Linear Regression

Linear Regression
Using the attached data (“Car Weight and MPG.sav”), compute and interpret the relationship between:
Car Weight (“Weight”) and miles per gallon consumed (“CityMPG”)
Sample = cars in the dataset. Population = all cars on the road in Illinois in 2020.
For this regression analysis, state the following:
A clear research question appropriate for a linear regression: (e.g., Among population A, is X a significant predictor of Y?”)
Null and research hypotheses that align clearly and neatly with your RQ.
Descriiption of the variables used.
Your dependent and independent variables. (Clearly explain your rationale as to why which is which.)
State the sample size, along with the mean, standard deviation, and range (min & max) for each variable, in a paragraph format. (Do not just include a table,
and not talk about it.)
State the rationale for applying regression analysis in this investigation using appropriate readings and resources in Module 5. (Please cite specific
references.)
Findings in an APA format. (This includes the wording of the finding and the tables/figures included.)
Use the following link to provide the template: https://www.slideshare.net/plummer48/reporting-a-single-linear-regression-in-apa
Also add a clear interpretation of the R-square value in your finding. See last page:
https://www.sheffield.ac.uk/polopoly_fs/1.531434!/file/MASH_simple_linear_regression_SPSS.pdf
Note: Even if the p-value in the SPSS output shows “.000,” write it out as “p < .001." Write out your regression equation, and state the predicted miles per gallon for cars that weighs 3,000 and 4,000 pounds. (Clearly show the calculations and steps involved.) Include the SPSS output in your appendix. *** Post your discussion submission by 11:59 PM Thursday, and give critical feedback to two peers by noon Sunday. After you have received your comment, upload a revised discussion post (if you feel that it is warranted based on your peer feedback and other information you have gathered since the initial post) by 11:59 PM Sunday. Please keep the old version(s) in the discussion post so that revision and progress can be documented.