3.Submission of answers only in Minitab 18.0 files, without defining your work in obtaining the solution in full, is not acceptable.Detailed discussions must include the

(a) business problem

(b) data analysis techniques,

(c) data,

(d) analytical techniques,

(e) computerized procedures, and

(f) results and interpretation (per the course syllabus).

4.Merely providing screen shots from the Minitab 18.0 software is not acceptable. Rather they should be referenced in the results and interpretation. All computer output from Minitab 18.0 needs to be fully discussed and annotated.

A. Multiple Regression Forecast Modeling Analysis of You Tech Company (Dependent Variable)

Using the first 30 months of data for the year starting in January 2017, 2018, and 2019, forecast the price of your tech stock for months 31, 32, and 33 in year 2019.In all cases, the response variable is the price of your tech stock.You need to indicate the name of your tech stock in your submission and your dataset.

In order to insure for validity of your Minitab Best Subsets regression computations, you must show a link between your Minitab data set, your Minitab Best Subsets regression drop downs, and your Minitab Best Subsets regression outputs.That is, for each Best Subsets regression run, the data file, the drop down, and the output all need to be given.

B. Regression Models - Explanatory Variable Time Variables are the IndependentVariables.

Set 1:Variables of explanation: time, relating it to the price of your tech stock.Each of these multiple regression models for Set 1 contains 1 of the 5 time variables.

1. time (t) (1, 2, ..., 30)

2. time (t²) (1, 2, ..., 30)

3. time [(1/t)] (1, 2, ..., 30)

4. (sqt t) time (t-1, 2, ..., 30)

5. ln t time (t-1, 2, ..., 30)

C. Multiple Regression Model - Finance Variables in the Dependent Variable

Set 2:Variables of explanation:finance, relating it to the price of your tech stock.

1. Dow Jones Average (1, 2, ..., 30)

2. NASDQ Average (1, 2,.., 30)

3. S&P Average (1, 2,..., 30)

D. Multiple Regression Model:Economic Variable Is the Independent Variable.

1.GDP (1, 2,..., 30)

2. Price of Oil Per Variable (1, 2,..., 30)

3. Unemployment Rate (1, 2,..., 30)

E. You will develop 3 Multiple Regression Models using Best Subsets Regression.

1.Model 1- Relating the stock price of your tech stock (A) to time variables (B) and the finance variables (C) using Best Subsets Regression (first 30 months of data).

2.Model 2- Relating the stock price of your tech stock (A) to time variables (B) and the economic variables (D) using Best Subsets regression (first 30 months of data).

3.Model 3- Relating the stock price of your tech stock (A) to time variables (B) and the finance variables (C), and economic variables (D) using Best Subsets Regression (first 30 months of data).

F. Evaluation of Best Fit Model

For each of the three regression models in Model 1, 2, and 3, you need to display and discuss the models in terms of the best fit:

R²,

Mallow Cpstatistic,

standard error of the model,

coefficients, and

coefficient standard errors.

G. Evaluation of the Forecasts

You need to evaluate and discuss the regression models in periods 31, 32, and 33 in terms of the forecasting your tech stock price.