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Statistical Analysis of the Sample Data
Identification of Discreet Variables and Continuous Variables
A discrete variable is obtained by counting, and the continuous variable is obtained by measuring. The study selects the following discreet variables for the analysis:
• Number of cars
• Number of Children
• Mail Buyer
The study also selects the following continuous variables for the analysis:
• Length of residence
• Athletic Dimension
• Wealth Rating.
Numerical Distribution of Discreet and Continuous Variable
The study uses the frequency distribution to compare the selected discreet and continuous variables using the central tendency tools and graph. As being revealed in the frequency table below, THE variables Lengthofresidence and Athleticdimension do not have the mean values showing the limitation of the data.
Frequencies
Comparison of Discreet and Continuous Variables
MailBuyer
LengthOfResidence
AthleticDimension
WealthRating
N
Valid
2000
2000
2000
2000
Missing
0
0
0
0
Mean
1,03
0,59
1,25
7,39
Median
1
0
1
8
Mode
1
0
2
9
The bar graph of all the six variables are presented below
Bar Graph
T-Test
The section presents the T-Test for the discreet and continuous variables. The p-value of the sample four populations is 0 revealing that the difference between the four means of the sample population is not statistically significant. While the T-test presents the results of four variables, the results of variables Length of residence and Athletic Dimension are missing because of the missing values. Thus, the missing values have affected the reliability and validity of tests of differences and statistical estimations.
One-Sample Statistics
N
Mean
Std. Deviation
Std. Error Mean
1,03
1,056
,035
2000
,59
1,020
,023
MailBuyer
2000
1,25
,808
,018
WealthRating
7,39
1,703
,076
One-Sample Test
Test Value = 0
t df
Sig. (2-tailed)
Mean Difference
95% Confidence Interval of the Difference
Lower
Upper
29,742
0
1,031
0,96
1,1
25,684
1999
0
0,586
0,54
0,63
MailBuyer
69,395
1999
0
1,254
1,22
1,29
WealthRating
97,762
0
7,393
7,24
7,54
Chi Square
The study also presents the chi-square of all the six variables. The results of the chi-square show that there is a statistically significant association between Numberofcars and Lengthofresidence because their chi-square is 115,441. As being revealed in the table below, the chi-squares of all the variable relationships are statistically significant. However, lots of missing values in some of the variables affect the validity and reliability of the results.
Variables Relationships
Pearson chi square
NumberOfCars and Lengthofresidence
115,441.
NumberOfCars and Athleticdimension
2.704
NumberOfCars * Wealthrating
27.960
NumberOfChildren * Lengthofresidence
NumberOfChildren * Athleticdimension
30.089
NumberOfChildren * Wealthrating
27.683
MailBuyer * Lengthofresidence
MailBuyer * Athleticdimension
24.293
MailBuyer...
Sig. (2-sided)
Pearson Chi-Square
115,441a
,779
Likelihood Ratio
109,747
,877
N of Valid Cases
a. 108 cells (70,6%) have expected count less than 5. The minimum expected count is,00.
NumberOfCars * Athleticdimension
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
2,704a
8
,952
Likelihood Ratio
3,590
8
,892
N of Valid Cases
a. 9 cells (50,0%) have expected count less than 5. The minimum expected count is,10.
NumberOfCars * Wealthrating
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
27,960a
36
,829
Likelihood Ratio
30,852
36
,712
Linear-by-Linear Association
,000
1
,989
N of Valid Cases
a. 39 cells (79,6%) have expected count less than 5. The minimum expected count is,02.
NumberOfChildren * Lengthofresidence
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
114,259a
96
,099
Likelihood Ratio
100,816
96
,348
N of Valid Cases
2000
a. 65 cells (54,6%) have expected count less than 5. The minimum expected count is,01.
NumberOfChildren * Athleticdimension
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
30,089a
6
,000
Likelihood Ratio
27,253
6
,000
N of Valid Cases
2000
a. 4 cells (28,6%) have expected count less than 5. The minimum expected count is,09.
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
27,683a
40
,930
Likelihood Ratio
33,030
40
,775
Linear-by-Linear Association
2,920
1
,088
N of Valid Cases
a. 34 cells (63,0%) have expected count less than 5. The minimum expected count is,02.
MailBuyer * Lengthofresidence
Chi-Square Tests
Value
df
Asymp. Sig. (2-sided)
Pearson Chi-Square
305,292a
32
,000
Likelihood Ratio
300,791
32
,000
N of Valid Cases
2000
a. 2 cells (3,9%) have expected count less than 5. The minimum…
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