achyuthkumar. application assignment 5.pdf
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Week- 5 Assignment
Achyuth Kumar Thalloju
Saint Louis University ` School of Professional Studies
AA 5000-22 – Foundation of Analytics
Prof. Kamal Lamsal
Wednesday, 29th November 2023
Identify three continuous (numeric) variables and one categorical (factor) variables.
Numercial Variables:
“Comment”
“Like”
“Share”
Categorical variable:
“Paid”
2. For each pairwise combination of the three continuous variables (three total
combinations), present null and alternate hypotheses regarding the nature of association
(correlation), unambiguously.
# Calculate the correlation and its p-value
cor.test(Data$'comment', Data$'like')
# Calculate the correlation and its p-value
cor.test(Data$'comment', Data$'share')
# Calculate the correlation and its p-value
cor.test(Data$'like', Data$'share')
3. Test each of the three hypothesized relationships using correlational analysis. Explain,
using appropriate evidence, whether the null can be rejected in each case.
Let’s analyze the three hypothesized relationships using correlational analysis and determine
whether the null hypothesis can be rejected in each case:
Relationship between 'comment' and 'like':
Correlation Coefficient (r) = 0.8379
: There is a strong positive correlation
between the number of comments and the number of likes on posts.
P-Value < 2.2e-16
: The p-value is significantly less than 0.05, showing that the
observed correlation is highly statistically significant.
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Conclusion
:
The null hypothesis is rejected, showing that there's a clear and strong positive link
between the number of comments and likes on posts.
Relationship between 'comment' and 'share':
Correlation Coefficient (r) = 0.8683
: There is a strong positive correlation
between the number of comments and the number of shares of posts.
P-Value < 2.2e-16
: The p-value is significantly less than 0.05, showing that the
observed correlation is highly statistically significant.
Conclusion
:
We can remove the null hypothesis and confirm that there's an important and strong
positive relationship between the number of comments and shares on posts.
Relationship between 'like' and 'share':
Correlation Coefficient (r) = 0.9040
: There is a very strong positive connection
between the number of likes and the number of shares of posts.
P-Value < 2.2e-16
: The p-value is significantly less than 0.05, showing that the
observed correlation is statistically significant.
Conclusion
: We can reject the null hypothesis and state that there's a very strong and
significant positive connection between the number of likes and shares on posts.
In each case, we reject the null hypothesis of zero correlation because of very low p-values. So, it's
clear that there are significant positive relationships between these pairs of variables.
4. For each hypothesized associated, conduct a nuanced analysis to determine whether the
hypothesized association holds across different levels (categories) of the factor (categorical)
variable. Use appropriate graphical and numerical information to draw appropriate
conclusions.
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