Title- AI Tools Preference Survey Using ANOVA: Single Factor
Author- Harshit Dubey.
Introduction–
AI tools play a crucial role in automating tasks, enhancing decision-making, and improving efficiency across various industries. They analyze large datasets, recognize patterns, and make predictions, helping businesses optimize processes and reduce human error. AI tools also enable natural language processing, image recognition, and personalized recommendations, transforming user experiences in sectors like healthcare, finance, and customer service. Their adaptability allows them to assist in both routine and complex tasks, driving innovation and productivity.
AI Tools preference attracts different levels of interest among audiences. This report focuses on understanding the preferences of students at ITM Business School by analysing their ratings for four major AI Tools preference. A statistical method, ANOVA: Single Factor, is used to determine if there is a significant difference in the ratings given to these AI Tools.
Objective-To find out if there are significant differences in the preferences (ratings) of ITM students for the AI Tools
Data Collection: Students of ITM Business School were surveyed. Each student rated four AI Tools preference i.e. ChatGPT, Gemini, Quil Bolt, Copilot on a scale of 1 to 10, were 1 indicates low preference and 10 indicates high preference. The ratings for each genre were recorded for analysis.
Data Analysis-
The ANOVA: Single Factor test was performed to compare the means of the ratings across the four AI Tools.
The hypotheses for the test are:
- Null Hypothesis (H0): There is no significant difference in the average ratings of ChatGPT, Gemini, Quil Bolt, Copilott.
- Alternate Hypothesis (H1) At least one of the AI Tools has a significantly different average rating.
The results of the ANOVA: Single Factor test are as follows:
|
Anova: Single Factor |
||||||
|
SUMMARY |
||||||
|
Groups |
Count |
Sum |
Average |
Variance |
||
|
chatgpt |
25 |
224 |
8.96 |
0.54 |
||
|
gemini |
25 |
202 |
8.08 |
0.66 |
||
|
quil bolt |
25 |
181 |
7.24 |
1.523333 |
||
|
copilot |
25 |
198 |
7.92 |
2.41 |
||
|
ANOVA |
||||||
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
37.55 |
3 |
12.51667 |
9.753247 |
1.11846E-05 |
2.699393 |
|
Within Groups |
123.2 |
96 |
1.283333 |
|||
|
Total |
160.75 |
99 |
|
|
|
|
|
|
||||||
Since the p-value (1.118465) is greater than the standard significance level of 0.05, we accept the null hypothesis.
Conclusion: There is no significant difference in the AI Tools ratings given by the ITM students
Author– Shrushtii Rathi.
Introduction–
Bollywood actresses are central figures in India’s film industry, known for their talent, beauty, and versatility. They bring life to diverse roles, from traditional and cultural characters to modern, globalized personas, contributing to the massive appeal of Indian cinema. Actresses like Deepika Padukone, Priyanka Chopra, Alia Bhatt, and Kareena Kapoor have achieved both critical acclaim and commercial success. Many Bollywood actresses also use their influence to advocate for social causes, expanding their impact beyond films into areas like women’s empowerment, mental health, and environmental activism.
Actresses preference attracts different levels of interest among audiences. This report focuses on understanding the preferences of students at ITM Business School by analysing their ratings for four major Actresses preference. A statistical method, ANOVA: Single Factor, is used to determine if there is a significant difference in the ratings given to these Actresses.
Objective– To find out if there are significant differences in the preferences (ratings) of ITM students for Actresses.
Data Collection-Students of ITM Business School were surveyed. Each student rated four Actresses preference i.e. Kriti Sanon, Alia Bhatt, Deepika Padukone,Tripti Dhimpri on a scale of 1 to 10, were 1 indicates low preference and 10 indicates high preference. The ratings for each genre were recorded for analysis.
Data Analysis–
The ANOVA: Single Factor test was performed to compare the means of the ratings across the four Actresses.
The hypotheses for the test are:
- Null Hypothesis (H0): There is no significant difference in the average ratings of Kriti Sanon, Alia Bhatt, Deepika Padukone, Tripti Dhimpri.
- Alternate Hypothesis (H1) At least one of the Actresses has a significantly different average rating.
The results of the ANOVA: Single Factor test are as follows:
|
Anova: Single Factor |
||||||
|
SUMMARY |
||||||
|
Groups |
Count |
Sum |
Average |
Variance |
||
|
kriti sanon |
25 |
178 |
7.12 |
8.026667 |
||
|
alia bhatt |
25 |
172 |
6.88 |
7.276667 |
||
|
deepika padukone |
25 |
185 |
7.4 |
4.416667 |
||
|
tripti dhimpri |
25 |
177 |
7.08 |
5.41 |
||
|
ANOVA |
||||||
|
Source of Variation |
SS |
df |
MS |
F |
P-value |
F crit |
|
Between Groups |
3.44 |
3 |
1.146667 |
0.182518 |
0.908041 |
2.699393 |
|
Within Groups |
603.12 |
96 |
6.2825 |
|||
|
Total |
606.56 |
99 |
|
|
|
|
Since the p-value (0.9808041)) is greater than the standard significance level of 0.05, we accept the null hypothesis.
Conclusion-There is no significant difference in Actress ratings given by ITM students.