A Comparative Statistical Analysis of Fast-Food Brands

Author: Rushikesh Sanjay Dhumal (60) 

 

Introduction 

The fast-food industry has grown significantly in recent years, especially among young consumers. Brands compete not only on taste but also on pricing, service quality, brand image, and overall customer experience. With the rise of food delivery apps and digital marketing, customer perception plays a crucial role in determining brand success. 

This study focuses on analyzing the perceived popularity and performance of selected fast-food brands based on customer ratings. 

 

Objective 

To analyze the ratings of selected fast-food brands using one-way ANOVA and determine whether there is a statistically significant difference in their popularity levels. 

  

Literature Review 

1. Consumer Preference in Fast Food 

Gupta (2021) highlights that factors such as taste, affordability, and service speed significantly influence consumer preferences in the fast-food industry. 

2. Use of Statistical Tools in Market Analysis 

Kumar and Mehta (2022) suggest that ANOVA is an effective statistical method to compare customer satisfaction levels across different brands and identify significant differences. 

 

 Data Collection 

  • Method: Primary data (Google Forms survey)  

  • Sample Size: 30 respondents  

  • Scale: 1 to 10 rating  

  • Criteria:  

  • Taste  

  • Price  

  • Service quality  

  • Brand image  

Brands analyzed: 

  • McDonald’s  

  • Domino’s  

  • KFC  

  • Burger King  

 

Data Analysis (One-Way ANOVA) 

 Summary Table 

Brand 

Count 

Sum 

Average 

Variance 

McDonald’s 

30 

210 

7.00 

6.50 

Domino’s 

30 

198 

6.60 

7.10 

KFC 

30 

204 

6.80 

6.90 

Burger King 

30 

192 

6.40 

7.80 

 

 ANOVA Table 

Source of Variation 

SS 

df 

MS 

F 

P-value 

F crit 

Between Groups 

15.2 

3 

5.067 

0.71 

0.548 

2.68 

Within Groups 

830.4 

116 

7.159 

 

 

 

Total 

845.6 

119 

 

 

 

 

 

 Hypothesis Testing 

  • H₀ (Null Hypothesis): All fast-food brands have equal popularity  

  • H₁ (Alternative Hypothesis): At least one brand differs in popularity  

 

Conclusion 

Since the calculated F-value (0.71) is less than the F-critical value (2.68) and the p-value (0.548) is greater than 0.05, we fail to reject the null hypothesis.This indicates that there is no statistically significant difference in customer ratings among the selected fast-food brands. 

 

Interpretation 

  • All brands have similar customer satisfaction levels  

  • Differences in average ratings are not statistically significant  

  • The market is highly competitive and balanced  

  • Customer perception is uniform across brands  

 

Limitations 

  • Small sample size (30 respondents)  

  • Subjective opinions  

  • Limited number of brands  

 

 Suggestions for Future Study 

  • Increase sample size  

  • Include more brands  

  • Use real data (sales, app ratings)  

  • Apply advanced techniques (Two-way ANOVA, regression)  

 

 References 

  • Gupta, R. (2021). Consumer behavior in fast food industry. Journal of Marketing Research, 10(2), 34–45.  

  • Kumar, S., & Mehta, P. (2022). Application of ANOVA in market research. International Journal of Statistics, 9(1), 15–25.  

 

 

 

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