I need help with my regression analysis for research capstone.

[tlowe]

Hi all,

I'm new to regressions and also new to posting here.

My topic is: How have E-books Affected College Textbook Prices?

My hypothesis is:
H0: The CPI for college textbooks will fall with the introduction of the e-book because increased innovation and competition causes an increase in supply causing prices to fall.

H1: The CPI for college textbooks is unaffected by the introduction of the e-book.
(I can change my alternative and probably will since my r2 is >80% as of now...)

I have basically no idea how to do regressions so I used a online helper and I came up with this:

My dependent variable (x) is the CPI for College Textbooks by the BLS from 2001 to 2016 separated by year.

My independent variable (y) is the # of ebooks sold from 2001 to 2016 separated by year.

Which gave me these results:

View attachment 6534


What I'm trying to figure out is what does all of this mean? My p val is <.0001 which is good I think but I need help putting what all of this info means in words?

Also, I have other variable (control variables I'm guessing?) such as the Consumer Price Index for College Tuition and Fees, GDP, and Higher ED Enrollment among other things and I want them to be a part of the regression. The prob is I don't know how to add them into it!!!

Any help is appreciated.

Thank you so much an advance!

PS I have the data in excel and can include also.

 

[Miner]

The null hypothesis would be no relationship between x and y. The alternate hypothesis is that there is a relationship between x and y. The p-value is the probability that you would see these results assuming the null hypothesis is true. A p-value of <0.0001 would be extremely unlikely, so you would reject the null hypothesis in favor of the alternate that there is a relationship between x and y.

 

[tlowe]

Does any of that make sense? I don't even know if I set up my regression right. Can we email or something I can't DM!

 

[CB]

I've deleted OP's duplicate post.

 

[ondansetron]

The null hypothesis would be no relationship between x and y. The alternate hypothesis is that there is a relationship between x and y. The p-value is the probability that you would see these results or more extreme results assuming the null hypothesis is true. A p-value of <0.0001 would be extremely unlikely, so you would reject the null hypothesis in favor of the alternate that there is a relationship between x and y.

Only added a few words to your post

 

[Miner]

Also, I have other variable (control variables I'm guessing?) such as the Consumer Price Index for College Tuition and Fees, GDP, and Higher ED Enrollment among other things and I want them to be a part of the regression. The prob is I don't know how to add them into it!!!

PS I have the data in excel and can include also.

If you are trying to use Excel for your analysis, I believe that it can only handle one IV at a time. Do you have access to any statistical software?

Attaching data is always helpful.

 

[tlowe]

If you are trying to use Excel for your analysis, I believe that it can only handle one IV at a time. Do you have access to any statistical software?

Attaching data is always helpful.

Thank you for the response!

I have SAS University on my computer but not sure how to put this data into it.

I have attached my dataset as well. CPI text is my dependent and # of ebooks in mill is my independent. I just want to make sure I ran the regression right.

Also, I want to be able to add in those other datasets too but I also have no idea how!

Any help is awesome... Thanks!

View attachment 6536

 

[tlowe]

Moderator has to approve my post?

 

[ondansetron]

If you are trying to use Excel for your analysis, I believe that it can only handle one IV at a time. Do you have access to any statistical software?

Attaching data is always helpful.

Although I would recommend an actual stats package also, I just double checked to confirm that Excel can handle multiple IVs. For the X-variable range, just highlight the entire matrix of x-values and it will take each column in the range as it's own variable.

 

[tlowe]

Here is the data and what I came up with....

If someone could check it and let me know what I did wrong that would be great.

My dependent variable (x) is the CPI for College Textbooks by the BLS from 2001 to 2016 separated by year.

My independent variable (y) is the # of ebooks sold (in millions) from 2001 to 2016 separated by year.


New hypothesis:

H0: The CPI for college textbooks is unaffected by the introduction of the e-book.

H1: The CPI for college textbooks will fall with the introduction of the e-book because increased innovation and competition causes an increase in supply causing prices to fall.

View attachment 6538

View attachment 6537