check details he instructions are in the assignment. You will just have to follow the steps.? If the work is extensive, I can do part 1 (explora
check details
he instructions are in the assignment. You will just have to follow the steps.
If the work is extensive, I can do part 1 (exploratory analysis)
Final exam data (Winter 2022).xlsx
DATA
| Sales manager ID # | Sales | Wonder | SCIIT | Experience (yrs) |
| 798 | 96 | 27 | 42 | 5 |
| 178 | 90 | 35 | 46 | 8 |
| 264 | 113 | 30 | 55 | 8 |
| 589 | 98 | 26 | 47 | 2 |
| 392 | 76 | 28 | 45 | 7 |
| 476 | 117 | 24 | 56 | 11 |
| 620 | 118 | 35 | 63 | 4 |
| 653 | 101 | 33 | 50 | 9 |
| 237 | 95 | 27 | 54 | 4 |
| 333 | 94 | 38 | 41 | 8 |
| 497 | 119 | 31 | 62 | 3 |
| 257 | 120 | 31 | 79 | 1 |
| 378 | 115 | 32 | 52 | 9 |
| 260 | 131 | 31 | 62 | 4 |
| 514 | 99 | 34 | 45 | 3 |
| 343 | 102 | 25 | 59 | 0 |
| 213 | 66 | 26 | 40 | 6 |
| 754 | 129 | 25 | 64 | 11 |
| 696 | 100 | 25 | 39 | 6 |
| 132 | 111 | 33 | 52 | 2 |
| 820 | 128 | 39 | 74 | 5 |
| 615 | 104 | 28 | 45 | 9 |
| 676 | 133 | 33 | 61 | 5 |
| 905 | 125 | 37 | 66 | 8 |
| 861 | 99 | 23 | 46 | 8 |
| 944 | 90 | 31 | 46 | 5 |
| 890 | 122 | 36 | 63 | 9 |
| 158 | 62 | 32 | 54 | 11 |
| 468 | 98 | 37 | 46 | 11 |
| 421 | 100 | 25 | 49 | 3 |
| 993 | 123 | 30 | 62 | 0 |
| 640 | 120 | 36 | 57 | 5 |
| 298 | 83 | 28 | 41 | 2 |
| 724 | 71 | 24 | 34 | 9 |
| 388 | 102 | 34 | 54 | 4 |
| 212 | 89 | 35 | 48 | 8 |
| 690 | 75 | 31 | 53 | 1 |
| 304 | 106 | 30 | 54 | 5 |
| 559 | 80 | 30 | 36 | 0 |
| 149 | 99 | 25 | 49 | 8 |
| 290 | 104 | 38 | 56 | 11 |
| 220 | 105 | 26 | 55 | 4 |
| 283 | 87 | 24 | 43 | 13 |
| 686 | 105 | 26 | 50 | 5 |
| 535 | 90 | 37 | 41 | 5 |
Final exam (Winter 2022).docx
MGMT 2262
Final exam
Winter 2022
Contents
General Information 2 Rules 2 Outside sources 3 Scenario 4 What you need to do 4 Part 1 – Exploratory data analysis 5 Table 1 5 Part 2 – Training and testing set (sample) 5 Table 2 7 Part 3a – Simple linear regression 9 Table 3 10 Part 3b – Choosing between models 12 Table 4 12 Part 4 – Multiple linear regression 13 Table 5 13 Submission Guidelines 14 Breakdown of marks 15 Notes on plagiarism and cheating (and how to avoid it) 17
Two very important notes:
1. This is a statistics course and the goal of this final exam is to demonstrate your understanding of the whole course. When you are reviewing your work, ask yourselves “are we demonstrating our understanding of relevant topics?”
2. Related to 1, though the rubric is in the middle of the document, it is the most important part of the exam as it specifically tells you what you are being grade on. As you complete each step, ensure that you have checked your work against the rubric to make sure you are maximizing your grade. Also it indicates where to put most of your effort (i.e. the portion of the exam that is worth the most should be where you put most of your work).
General Information
· This exam has four parts, which involve utilizing multiple analysis techniques to explore a human resources problem.
· The overall goal of this exam is to demonstrate your understanding of the key topics in this course and that you can apply them in a real-world situation.
· Worth: 25% of total mark for the course.
· Due: Wednesday, April 20th by 11:59pm
· Late submissions will not be accepted. Extensions will not be granted except in extreme circumstances. If you submit late, expect to receive 0% on the exam.
