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Statistical analysis of discrete and continuous variables using t-test and chi-square

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Essay 661 words

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

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 * Wealthrating

19.716

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

NumberOfCars * Lengthofresidence

46,4%

53,7%

2000

100,0%

NumberOfCars * Athleticdimension

46,4%

53,7%

2000

100,0%

NumberOfCars * Wealthrating

11,0%

89,0%

2000

100,0%

NumberOfChildren * Lengthofresidence

2000

100,0%

0

0,0%

2000

100,0%

NumberOfChildren * Athleticdimension

2000

100,0%

0

0,0%

2000

100,0%

NumberOfChildren * Wealthrating

25,4%

74,7%

2000

100,0%

MailBuyer * Lengthofresidence

2000

100,0%

0

0,0%

2000

100,0%

MailBuyer * Athleticdimension

2000

100,0%

0

0,0%

2000

100,0%

MailBuyer * Wealthrating

25,4%

74,7%

2000

100,0%

NumberOfCars * Lengthofresidence

Chi-Square Tests

Value

df

Asymp. 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 expected count is 3,24.

MailBuyer * Athleticdimension

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

24,293a

2

,000

Likelihood Ratio

25,629

2

,000

N of Valid Cases

2000

a. 0 cells (0,0%) have expected count less than 5. The minimum expected count is 42,83.

MailBuyer * Wealthrating

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

19,716a

16

,233

Likelihood Ratio

18,676

16

,286

Linear-by-Linear Association

3,861

1

,049

N of Valid Cases

a. 11 cells (40,7%) have expected count less than 5. The minimum expected count is,45.

108 Words Hidden
T-Test108 words
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…
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PaperDue. (2016). Statistical analysis of discrete and continuous variables using t-test and chi-square. PaperDue. https://www.paperdue.com/essay/statistical-analysis-and-variables-2161841

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