This essay focuses on wright as independent variable.. Answers will not be accepted after due date. Get the data from data folder on Canvas or assignment
on, upload the file on Canvas before the due date. Answers will not be accepted after due date. Get the data from data folder on Canvas or assignment folder. Q1a. Price of diamond depends on a variety of factors such as clarity, weight, cut as well as color. The data table provides a sample of 93 diamond pieces in terms of its price and weight. Run the following simple regression model with price as response variable and wright as independent variable and answer the questions: a) Create a scatterplot and describe the association wright as independent variable between the two variables in JMP (Print screen) b) Estimate the linear equation
the intercept and slope with wright as independent variable appropriate units (Print Screen) c) Interpret R square and root mean square error (RMSE) associated with the fitted equation. d) What does the p value for the slope term tell us? (chapter 19) [8 pts.] Q1b. You are to perform the stock beta analysis (Project 1). The wright as independent variable data for three stocks ( General Electric
(GE), Pfizer, and Amazon) and S&P500 are provided in the data folder (Q1 Stock Beta data) as the MONTHLY VALUES for the wright as independent variableperiod August 30, 2010 through August 30, 2020. Compute the mean and standard deviation for the rate of returns of all three stocks. Then run three simple regression models with rate of return of three stocks as dependent variable and ROR of S&P500 as independent variable one at a time. Determine which stock is the best.
[12 pts.] 1. Fill the table and evaluate which stock will you invest in (Slope and P Value are the determining factors). 2. Can the volatility/risk and stock beta (slope analysis) evaluation give different stock choices? Which analysis will you prefer and why? Q40 1 Q40 2 2 | Page Stock Mean Standard Deviation Slope P Value R Square General Electric Pfizer Amazon Q2a. Define a dummy variable. How will you use the dummy variable in
(Week 13, Chapter 25) [8 points] Q2b. In real estate often, the housing prices are dependent upon the cost of construction, location, and various other attributes of housing such as number of bedroom, bathrooms, size of lot, and proximity to various locations (employment, freeway, and other amenities). Run a multiple regression model with price as dependent and square foot, bedroom, bathroom, three car garage and pool as independent variable (Q2b Home Price). a. Use the housing data to develop a relationship among prices, square foot, bedrooms, bathrooms, 3 car garage (dummy variable with 1 as
3 garages), and pool (dummy variable with 1 as a house with a pool and 0 without). b. Is a three-car garage a significant factor in the estimation of house price? Explain. (Print Screen) c. What is the expected price of a house if you are considering buying a house in this neighborhood with the following
characteristics: 2000 square foot, 4 bedrooms, 2 baths, three-car garage and a pool? (Week 13, see DQ-2 video, Chapter 25) [12 points] Q3a Define the term multicollienarity. When does the problem of multi-collinearity occur in regression analysis? How do you detect the problem of multi-collinearity in the data set?
Q3b Run a multiple regression model using the following formulation and conduct a hypothesis test. The model is +) The data set is PINKHAM. Answer the following questions. a. State the null and alternate hypothesis for both slopes. Q41 1 Q41 2 Q43 1 Q43 2 3 | Page b. Compare P value at for, (Print Screen) c. What is r squared value and its interpretation? (Print Screen) a. Interpret the slopes for lag of sales and advertise(Print Screen) b. What will you state to your Sales Director after running the hypothesis test? . (Chapter 5) [2*5=10 points] Q4. Purchasing a car is a difficult decision. Car prices are a function of many variables such as mileage, age, foreign or domestic manufacture and engine technology utilized. Carefully read the dummy description for dummy engine and dummy foreign in the data table columns.
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