Title: Actress talent rating.
Introduction: Good actress appear to become their characters to be real life. Every actress must master three fundamental skills in reels like developing characters, conveying emotion, projection and pronunciation.
Author: Disha Kshetija
Objective: To compare the four different actress skills in reels.
Data collection: The data collection from every individual participants provided ratings for Disha Patani, Kriti Sanon, Katrina Kaif, Deepika Padukone. Each rating was collected independently to reflect personal preferences, ensuring fans think about them, this data is being collected from the fans, how much do they support them.
Data analysis: The ratings were then compiled to analyze fans preferences using ANOVA: single factor, allowing for statistical evaluation of differences in actress skills.
The hypothesis for the test are:
- Null Hypothesis (H0): Its indicates all the Actress skills are the same.
- Alternative Hypothesis (H1): It indicate that at least one Actress skills is rated significantly different.
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Anova: Single Factor |
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SUMMARY |
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Groups |
Count |
Sum |
Average |
Variance |
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How would you rate Disha Patani |
25 |
150 |
6 |
10.526 |
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How would you rate Kriti Sanon |
25 |
126 |
5.04 |
10.937 |
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|
How would you rate Katrina Kaif |
25 |
164 |
6.56 |
6.800 |
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How would you rate Deepika Padukone |
25 |
115 |
4.6 |
8.408 |
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ANOVA |
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Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
77.2375 |
3 |
25.746 |
2.808 |
0.047 |
2.725 |
|
Within Groups |
696.75 |
76 |
9.168 |
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Total |
773.9875 |
79 |
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Since the P-value is 0.047 is less than the significance level of 0.05, we accept the Alternative Hypothesis.
Conclusion:
The ANOVA: single factor analysis yielded a P-value less than 0.05, leading to rejecting the Null Hypothesis. This confirms that at least one — Disha Patani, Kriti Sanon, Katrina Kaif, Deepika Padukone —has a significantly different preference level among respondents.