect a clear pattern indicating that there is no correlation among the variables Income and Size The below scatter plot indicates that there is no relationship between years and credit balance, the scatter plot does not reflect a clear pattern indicating that there is there is correlation among the variables Years and Credit

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