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Output based on different Classes.

Output based on different types of Students.

Analysis based on different types of students.

Output based on marks of class for different types of students.

Analysis based on marks of class for different types of students.

Research Objectives

The Automobile association has been facing problems in targeting the population group to whom which brand of car should be more advertised. The taste and preferences of the people differ with different age group, income and education. Thus, the company wanted to analyse the demand for the luxury cars in the households considering the factors such as age, income and years of education. The main aim of this research will be to identify how each of the considered attributes such as age, income and education of the buyers of luxury cars define their preferences towards any particular brands. The customer profile information will be useful for the association to analyse their demands so that they can come up with some strategies to sell the cars to the potential buyers and attract new customers as well.

The business problem that has been discussed already needs to be evaluated with the help of the application of appropriate statistical techniques and interpretation of the results as well. Measures of shape and location will be used to determine the shape of the distribution of the profiles of the customers. The Association is also interested to know the differences in the age, annual income and years of education of the buyers of the different brands of cars. Appropriate testing strategies will be used in order to test these differences. The preference of the brands of the luxury cars with respect to the influence of age, education and annual income of the customers will be evaluated with the help of logistic regression technique.

It can be seen from table that in the lower age group of 35 – 44 years, preference of people is more towards BMW rather than Lexus and Mercedes, in the age group of 45 – 54 years, people can be seen to be preferring Lexus and between 55 – 64 years, people mostly prefer Mercedes. Thus, it can be said that the older people are more likely to prefer Mercedes than BMW or Lexus and the Younger People are more likely to prefer BMW over Mercedes and Lexus. Lexus is preferred by the middle aged people mostly.

Table 1: Preference of Luxury Cars with respect to Age Groups

Car Type and Age

Car Types

Age Group (In Years)

BMW

Lexus

Mercedes

Grand Total

35-44

58

20

24

102

45-54

66

82

74

222

55-64

6

34

50

90

65-74

4

2

6

Grand Total

130

140

150

420

It can be seen that the average age of the people preferring BMW cars is 45.22 years, preferring Lexus cars is 50.46 years and preferring Mercedes cars is 51.99 years. It can also be seen that the standard deviation of the ages of the people preferring the three types of cars namely BMW, Lexus and Mercedes are 4.4 years, 6.1 years and 6.7 years respectively, which can be said as very low deviations. Thus, it can be said that the ages of the people preferring these types of cars are close to the average ages. Moreover, the mean, median and the mode of the ages are quite close to each other. Thus, the distribution of the ages of the three types of car users can be said to be symmetrically distributed. These has also been illustrated with the help of histograms provided in figures 2, 3 and 4.  

Table 2: Descriptive Summary of Ages

 

BMW

Lexus

Mercedes

Mean

45.22

50.46

51.99

Standard Error

0.38

0.52

0.55

Median

45

50

53

Mode

46

55

53

Standard Deviation

4.4

6.1

6.7

Sample Variance

18.96

37.2

45.44

Kurtosis

0.05

0.61

-0.02

Skewness

0.51

0.36

-0.03

Range

21

32

35

Minimum

36

36

35

Maximum

57

68

70

Sum

5878

7064

7798

Count

130

140

150

Methodology

It can be seen from table 3 that the people preferring Mercedes belong to higher income group. The people of the lower income group can be seen to be preferring BMW cars over Lexus and Mercedes. Lexus cars are preferred mostly by people who belong to an average income group.

Table 3: Preference of Luxury Cars with respect to Income Groups

Car Type and Annual Income

Car Types

Annual Income (in $)

BMW

Lexus

Mercedes

Grand Total

45000-74999

2

2

4

75000-104999

16

4

2

22

105000-134999

38

38

16

92

135000-164999

44

48

38

130

165000-194999

26

40

36

102

195000-224999

4

4

28

36

225000-254999

6

20

26

255000-284999

4

4

285000-314999

2

2

315000-344999

2

2

Grand Total

130

140

150

420

It can be seen that the average income of the people preferring BMW cars is $139,271.3, preferring Lexus cars is $154,186.9 and preferring Mercedes cars is $184,423.9. It can also be seen that the standard deviation of the income of the people preferring the three types of cars namely BMW, Lexus and Mercedes are $2,907.85, $2,556.43 and $3,845.33 respectively, which can be said as very low deviations compared to the average income. Thus, it can be said that the income of the people preferring these types of cars are close to the average income. Moreover, the mean, median and the mode of the incomes of the individuals preferring different type of cars are quite close to each other. Thus, the distribution of the income of the three types of car users can be said to be symmetrically distributed. These has also been illustrated with the help of histograms provided in figures 6, 7 and 8.

