Title : A Comparative Statistical Analysis of Subcompact SUVs.
Author : Vinayak Sunil Kale – 73
Introduction :
The subcompact SUV segment has gained significant popularity among consumers due to its affordability, fuel efficiency, compact design, and modern features. These vehicles are widely preferred in urban environments where space constraints and cost considerations play an important role. Consumer perception of different SUV brands is influenced by factors such as performance, mileage, design, safety, and brand reputation. This study evaluates the ratings of major subcompact SUVs to understand differences in consumer preferences and perceived value.
Objective :
To analyze the ratings of subcompact SUVs using one-way ANOVA in order to determine whether statistically significant differences exist among them.
Literature Review:
1) Consumer Preference and Automobile Choice
Sharma and Singh (2020) state that consumer preferences in automobiles are influenced by factors like price, brand image, fuel efficiency, and features. The study highlights the growing demand for compact SUVs due to their affordability and balanced performance, and notes that ratings differ across brands, making ANOVA useful for analysis (Sharma and Singh, 2020).
2) Statistical Analysis in Automobile Research
Patil and Deshmukh (2021) explain that one-way ANOVA is an effective tool for comparing multiple automobile brands and identifying differences in customer satisfaction. The study also notes that consistent brands tend to have higher average ratings with lower variation (Patil and Deshmukh, 2021).
Data Collection:
The data for study was collected using primary research through a structured questionnaire distributed via Google Forms. A total of 30 responses were obtained. Participants were asked to rate selected subcompact SUVs (such as Tata Nexon, Maruti Suzuki Brezza, Hyundai Venue, and Kia Sonet) on a scale of 1 to 10 based on factors like performance, features, design, and value for money. The collected data was then analyzed using one-way ANOVA to compare the ratings.
Data Analysis :
Hypothesis:
- H₀: Tata Nexon = Maruti Suzuki Brezza = Hyundai Venue = Kia Sonet
- H₁ : Any one of them is different.
|
SUMMARY |
|
|
|
|
|
Groups |
Count |
Sum |
Average |
Variance |
|
Tata Nexon |
30 |
244 |
8.1333 |
2.3264 |
|
Maruti Suzuki Brezza |
30 |
224 |
7.4667 |
1.5678 |
|
Hyundai Venue |
30 |
246 |
8.2 |
2.0276 |
|
Kia Sonet |
30 |
234 |
7.8 |
2.4414 |
|
ANOVA |
|
|
|
|
|
|
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
10.2667 |
3 |
3.4222 |
1.6368 |
0.1847 |
2.6828 |
|
Within Groups |
242.5333 |
116 |
2.0908 |
|
|
|
|
|
|
|
|
|
|
|
|
Total |
252.8 |
119 |
|
|
|
|
Conclusion :
Since, the p-value (0.1847) is greater than 0.05 and the F-value (1.6368) is less than the F crit (2.6828), accept H₀ and reject H₁, meaning there is no statistically significant difference in the average ratings of Tata Nexon, Maruti Brezza, Hyundai Venue, and Kia Sonet.
References :
1) Sharma, R., & Singh, A. (2020). Consumer buying behavior towards passenger cars in India. International Journal of Marketing Studies, 12(3), 45–60.
2) Patil, V., & Deshmukh, S. (2021). Application of statistical tools in automobile industry analysis. Journal of Business Analytics, 8(2), 101–115.