A Comparative Statistical Analysis of Car Brands
Author: Praful Uttareshwar Landge
Introduction:
The automobile industry is one of the most competitive industries, where consumer ratings and perceptions play a major role in evaluating the success of car brands. Customers often judge car brands based on quality, reliability, design, performance, affordability, and brand image. Studying the ratings of different car brands helps in understanding their comparative popularity and market perception.
Beyond product features, a brand’s success is also influenced by customer trust, after-sales service, and overall market reputation. This study examines the perceived performance of major car brands and how they are rated by respondents.
Objective:
To analyze the ratings of car brands using One-Way ANOVA in order to determine whether significant differences exist among them.
Literature review:
Consumer Preference and Brand Perception
Kotler and Keller (2016) explain that consumer buying behavior is highly influenced by brand image, perceived quality, and trust. In the automobile industry, customers evaluate car brands not only based on features and price but also on long-term reliability and reputation. The study suggests that brands with stronger customer satisfaction and loyalty often receive higher ratings.
Comparative Methodology and Statistical Modeling
Sharma and Jain (2021) discuss the use of statistical techniques to examine customer preferences in the automobile industry. This review explains how ANOVA can be used to compare the ratings of different car brands and determine whether the differences in consumer perception are statistically significant. The study suggests that established brands may receive higher mean ratings, while customer opinions may vary depending on performance, affordability, and brand value.
Data collection:
The data for this study was collected using primary research methods via a structured survey distributed through Google Forms. A total of 30 responses were recorded. Participants were asked to rate the car brands—Mahindra, Tata Motors, Hyundai, and Maruti Suzuki—on a scale of 1 to 10 based on their overall performance, design, reliability, and brand reputation, and a One-Way ANOVA was calculated on the compiled data.
Data Analysis:
Anova: Single Factor
SUMMARY
|
Groups |
Count |
Sum |
Average |
Variance |
|
Mahindra |
30 |
252 |
8.4 |
4.317241 |
|
Tata Motors |
30 |
187 |
6.233333 |
6.874713 |
|
Hyundai |
30 |
234 |
7.8 |
3.131034 |
|
Maruti Suzuki |
30 |
212 |
7.066667 |
3.374713 |
ANOVA
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
81.49167 |
3 |
27.16389 |
5.830052 |
0.000995 |
2.682809 |
|
Within Groups |
540.4 |
116 |
4.658621 |
|
|
|
|
Total |
621.8917 |
119 |
|
|
|
|
H0: Mahindra = Tata Motors = Hyundai = Maruti Suzuki
H1: Any one of them is different.
Conclusion:
As calculated, F (5.830052) is more than F crit (2.682809). Accept H1, meaning any one of them is different.
Reference:
Kotler, P., & Keller, K. L. (2016). Marketing Management (15th ed.). Pearson Education.
Sharma, R., & Jain, S. (2021). Consumer perception and statistical analysis of automobile brands in India. International Journal of Marketing and Consumer Research, 8(2), 45–53.