· Though you do not need to do additional research for this exam, if you directly use any sources outside of the course (i.e. not from course notes or from the textbook), it is expected that you properly cite them. Both in-text citations and the reference list need to be done in APA style: https://library.mtroyal.ca/citations
Rules
1. Most important rule: This is an individual exam. It must be completed by you and only you. The work you submit must be your own work. The normal expectations of students completing an exam apply.
· You are not allowed to ask for help from another human, show your work to another human (other than when you submit to your instructor), or in any way gain any form of assistance from another human.
· You cannot pay someone to do this exam for you. You cannot go to a website and share the document, get possible answers and use them in any way. You cannot go to a website, look for the exam, get possible answers and use them in any way.
· Communication about any portion of the exam in any way with any person other than Your instructor is strictly prohibited.
· Asking for any kind of help for this exam is strictly prohibited. Think like you are writing an in-person exam. You couldn’t lean over to your buddy and ask them how to make a histogram. So you can’t do it on this exam.
· Note: If two people submit work that is strangely similar, there is a very good chance that both students will receive 0 and will be sanctioned with academic misconduct. Further to this, I will pay special attention to students who have worked together in the past to see if their answers are similar.
2. It is “open” book. This means you can use any resource (other than a human) you want to complete the submission. This includes the textbook, course notes, course videos, and internet sites (excluding homework help sites like Chegg and CourseHero).
3. You can ask the course coordinator Collette Lemieux ( [email protected] ) for help that involves clarification. For example, if you do not understand what an instruction means, you can ask for clarification.
· Similar to assignments 1 and 3, a FAQ document has been created. Please check there for questions and answers.
4. You cannot ask your instructor for help doing the exam because it is expected that you know how to do it. For example, if you do not know how to make a histogram, you need to figure it out on your own. Or if you are not sure what model to use in Step 3 of a hypothesis test, you need to figure it out on your own.
· This relates to the majority of Excel issues as well. For example, if you don’t have the Data Analysis Toolpak properly installed prior to the final exam, that suggests you aren’t prepared to write the final and need to figure out the problem yourself. As another example, it is expected that you have actually used Excel to do a similar analysis prior to the final exam. Therefore, if you are having problems with doing the analysis, you need to figure it out on your own.
5. You cannot ask your instructor for feedback.
6. For all parts, you can work as much or as little on it as you want. As long as it is completed by April 20th end of day.
· You have been given over ten days to complete this exam. It is expected that you work on the exam throughout this period. If you choose to wait until late on Wednesday to start the exam and run into problems, then you need to accept the consequences.
· If you studied for the final exam prior to writing it, it will take 3 to 4 hours to complete. But most of you will study as you are writing it (because it is an open book exam). Therefore, plan to spend at least 12 hours working on the exam. Therefore, starting this exam three hours before it is due is like showing up to an exam two hours after it has started.
· This is a final exam. It is worth 25% of your mark. Behave accordingly.
7. This is not a complete list of rules as that is hard to do. Instead, please keep in mind the spirit of the rules which is an open book, individual exam .
Outside sources
NOTE: If you directly use an outside source (e.g., paraphrase or quote), you still need to do a proper APA citation. What is described below is only for outside sources that you looked at for help and not for directly writing your final work.
As I am absolutely convinced that most of you are using outside sources and failing to cite them, let us make it easy. If you look at a website outside of the class (i.e. not our textbook or from BB), insert the URL in the table below, state which part of the exam you used it for (1, 2, 3 ,4), and very briefly how you used it. In the first row, I’ve provided an example of what I’m expecting. Please delete it before submitting.
|
URL |
Part |
How used |
|
2 |
Read about r and how to interpret it. |
|
If you claim you used no outside sources OR you directly used all outside sources, instead of submitting the above table, include the following sentence in your final work (see submission guidelines for where):
“I, [insert full name], solemnly swear that I did not use any outside source (except those properly cited using APA referencing) to complete this exam. I understand that failure to indicate outside sources is an act of academic misconduct and could result in getting 0 on this exam.”
Scenario
The Craybill Instrumentation Company produces highly technical industrial instrumentation devices. The company has 45 sales regions, each headed by a sales manager.
The human resources (HR) director has the business objective of improving recruiting decisions concerning sales managers. The HR director determined that the primary method of evaluating the effectiveness of recruitment is the hire’s resulting “sales index” score, which is the ratio of the regions’ actual sales divided by the target sales. The target values are constructed each year by upper management, in consultation with the sales managers, and are based on past performance and market potential within each region.
