Mis171 - Apply Quantitative Reasoning Assessment Answer

Assignment Task

Assessment Feedback: 
Students who complete their test by the due date will receive their marks in CloudDeakin on or before 9 October 2020. In order to understand areas where improvement is required, students are  encouraged to refer to the suggested solutions, comparing their answers with the ‘model’ answers provided, which will be released after the test closes. 
General Description / Requirements 
This is an individual assignment. It focuses on materials presented up to and including Week 9. To  complete the assignment you should: 
• Analyse the dataset to answer the specific questions presented to you during the online test (see the two cases below); 
• Interpret the results, and draw conclusions. 
Once you have done this, you will have the necessary output (i.e., data analysis, related summary information, and relevant visualisations) to complete the online test. The test contains fifteen (15) randomly allocated multiple-choice questions related to your data analysis, its interpretation, and your subsequent conclusions. The assignment uses the file MIS171-2020-T2-A3.xlsx which can be  downloaded from CloudDeakin. 
Scenario 
You are Tank McTavish, an analyst often asked for by media outlets and journalists to assist in giving their stories more credence. That is, they believe your numerical perceptiveness gives their stories greater rigour. You work for the firm “Media Analytical Insight (MAI)”1 in their analysis department. A large Australian news media group has requested information for two stories they wish to run. One regarding the salaries of Australian University Vice Chancellors, and the other regarding climate change and its effect on a changing sea level. You have been forwarded an email from Dr Tiny Numbaz, asking you to perform some specific data analysis. The email making this request alongside some guidelines (in blue) is presented below. Consider all comments carefully. 
1. Project 1: University Vice Chancellor Salaries 
Universities around the world help interested students find the true meaning of things. Universities are renowned knowledge generators, and they help societies evolve by assisting in the challenges that people face. Universities reward their Vice Chancellors (the Universities CEO) as a consequence of many things, including the university’s success. 
We have been provided with a data set that includes the salary for 37 Vice Chancellors from universities across Australia. Build a multiple regression model to predict the salary of a Vice Chancellor. Your model should provide insights into which of the factors influence a Vice Chancello’rs salary, as well as the ability to predict salary for various scenarios. 
For this analysis, you will need to build a multiple regression model using Sal($’000) as the dependent variable, and all other measures included in the data set as possible predictors. You should follow the model building process introduced in the lecture and seminars. You should also carefully consider the following: 
(a) Transform the categorical measure into a suitable dummy variable. 
(b) Generate relevant model summary information. 
(c) Build a multiple regression model and assess the model for overall significance (F test with alpha set at 0.05). 
(d) In the next step(s), if the overall model is found to be significant, in a stepwise fashion, sequentially (one at a time) remove the variables that are least likely to be contributing to any significant change in the dependent variable. You will need to conduct t-tests with alpha set at 0.05 to determine the significance of the various independent variables you exclude and include in your model. 
(e) Once you have created a multiple regression model, where all of the included independent measures are contributing significantly to a change in salary, ensure that you can use the regression model to provide salary estimates for any scenario regarding your included set of independent measures. 
2. Project 2: The Global Mean Sea Level Climate change is of global interest, particulary in costal areas where there are relatively higher densities of people. That the climate is changing is undeniable, however, a great deal of debate continues regarding the underlying causes of climate change. 
Data collected on the Global Mean Sea Level (mm) is recorded on the spread sheet “Time series data”. One hundred and thirty three (133) data points have been recorded covering the period from 1880 through to and including 2013. We are interested to better understand the mean sea level. Is it changing? If so, in what way? How fast is it changing? We want to forecast both the proportional change that might be expected at some time in the future, as well as the magnitude of that change. 
Implement a proper forecasting model to address this request and provide your interpretation. 
For this investigation, you will need to consider several forecasting models and evaluate their performance in terms of forecasting accuracy and model fit. You should consider the following: 
(a) Both 3 and 5 year centred moving average models. 
(b) Fitting linear, exponential, and polynomial (order 2), trend lines to the original data. 
(c) What do the errors say about the usefulness of the forecasting models? 
(d) What are the R2 values of the various models you have fitted? 
(e) Using each of the models you have built, develop a forecast model for the Global Mean Sea 
Level change that can be used to forecast any time period. 
I look forward to your response. 
Assignment instructions 
In order to prepare a reply to Dr Tiny Numbaz email, you will need to thoroughly examine and analyse the datasets. The Excel file (MIS171-2020-T1-A3.xlsx) includes a sheet named “Variable Definitions” describing all of the variables used in other worksheets. The following provides some guidelines that will help you to prepare your reply to Dr Tiny Numbaz and answer the online test. 
Once you have completed your data analysis, you should summarise the key findings. Before you attempt the online test, make sure you have a copy of your data analysis, your summaries and visualisations, so that you can refer to them as required. Ideally, you should be familiar with all aspects of your assignment. 
The test contains 15 multiple-choice questions. Some questions focus on the appropriateness of the technique, steps in the analysis, specific measures, and the theoretical assumptions you may have had to make. The rest of the questions relate to interpreting and drawing conclusions from your analysis. 
The following sample question is indicative of the type of questions you will receive in the online test. 
Multiple-choice: 
Is there any relationship between the number of students that attend a particular university, and the salary of the Vice Chancellor of that university? 
a) Yes, there is a positive relationship. 
b) Yes, there is a negative relationship. 
c) No, there is no evidence of any relationship. 
d) The provided information is inconclusive. 
Please ask any questions you may have regarding the assignment on the discussion board. 
 

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