https://ronellekriegerprofile.weebly.com/uploads/7/4/8/4/7484534/the_importance_of_assumptions_in_multiple_regression_and_how_to_test_them.pdf
https://ics.uci.edu/~jutts/110/Lecture3.pdf
Initial Post (Due Wednesday, May 8) Copy the questions in your post. Present your response directly below the question so that it is clear to what question you are responding to
Using the dataset associated with this thread. Select 2 explanatory continuous variables and one continuous response variable (Your choice).
List your variables and the variable descriptions
Run a multiple regression test using either JASP or Excel. Post all 3 of your multiple regression output tables to this thread.
Interpret the R, Adjusted R squared, ANOVA table p-value, the coefficient table p-values
Select ONE technique for assumption checking for multiple regression. Run that technique on the variables that the STUDENT used in their post (not your variables)
Present the results (chart, table, numerical summary … whatever your evidence is that you generated) and interpret them. Has the assumption been met? Explain.
Category: Statistics homework help
Calculate the hypothesis test p-value for the population mean with the given z-score. (Note: With two (2) tail tests you must add both tail p-values.) a. ????0: ???? ≤ 1.07 and ????a: ???? > 1.07, ???? = 2.27
For this Final project, you will be analyzing data that was collected from the survey that I sent to you all during the first couple weeks of class! I hope you have fun learning a little more about your classmates in this Final Project.:) This dataset contains information from 178 students (98 students in STA 2023 and 80 students in MAC 1105).
NOTE: You DO NOT need to work with the actual data set for this. I have included all of the relevant summary statistics in the statements of the problems.
Complete the assignment either on paper or on the computer.
Make sure to answer all questions.
Please try to include any sketches and work on the worksheet. If you are not able to, however, you may submit them as a separate document. (It’s just a little easier to grade when it’s all in one document.)
If you do not have access to a printer, you can hand write your asnwers on a separate sheet and upload a picture.
Upload completed worksheet to this assignment in Canvas.
If you have any questions, don’t hesitate to ask!
NOTES/HINTS:
The degrees of freedom for these problems is large, you may need to use StatCrunch or an online calculator to find the critical values for the t-distribution:
please follow the template attached
1. Abstract: A brief statement (few sentences at most) summarizing the purpose of the report as well as the results and what they mean in substantive rather than statistical terms. Be brief and to the point, stimulating your reader’s interest. You essentially have 15 seconds to let the reader know what’s in the report and if they should read it.
2. Introduction: Give background and motivate the question to be investigated. Introduce the data, perhaps with visualization or descriptive statistics, but only if you think it significantly adds to the narrative. A reader could jump from here to Results. While a formal research study has explicit hypotheses, you likely won’t have any, but at least try to suggest which variables in what form you expect to be important predictors.
3. Methodology: Describe the approach used to analyze the problem while keeping in mind that your reader likely never took or doesn’t remember ST 625. What was your approach? Why is your approach is appropriate? What are the assumptions? Are there any concerns about these assumptions?
4. Results: Present the recommendation simply and clearly. Use graphical display, table, and discussion as you see appropriate. You are providing an answer to the question outlined in the introduction.
5. Conclusion: Briefly summarize everything. Does the model make sense? Do the predictors seem reasonable? What does it all mean? Suggestions for further analysis or other data might be appropriate.
6. Appendix: Screenshots of recommended R model
Using the range of models, tools, and techniques studied in ST 625, build and present two models: one for predicting casual bike rentals using the independent variables, and another for predicting registered bike rentals. Your ultimate goal is to explain the factors that influence bike demand, and as such your model/variable selection should be based both on context and statistics. Model interpretation will be very important part of your report! What influences demand for bikes, and how, and to the extent plausible why? You should at a minimum perform linear regression using all the available independent variables as well as consider some types of complex model (terms that are higher-order, interaction, dummy), then perform variable selection/compare models. And to be very clear, casual should not be a variable used to predict registered, nor vice-versa
If X average and S2^2 The variance of a random sample of 26 from a normal population with a mean of zero and a variance of 16.
If the value is 0 < m , then check the value of m in the following case: