Description based on excel data. Regression Analysis Output: 1. Solve the follow
ID: 3273490 • Letter: D
Question
Description based on excel data.
Regression Analysis Output:
1. Solve the following questions: What is the relationship between saturated fat (sfat_dr) and alcohol consumption (alco_dr) for all groups? In addition, please state the hypotheses and explain in your own words what the answer means.
2. Please construct a simple regression with the dependent variable of alcohol consumption (alco_dr) and the independent variable as saturated fat (sfat_dr). What are the null and alternative hypotheses? Explain in your own words what the answer means. (*Graph is below.)
Simple Regression Graph:
3. Using the dataset, is there a total alcohol consumption (alco_dr) difference among the three groups? Please state the hypotheses and explain in your own words what the answer means.
Explanation / Answer
Given that, the dependent variable of alcohol consumption (alco_dr) and the independent variable as saturated fat (sfat_dr).
We have given the regression output.
We can answer all the questions by using this output.
Solve the following questions: What is the relationship between saturated fat (sfat_dr) and alcohol consumption (alco_dr) for all groups?
Here we have to find correlation.
In the output Multiple R indicates that correlation value.
MultipleR = relationship between saturated fat (sfat_dr) and alcohol consumption (alco_dr) for all groups = 0.1814
Here correlation is positive indicates that there is positive relationship between saturated fat (sfat_dr) and alcohol consumption (alco_dr) for all groups.
From the normal probability plot it indicates that the data follows normal distribution.
Tests of Hypothesis :
Here we can test the overall significance and individual significance.
Using the dataset, is there a total alcohol consumption (alco_dr) difference among the three groups? Please state the hypotheses and explain in your own words what the answer means
Overall significance :
Here we have to test the hypothesis that,
H0 : Bj = 0 Vs H1 : Bj not= 0
where Bj is population slope for jth independent variable.
Assume alpha = level of significance = 5% = 0.05
Here test statistic follows F-distribtution.
F = 5.82
P-value = 0.0169
P-value < alpha
Reject H0 at 5% level of significance.
Conclusion : Atleast one of the slope is differ than 0.
We get significant result about overall significance.
Individual significance :
Here we have to test the hypothesis that,
H0 : B = 0 Vs H1 : B not= 0
where B is population slope for independent variable.
Assume alpha = level of significance = 5% = 0.05
Here test statistic follows t-distribtution.
t = 2.412
P-value = 0.0169
P-value < alpha
Reject H0 at 5% level of significance.
Conclusion : Atleast one of the slope is differ than 0.
We get significant result about individual significance.