Table 4: Descriptive Summary of Annual Income

 

BMW

Lexus

Mercedes

Mean

139271.3

154186.9

184423.9

Standard Error

2907.846

2556.425

3845.333

Median

138512

154492

186070

Mode

109568

179617

161590

Standard Deviation

33154.54

30248.02

47095.52

Sample Variance

1.1E+09

9.15E+08

2.22E+09

Kurtosis

-0.22439

0.963641

0.987178

Skewness

-0.03855

0.693685

0.273966

Range

170652

152065

284882

Minimum

46068

96069

49941

Maximum

216720

248134

334823

Sum

18105274

21586160

27663592

Count

130

140

150

It can be seen from table 5 that in the lower education group of 11 – 13 years, preference of people is more towards Lexus rather than BMW and Mercedes, in the education group of 14 – 16 years, people can be seen to be preferring BMW and between 17 – 22 years, people mostly prefer Mercedes. Thus, it can be said that the people with higher education are more likely to prefer Mercedes than BMW or Lexus and the people with lower income groups are more likely to prefer Lexus over Mercedes and BMW. BMW is preferred by the mostly by the people with 14 – 16 years of education.

Table 5: Preference of Luxury Cars with respect to Years of Education

Car Type and Education

Car Types

Education (in Years)

BMW

Lexus

Mercedes

Grand Total

11-13

12

34

2

48

14-16

66

52

38

156

17-19

52

44

94

190

20-22

10

16

26

Grand Total

130

140

150

420

It can be seen that the average years of education the people preferring BMW cars is 15.8 years, preferring Lexus cars is 15.8 years and preferring Mercedes cars is 17.3 years. It can also be seen that the standard deviation of the years of education of the people preferring the three types of cars namely BMW, Lexus and Mercedes are 1.8 years, 2.4 years and 1.7 years respectively, which can be said as very low deviations. Thus, it can be said that the years of education of the people preferring these types of cars are close to the average years of education. Moreover, the mean, median and the mode of the years of education are quite close to each other for each of the car types. Thus, the distribution of the years of education of the three types of car users can be said to be symmetrically distributed. These has also been illustrated with the help of histograms provided in figures 10, 11 and 12.

Table 6: Descriptive Summary of Years of Education

 

BMW

Lexus

Mercedes

Mean

15.83077

15.8

17.29333

Standard Error

0.160923

0.20407

0.142067

Median

16

16

17

Mode

16

16

17

Standard Deviation

1.834799

2.414584

1.739963

Sample Variance

3.366488

5.830216

3.027472

Kurtosis

-0.17288

-0.97728

0.039633

Skewness

-0.4345

0.16972

0.081676

Range

8

9

9

Minimum

11

12

13

Maximum

19

21

22

Sum

2058

2212

2594

Count

130

140

150

Analysis of Age Group Preferences

In order to check independency of average ages of buyers of belonging to groups of three different luxury cars, hypothesis testing needs to be done. The most significant statistical tool for analyzing mean ages of three different group the test of Analysis of Variance or ANOVA.

The null and alternative hypothesis for the specific ANOVA test is given as follows.

Null hypothesis: Average ages of buyers of three different groups are equal.

Alternative Hypothesis: Average ages of buyers are significantly different.

Result of the ANOVA test is produced below.

Table 7: ANOVA test result for independency of average ages

Groups

Count

Sum

Average

Variance

BMW

130

5878

45.21538

18.961

Lexus

140

7064

50.45714

37.19959

Mercedes

150

7798

51.98667

45.43606

Source of Variation

SS

df

MS

F

P-value

F crit

Between Groups

3436.362

2

1718.181

49.802

0.000

3.017

Within Groups

14386.69

417

34.500

Total

17823.05

419

Decision rule of the ANOVA test indicates that the null hypothesis is rejected at 5% level of significance if the estimated value F exceeds the tabulated value. The estimated F value of the given test is obtained as 49.8. The critical F value or tabulated F value is given as 3.017. As the estimated F value exceeds the critical F value, null hypothesis is rejected.  It can thus be said that average ages of buyers of three groups are not equal. The mean ages differ significantly among the three groups.

In order to check independency of average income of buyers of belonging to groups of three different luxury cars, hypothesis testing needs to be done. The most significant statistical tool for analyzing mean incomes of three different group the test of Analysis of Variance or ANOVA.

The null and alternative hypothesis for the specific ANOVA test is given as follows.

Null hypothesis: Average income of buyers of three different groups are equal.

Alternative Hypothesis: Average income of buyers are significantly different.

Result of the ANOVA test is produced below.

Table 8: ANOVA test result for independency of average income

Groups

Count

Sum

Average

Variance

BMW

130

18105274

139271.3

1.1E+09

Lexus

140

21586160

154186.9

9.15E+08

Mercedes

150

27663592

184423.9

2.22E+09

Source of Variation

SS

df

MS

F

P-value

F crit

Between Groups

1.5E+11

2

7.5E+10

52.176

0.000

3.017

Within Groups

5.99E+11

417

1.44E+09

Total

7.49E+11

419

Decision rule of the ANOVA test indicates that the null hypothesis is rejected at 5% level of significance if the estimated value F exceeds the tabulated value. The estimated F value of the given test is obtained as 52.18. The critical F value or tabulated F value is given as 3.017. As the estimated F value exceeds the critical F value, null hypothesis is rejected.  It can thus be said that average income of buyers of three groups are not equal. The mean incomes differ significantly among the three groups.

