Math 54 Online - Project Information Handout
This small project will give you a chance to apply what you have learned about simple linear regression and study a problem that you find interesting. In this project, you will perform a statistical analysis to investigate how two quantitative variables (not qualitative variables) are associated and how one influences the other. You can choose what two variables you are interested in studying and will use your own data in order to perform an analysis. I will provide you with a few good sources from which you might be interested in obtaining your data. The requirements for this project are discussed in detail below.
You may work individually or with up to three other classmates maximum (so for a group of up to 4 people, including you). Use of Excel or other computer statistical software will be required to carryout various calculations, produce tables and graphs, and to perform a statistical analysis. You will be required to write a 2 or more page report (double-spaced) briefly discussing the problem being studied, your analysis and findings, as well as additional or concluding remarks. Note that the 2 or more page minimum length does not include any tables or graphs (which will be included separately after the paper). You will include the Excel graphs or charts produced after the report, as well as the raw data collected.
This project will be worth 70 points in total, and the project will count for 6% of your course grade. However, a project survey in the form of a Canvas quiz, in which you can give your preferences for the project, will be worth an additional 5 points (so for 75 points including the survey). Your report should be well-written with proper grammar. Below I have a suggested framework of how to structure your short project report (for after you have completed your summary output using technology). Following this will make writing your report much easier. You must include these key points, but you can alter the ordering slightly, if you wish.
A. Suggested Paragraph Structure for the Written Report (Minimum 2 pages, double-spaced)
Paragraph 1: First, give an introduction discussing the problem being studied, some background on the topic, and why it is of interest to you. Second, mention how your data was obtained, citing your data source. Lastly, describe which variable would be the explanatory variable and which one is the response variable, and why so.
Paragraph 2: First, interpret the meaning of the correlation coefficient from your summary output in in a sentence for your project example (follow the structure that I taught in my notes and videos). Second, include the linear regression equation in the report with the determined intercept and slope values. Third, interpret the slope and intercept values from the regression equation in sentences (follow the structure that I taught in my notes and videos).
Paragraph 3: First, state what the coefficient of determination value is, and interpret its meaning in a sentence for your project (follow the structure that I taught in my notes and videos). Second, perform. diagnostics on the regression model using the residual plots from your summary, based on material taught in section 4.3 (chapter 4); here comment on (1) whether or not a linear model should be appropriate, (2) whether or not the residual error term appears to have constant variance, and (3) whether or not there are any outliers.
Paragraph 4: Briefly describe, in conclusion, if this regression model does a good job in explaining the dataset, based on your Excel findings. Here you can make additional comments about the regression model that you think are worth mentioning. This is your chance to be creative and provide additional insight, but there is not really a right or wrong way to do this.
B. Requirements for the Appendix After the Written Report:
a) A scatter diagram showing the relationship between the 2 variables being analyzed.
Include a graph of the linear regression equation in this plot as well. Be sure to label the axes and the plot.
b) Show the tables, determined using Excel toolbars and functions, which display coefficient values, t values for the regression coefficients, and the p-values.
c) The residual plot, as shown in class. Be sure to label the axes and the plot.
d) The raw data collected.
e) Describe how you and your group member each contributed to the project (if you worked in a group). [If you worked alone then you will not need to do anything for this parte)].
Note: Full credit (100%) will be given on the project if you: (1) follow correctly all of the guidelines from the suggested framework (from this document) for the report section with proper sentence interpretations for your project variables, and if your report is well-written , (2) if you follow the requirements for the appendix graphs and charts shown right above on this page. Thus, if you allow enough time for this project and follow my suggestions it should not be hard to get an ‘A’ grade on it.
Each group only has to turn in 1 paper (including Excel graphs or calculations. This will be submitted on Canvas. I will check the report for plagiarism. This project must be submitted no later than Saturday, February 15 by 11:59pm. Note that Iam giving a few extra days to complete the project than the due date on the syllabus. This means that you must submit your report (or your group’s report) by that time. No late reports will be accepted.