AUTHOR – KHUSHI CHIKANE
1. INTRODUCTION –
The cosmetic and beauty industry is one of the fastest-growing consumer sectors, with increasing demand for makeup products globally. Consumers often compare makeup brands based on quality, durability, price, skin-compatibility, and overall satisfaction. To analyse whether significant differences exist in consumer ratings among four major makeup brands, a One-Way ANOVA test was conducted. This statistical method helps determine whether variations in user ratings are meaningful or due to random chance.
2. OBJECTIVE –
The objective of this study is to apply One-Way ANOVA to compare consumer ratings of four different makeup brands and determine if there is a statistically significant difference in their mean satisfaction scores.
3. LITERATURE REVIEW –
Nie (2019)
Nie’s research emphasizes how external market conditions, consumer behaviour, and organizational performance can influence variations within and between product categories. Although the focus is on technological organizations, the concept relates to cosmetics: changes in market trends and consumer expectations often affect brand performance and ratings.
Zhang & Chen (2014)
The study highlights the importance of resource allocation, product innovation, and quality consistency in maintaining competitive advantage. Makeup brands similarly differ in their formulation quality, pricing, marketing strategies, and customer loyalty—factors that may cause measurable statistical differences in consumer ratings.
4. DATA COLLECTION –
Data was collected through consumer surveys evaluating four makeup brands. Each brand received ratings from multiple respondents on a standardized 1–10 scale. A total of 160 observations were categorized into four groups (Lakme, Maybelline, L’Oreal Paris, MAC Cosmetics)
ANOVA was used to determine if these groups differ significantly.
- Sample Size (N) = 160
- Brands = 4
- Ratings included: quality, durability, smoothness, and user satisfaction.
5. DATA ANALYSIS –
The following ANOVA results were generated:
ANOVA Table
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
69.22 |
3.00 |
23.07 |
28.54 |
0.00 |
2.66 |
|
Within Groups |
126.13 |
156.00 |
0.81 |
|
|
|
|
|
|
|
|
|
|
|
|
Total |
195.34 |
159.00 |
|
|
|
|
Null hypothesis (H₀): The means of all groups are equal.
Alternative hypothesis (H₁): At least one group mean is different.
Since the p-value (0.00) is less than 0.05, the null hypothesis (H₀) is rejected and the alternative hypothesis (H₁) is accepted There is a statistically significant difference between the group means.
6. CONCLUSION –
The ANOVA results show that there is a significant difference in the mean ratings of the four makeup brands. The F-value is much larger than the F-critical value, and the p-value is far below 0.05. This indicates that the variation between the brands is not due to random chance but reflects real differences in consumer perceptions. Therefore, we reject the null hypothesis and conclude that at least one makeup brand is rated differently from the others.
7.REFERENCES –
Nie, X. (2019). Legal challenges of the Asia-Pacific Space Cooperation Organization in the context of the Belt and Road Initiative. Space Policy, 47, 1–7.
Zhang, H., & Chen, Y. (2014). Role of the Asia-Pacific Space Cooperation Organization in advancing space technology and its applications in the Asia-Pacific region. Advances in Space Research, 54(3), 403–409.