In order to check independency of average years of education of buyers of belonging to groups of three different luxury cars, hypothesis testing needs to be done. The most significant statistical tool for analyzing mean education years of three different group the test of Analysis of Variance or ANOVA.

The null and alternative hypothesis for the specific ANOVA test is given as follows.

Null hypothesis: Average education years of buyers of three different groups are equal.

Alternative Hypothesis: Average education years of buyers are significantly different.

Result of the ANOVA test is produced below.

Table 9: ANOVA test result for independency of average education years

Groups

Count

Sum

Average

Variance

BMW

130

2058

15.83077

3.366488

Lexus

140

2212

15.8

5.830216

Mercedes

150

2594

17.29333

3.027472

Source of Variation

SS

df

MS

F

P-value

F crit

Between Groups

210.858

2

105.429

25.926

0.000

3.017

Within Groups

1695.770

417

4.067

 

Total

1906.629

419

Decision rule of the ANOVA test indicates that the null hypothesis is rejected at 5% level of significance if the estimated value F exceeds the tabulated value. The estimated F value of the given test is obtained as 25.93. The critical F value or tabulated F value is given as 3.017. As the estimated F value exceeds the critical F value, null hypothesis is rejected.  It can thus be said that average education years of buyers of three groups are not equal. The mean education years differ significantly among the three groups.

Some dealers claim that there is a higher chance of buying Mercedes cars in case of buyers with higher age, higher income and higher years of education. To verify this claim regression analysis needs to be done. The simple linear regression however cannot be done here because of categorical nature of the dependent variable. For this, logistic regression has been done. The dependent variable takes two values 0 and 1. 1 represents probability of buying Mercedes and 0 represents probability of buying Lexus or Mercedes.

The table below represents proportion of samples choosing Mercedes and other two types of cars.

Table 10: Proportion of choosing Mercedes and two other types of cars

 

Suc-Obs

Fail-Obs

Total

Suc-Pred

88

26

114

Fail-Pred

62

244

306

Total

150

270

420

In the selected sample group, among the 420 household 150 are buying Mercedes and 270 are buying BMW or Mercedes. That is in chosen sample, 35.7% are preferring Mercedes over BMW or Lexus.

The result of logistic regression is given in the following table:

Table 11: Logistic Regression Coefficients

 

coeff b

s.e.

Wald

p-value

exp(b)

lower

upper

Intercept

-14.857

1.677

78.523

0.000

0.000

Age (Years)

0.098

0.020

24.641

0.000

1.103

1.061

1.146

Annual Income ($)

0.000

0.000

47.145

0.000

1.000

1.000

1.000

Education (Years)

0.326

0.064

26.170

0.000

1.386

1.223

1.570

From the regression result the estimated regression equation is obtained as:

From regression table coefficient of all the independent variables are found to be positive. This implies that with increase in each of the independent variable the probability of buying Mercedes cars increases. P values corresponding to all the independent variables are 0.000. The p value lower than the significance level indicates rejection of null hypothesis stating no significant relation between the dependent and independent variables. The regression result thus supports the claim that older people who has higher income and more years of education tend to buy Mercedes cars.

Conclusion

The analysis conducted so far in this research paper indicates that the people with lower age groups prefer BMW and higher age groups prefer Mercedes cars. People having higher income prefer Mercedes whereas with lower income prefer BMW. The people with lower years of education prefer Lexus cars whereas with higher years of education prefer BMW vars. Thus, it can be concluded that older people with higher income group and higher years of education prefer Mercedes over other car types. Significant differences have also been observed in the average ages, average income and average years of education for the three different car types. Further, it has also been observed that the preference of Mercedes cars is positively influenced by the attributes such as age, income and years of education.

The information obtained so far can be used to determine the marketing strategy for the Automobile association. The advertisement for the different types of cars can be targeted to different people belonging to different customer profile. Mercedes cars can be shown to older people with higher income and higher education years. They will be more likely to buy the car. The middle aged people must be given preference for selling of Lexus and BMW cars.

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My Assignment Help (2020) Demand Analysis Of Luxury Cars Based On Age, Income, And Education In An Essay. [Online]. Available from: https://myassignmenthelp.com/free-samples/econ940-statistics-for-decision-making/business-problem.html
[Accessed 22 December 2024].

My Assignment Help. 'Demand Analysis Of Luxury Cars Based On Age, Income, And Education In An Essay.' (My Assignment Help, 2020) <https://myassignmenthelp.com/free-samples/econ940-statistics-for-decision-making/business-problem.html> accessed 22 December 2024.

My Assignment Help. Demand Analysis Of Luxury Cars Based On Age, Income, And Education In An Essay. [Internet]. My Assignment Help. 2020 [cited 22 December 2024]. Available from: https://myassignmenthelp.com/free-samples/econ940-statistics-for-decision-making/business-problem.html.

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