Regression Analysis - How to Read Prediction Data

azray

New member
Joined
Oct 6, 2018
Messages
1
I'm needing to interpret the data from my Regression Analysis, but am obviously going wrong somewhere.

The data set is...
StudentCollege GPA, yHigh School GPA, x
13.854.00
22.962.50
32.513.50
43.523.41
53.953.80
63.303.10
73.253.60
83.002.50
92.753.70
103.413.50
113.652.75
123.203.10
132.502.30
143.803.55
153.373.40

The question is: A researcher wanted to know if students' College GPA was associated with their High School GPAs, and collected the data in the table. What can you say regarding the relationship between these two variables? Be sure to show your work and reference calculated values to support your answer.

My Incomplete Answer: I conducted a Regression analysis with High School GPA as my x-variable and College GPA as my y-variable. My sample size was 15. I calculated an R = .4837 which is a moderate relationship. My R-Square was 23.4% which means that I have accounted for 23.4% of the variation in High School GPA as the predictor variable. This is a weak prediction model. Observation 3 is a possible outlier. I predict for ??? that they will have ??? GPA. With a P-value of 6.77, this prediction is statistically insignificant???

Furthermore, I've tried to come up with the predictive GPA, but have an number of 8.28, which obviously is incorrect or needs further work. To get that number, I added the intercept to (x variable of .4263 x the sample size of 15 GPA's).

If anyone can help with clarifying an answer or showing where I may have went wrong, I'd greatly appreciate it!



Screenshot (116).jpg
 
I'm needing to interpret the data from my Regression Analysis, but am obviously going wrong somewhere.

The data set is...
StudentCollege GPA, yHigh School GPA, x
13.854.00
22.962.50
32.513.50
43.523.41
53.953.80
63.303.10
73.253.60
83.002.50
92.753.70
103.413.50
113.652.75
123.203.10
132.502.30
143.803.55
153.373.40

The question is: A researcher wanted to know if students' College GPA was associated with their High School GPAs, and collected the data in the table. What can you say regarding the relationship between these two variables? Be sure to show your work and reference calculated values to support your answer.

My Incomplete Answer: I conducted a Regression analysis with High School GPA as my x-variable and College GPA as my y-variable. My sample size was 15. I calculated an R = .4837 which is a moderate relationship. My R-Square was 23.4% which means that I have accounted for 23.4% of the variation in High School GPA as the predictor variable. This is a weak prediction model. Observation 3 is a possible outlier. I predict for ??? that they will have ??? GPA. With a P-value of 6.77, this prediction is statistically insignificant???

Furthermore, I've tried to come up with the predictive GPA, but have an number of 8.28, which obviously is incorrect or needs further work. To get that number, I added the intercept to (x variable of .4263 x the sample size of 15 GPA's).

If anyone can help with clarifying an answer or showing where I may have went wrong, I'd greatly appreciate it!



View attachment 10292

An explanation including "x-variable" and "y-variable" indicates mechanical understanding of what you are doing. You later refer to "predictor" or "prediction". That's a little better. Actually say what you are doing.

It is said that a[FONT=&quot] predictor that has a low p-value is likely to be a meaningful addition to your model. 6.77?! This seems to contradict your assertion that r = 0.4837 is moderate relationship. This disagreement seems to suggest that you have shown nothing. More data![/FONT]
 
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