ANOVA Based Comparison Ratings for Cricketer’s Name Reviews
Siddhanth Satpute (021331025437)
Introduction
Cricket is one of the most followed sports, and cricketers often become public figures whose names evoke specific perceptions among listeners and fans. These perceptions may be influenced by factors such as performance, media coverage, popularity, and personal branding. Understanding how listeners rate different cricketers based on name recognition or reviews can provide insights into public opinion and brand value. Analysis of Variance (ANOVA) is a statistical technique that helps compare the mean ratings of more than two groups and determine whether any significant differences exist among them.
This study applies ANOVA to compare listeners’ ratings for different cricketers’ name reviews and to identify whether perceptions significantly differ across cricketers.
Objectives of the Study
1. To analyze listeners’ ratings given to different cricketers based on name reviews.
2. To compare the mean ratings of multiple cricketers using ANOVA.
3. To examine whether there is a statistically significant difference in listeners’ perceptions of cricketers.
4. To provide insights into public perception trends based on listener ratings.
Literature Review
Previous studies on sports marketing and athlete branding suggest that athletes’ names act as strong brand identifiers influencing fan perception (Arai et al., 2014). Research has shown that public opinion about sports personalities varies significantly due to performance consistency, media exposure, and personal image (Keller, 2013). Statistical tools such as ANOVA have been widely used in social science and sports research to compare group perceptions and ratings (Field, 2018). These studies support the use of ANOVA for comparing listener ratings across multiple athletes.
Data Collection
The data for this study is collected using a structured questionnaire (Google Form). Respondents are asked to rate selected cricketers based on name review or overall perception using a Likert scale (for example, 1 = Very Poor to 5 = Excellent).
• Population: Cricket listeners/fans
• Sample Size: (as per responses collected)
• Sampling Technique: Convenience sampling
• Type of Data: Primary data
Data Analysis
ANOVA
Source of Variation
SS
df
MS
F
P-value
F crit
Between Groups
44.94871795
3
14.98290598
2.766764272
0.043831904
2.664106703
Within Groups
823.1282051
152
5.415317139
Total
868.0769231
155
Hypothesis Testing
• Null Hypothesis (H₀): There is no significant difference in listeners’ mean ratings among different cricketers.
• Alternative Hypothesis (H₁): There is a significant difference in listeners’ mean ratings among different cricketers.
Decision Rule
At a 5% level of significance (α = 0.05):
• If the calculated p-value ≤ 0.05, reject the null hypothesis.
• If the calculated p-value > 0.05, fail to reject the null hypothesis.
Result
The ANOVA test produces an F-statistic and a corresponding p-value. Based on the comparison between the p-value and the significance level, the statistical decision is made regarding the null hypothesis.
Interpretation
If the null hypothesis is rejected, it indicates that listeners perceive at least one cricketer differently from others in terms of ratings. If the null hypothesis is not rejected, it suggests that listeners’ ratings do not significantly differ across cricketers.
Inference
The analysis provides evidence on whether listeners’ perceptions of cricketers’ name reviews are uniform or varied. Significant differences imply the influence of popularity, performance, or media presence on listener ratings.
Conclusion
The study demonstrates the usefulness of ANOVA in comparing listeners’ ratings for different cricketers. By statistically analyzing perceptions, the research helps understand how cricketers are viewed by the public. Such insights can be useful for sports marketers, brand managers, and media analysts in evaluating athlete branding and public image.
References
1. Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics. Sage Publications.
2. Keller, K. L. (2013). Strategic Brand Management. Pearson Education