At the time of their application, candidates are asked to take the Strong-Campbell Interest Inventory Test and the Wonderlic Personnel Test. The former test measures the applicant’s perceived interest in sales, while the latter measures their perceived ability to manage. For both tests, the higher the score the better. Due to the time and money involved with the testing, some discussion has taken place about dropping one or both of the tests.
The HR director decided to use regression modelling to predict the sales index (Sales) of the sales managers. To start, the HR director gathered information on each of the 45 current sales managers, including years of selling experience (Experience), and the scores from both the Strong-Campbell Interest Inventory Test (SCIIT) and the Wonderlic Personnel Test (Wonder). The attached Excel file contacted information on the 45 current sales managers.
Your goal is to perform analysis to determine: Can the sales index be predicted by the variables chosen by the HR director? If so, which variable or combination of variables is the most effective predictor.
What you need to do
To answer the above question, follow the instructions below. You will submit all of the tables in each of the parts and your Excel file with your completed work. See Submission Guidelines for more details.
Part 1 – Exploratory data analysis
Prior to doing the regression analysis, the HR director wants to get a sense of the quality of sales managers Craybill currently has. To do this, run an exploratory data analysis of the sales index and determine what story you want to tell about the sales managers.
· Goal: Answer the HR director’s question: “What is the quality of the current sales managers at Craybill?”
· How: Perform exploratory data analysis.
· Step 1: Run an exploratory data analysis (i.e., create visualizations and numerical summaries) for the sales index.
· Step 2: Choose one other variable (i.e., Wonder, SCIIT or Experience) to drill down into the sales index data. Run an exploratory data analysis (i.e., create visualizations and numerical summaries) for the sales index and your chosen variable.
· Step 3: Review your work and decide what story you want to tell about the quality of the current sales managers at Craybill.
· Step 4: Choose one visualization or set of numerical summaries (or both) from Step 1 and one visualization or set of numerical summaries (or both) from Step 2. Insert them in Table 1. Then write an answer/explanation to the HR director that explains the story and answers their question.
Table 1
|
Evidence: Visualization, numerical summaries or both |
Explanation to HR director of current situation |
|
|
Sales index |
[Focus only on the sales index. What is the story of the quality of the current sales managers.] |
|
|
Drill down |
[Choose one other variable (i.e., Wonder, SCIIT or Experience) to drill down. What is the story of the sales manager based on one of the other variables? ] |
Part 2 – Training and testing set (sample)
Have you heard of machine learning ? Sounds like a super hard area of computer science that is way too hard for a first class. But actually, you’ve already engaged in machine learning! How? you ask. Well, a type of supervised machine learning is linear regression.
The goal of machine learning is to build a model that learns or changes as new information is provided. In regression, the model is built from data and it can be improved upon as new data is provided. For example, if we build a regression model to predict the sales index for sales managers, as we hire new sales managers, we can add their information to the model, re-run the regression analysis, and get an even better prediction model.
Another big part of machine learning is testing the accuracy of our model. We often do this by taking our data set and dividing it into two parts: a training set and a testing set. The training set is used to build the model, which in our case means using the data analysis toolpak to get the regression values. Then we plug the values from the testing set into the model to see how good the model is at making predictions for a different set of data. In short, the training data set is used to build the model (in this case the regression model), while the testing data set is used to test the ability of the model to make predictions. If you are interested in finding out more, check out this article (note: this isn’t needed to do this exam but is provided purely for interest).
The common rule for dividing the data is called the 80/20 split. That is, the training set is made up of 80% of the data while the testing set is made up of 20% of the data.
In this first step, divide the data set to make the training and testing set.
· Goal: Divide the data into two random samples. The first sample is called the training set and will contain 80% of the data values. The second sample is called the testing set and will contain 20% of the data values.
· How: Collect a random sample.
· Step 1: Choose a random sampling technique.
· Step 2: Apply the random sampling technique to the data set to randomly select 20% of the sales managers and their associated data. Copy and paste those into the “Testing set” part of the table below.
· Though this is the “second sample”, we are collecting it first for efficiency – it is faster to collect a 20% sample instead of collecting an 80% sample.
· Step 3: Then take the remaining 80% of the sales managers and their associated data, and copy and paste those into the “Training set” part of the table below.
· Step 4: At the top of the table, briefly explain how you collected your sample in the row provided in the table.
Table 2
|
Brief explanation of how the sample was collected. |
|||||
|
Sales manager ID |
Sales |
Wonder |
SCIIT |
Experience (yrs) |
|
|
Testing set |
|||||
