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.
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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