Regression modeling of a dataset that we chose. The dataset needs 50 rows and 10 columns. It's a decision-making business report, the dataset has to be chosen accordingly.
STAT4610 Project 4 Multiple Regression Model and Business Report For this Project you will collect data, perform preliminary data analysis, build and analyze a model, and use the results of your analysis to make predictions, draw conclusions, and support decisions. The Project will be submitted in two phases: Phase I: Collect data and describe your data set. Perform preliminary analysis of your data, using descriptive statistics [0 points, but corrections not made for Phase II will result in a deduction, as will late or missing submissions]. (Due before class, Lesson 13.) Phase II: Build a multiple regression model from your data, and prepare a business report that includes all of your previous work, and that presents a recommendation to a decision-maker based on your model and analysis [250 points]. (Due in hard copy at the beginning of class, Lesson 15.) PROJECT DETAILS Phase I, Data Collection and Preliminary Data Analysis You may collect your data from (almost) any source(s). The objective is to find a numerical response (dependent) variable that can be predicted from some number of other (independent) variables. (The independent variables may be categorical, binary, or numerical, but the response variable must be numerical.) These data do not have to come from the same source, but should be compatible as data sets. Data should be cross-sectional (no time-series data). The minimum requirement is 50 observations with ten independent variables. [Beware the tautology: do not collect temperature and humidity to “predict” the heat index!] Ensure that your data set will allow you to draw relevant conclusions about something that matters. The data may be from any field (preferably business-related) and should be collected so that you can establish relationships among your data to support some sort of a conclusion or recommendation. Apply descriptive statistics to your data set. This should include graphical depictions (histograms and scatter plots) as well as some basic calculated descriptive statistics. Since you will be building a multivariate model, the correlations between your independent variables should be included. You should, at this point, be able to make some preliminary observations about your data. These observations (and any others you come up with later) should make their way into your business report, but will generally appear in appendices unless you determine them to be critical to the decision you are recommending. This submission should be a word document (for the descriptive stats, graphics, and analysis) and an excel file (for the data only). Phase II: Model Construction and Business Report Build a multiple regression model from your data using the techniques we have learned in the course. You should decide here how you intend to use your model to conduct analysis, make predictions, and support decisions. Wrap all of your work up in a business report. Remember that the target is an executive who you will ask for a decision based on your recommendation. Perform analysis with your model, interpret your model, include your calculations and the original data (in appendices) but present the bottom line to the decision-maker up front. The report will be submitted through canvas as a word doc or pdf before class. While many organizations suggest a format for a business report, there are as many that do not, so the presentation is up to you. However, the following page may be used as a guideline. Business Report Format (Suggested) Cover Sheet Title. Indicate who the report is for, and what the report is about. (Use this to establish the “setting” for your instructor to grade your submission.) Your name and position. (Again to establish context for the grader.) Executive Summary. A single paragraph that an executive can read and immediately know what decision you are recommending and why. Main Body A 2-3 page report that tells the executive what decision should be made, and why the decision should be what it is. This should reference (and may include) the model you are using to support the decision-making process, and may also describe how confident the executive should be when making this decision. (In extreme cases the report can go up to 5 pages. Business reports not intended for senior executives may be longer, based on the organization’s needs.) BLUF! (Bottom Line Up Front!) The decision should be clear after the first few sentences, and definitely by the end of the first paragraph. Include only that information that will be critical to the executive’s decision-making process. Refer to all supporting data and analyses that are included in appendices. Appendices should appear in order of importance, and should be referenced in that order. Appendices (this shows one possible way of organizing your supporting information) AModel and Interpretation (Show the final model you developed to support the decision, and interpret it, to include discussing the effects of the ranges of your input variables.) BModel Statistical Analysis (Discuss the strength of the model in terms of how it supports the decision-making process. Include the relevant Excel output that supports the quality of the model.) CModel Development (Brag about the process you used to turn the data into a model. Discuss variable elimination and transformation, as well as any other clever modeling techniques you used. You do not have to include every step of your process, but you should show critical analyses that led to important modeling decisions.) DData Analysis (Show your descriptive and graphical analysis of the data, to include all the observations that might contribute to the modeling process.) EData Describe the data set and include the sources. For very small data sets you may include them. For small data sets (hundreds of observations) or larger, do not waste your company’s paper.