:"RegressionIt is argued that less time spent on social media will result in improved course marks among ECO242 students. To test whether this is the case you collect data from 20 students on their final marks (Y) and number of facebook posts during the semester (X). You make the following calculations:∑XY=9057,∑X2=2470 ∑X = 190 ∑Y=1164Next, you run the following regression:marks=β^1+β^2facebookpostswhere 'marks' is the final mark for the course in percentage points, and 'facebookposts' is the number of facebook posts completed during the course. Question 1 .The value for the slope parameter is? Question 2 The value for the intercept parameter is? Question 3 If the standard error for the intercept parameter estimate is 1.43701, construct a 95% confidence interval for the parameter. Pr( ?. ≤β1≤ ?. . )=95%
:"RegressionIt is argued that less time spent on social media will result in improved course marks among ECO242 students. To test whether this is the case you collect data from 20 students on their final marks (Y) and number of facebook posts during the semester (X). You make the following calculations:∑XY=9057,∑X2=2470 ∑X = 190 ∑Y=1164Next, you run the following regression:marks=β^1+β^2facebookpostswhere 'marks' is the final mark for the course in percentage points, and 'facebookposts' is the number of facebook posts completed during the course.
Question 1 .The value for the slope parameter is?
Question 2 The value for the intercept parameter is?
Question 3 If the standard error for the intercept parameter estimate is 1.43701, construct a 95% confidence interval for the parameter. Pr( ?. ≤β1≤ ?. . )=95%
Question 4 .If the standard error for the slope parameter estimate is 0.129308, construct a 95% confidence interval for the parameter. Pr( ? ≤β2≤ ?. )=95%
Questioion 5.Assuming all else is held constant, the estimated slope coefficient above can be considered an `effect size' for facebook post on marks. That is, for every additional facebook post, on average, the final mark changes by β^2. You conduct a hypothesis test to see whether the estimated effect that `posting on facebook' has on marks is statistically significant (make use of the standard errors given above). You start out with the following null and alternative hypotheses:H0:β2=0H1:β2"
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