4. Predict the global sales of video games using their North American sales, European sales,and other sales. Looking at the output (under the Analysis of Variance (ANOVA) sectionof the output, look at the Regression" p-value), is this model significant?Regression EquationGlobal Sales = 0.3443 + 1.1099 NA.Sales + 1.1554 EU Sales+0.7459 Other SalesCoefficientsTermCoef SE Coef T-ValueConstant 0.3443 0.0770NA.Sales 1.1099 0.0212EU Sales 1.1554 0.0387Other Sales 0.7459 0.0814Analysis of VarianceSourceRegressionNA. SalesEU SalesOther SalesError496 728.0Lack-of-Fit 493 726.331.7499 18849.1Pure ErrorTotal4.4752.4129.869.16P-Value VIF0.0000.000 1.780.000 2.160.000 1.60DF Adj SS Adj MS F-Value P-Value3 18121.1 6040.37 4115.451 4031.3 4031.33 2746.6411308.8 1308.81 891.721 123.1 123.13 83.891.471.470.552.660.0000.0000.0000.0000.230

The regression analysis to predict the global sales based on their North American sales, European…

Answered: 4. Predict the global sales of video…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 64?
ABC, Inc., sells tea products to various customers. In recent years, profits have been declining. The CFO of the company investigated the reasons for the profit decline and performed regression analysis for sales and costs. She determined that sales depend on product price, delivery speed, customer services, and marketing expenses. She also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales.Question 1:1. Define regression analysis, simple regression, and multiple regression. Identify one example of each in this scenario.
A nonprofit analyst considered two independent variables as a predictor for the dependent variable Commitment, the percent of total expenses that are allocated to charitable services. The independent variables are Revenue, total revenue in billions of dollars, andEfficiency, the percent of private donations remaining after fundraising expenses. The regression analysis resulted in this ANOVA table. Determine whether there is a significant relationship between commitment and the two independent variables at the 0.01 level of significance. Source Degrees of Freedom Sum of Squares Mean Square F p-value Regression 2 3640.0416 1820.02 51.0429 <.0001 Error 87 3102.1301 35.66 Total 89 6742.1717 Determine the p-value. The p-value is ________ (Round to three decimal places as needed.)
The condition of an independent variable being correlated to one or more other independent variables is referred to as nonlinearity. statistical significance. multicollinearity. linearity.
ABC, Inc., sells tea products to various customers. In recent years, profits have been declining. The CFO of the company investigated the reasons for the profit decline and performed regression analysis for sales and costs. She determined that sales depend on product price, delivery speed, customer services, and marketing expenses. She also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales.Question: List two advantages and two limitations of regression analysis.
Ordinal data cannot be analyzed using regression analysis. True False
Infant Mortality Rate. A social scientist wants to predict the infant mortality rate in cities in the United States. a. Suggest five predictor variables (characteristics associated with a city) that might be useful in predicting infant mortality rate. b. Write the multiple linear regression model for the conditional mean of the response variable, infant mortality rate.
According to an article, one may be able to predict an individual's level of support for ecology based on demographic and ideological characteristics. The multiple regression model proposed by the authors was the following. y = 3.60-.01x₁+.01.₂-.07x3+.12x4+.02xs-.04x6-01-.04.xg-.02.xg+c The variables are defined as follows. y = ecology score (higher values indicate a greater concern for ecology) X₁ = age times 10 x₂ = income (in thousands of dollars) x3 = gender (1 = male, 0 = female) X4 = race (1 = white, 0 = nonwhite) X5 = education (in years) x6 = ideology (4 = conservative, 3 = right of center, 2 = middle of the road, 1 = left of center, and 0 = liberal) X7 = social class (4 = upper, 3 = upper middle, 2 = middle, 1 = lower middle, 0 = lower) xg = postmaterialist (1 if postmaterialist, 0 otherwise) x9 = materialist (1 if materialist, 0 otherwise) (a) Suppose you knew a person with the following characteristics: a 30 year old, white female with a college degree (20 years of…
According to an article, one may be able to predict an individual's level of support for ecology based on demographic and ideological characteristics. The multiple regression model proposed by the authors was the following. y = 3.60-.01.x₁ +.01.x2-.07x3+.12x4+.02xs-.04x6-.01x7.04x8-.02xg+e The variables are defined as follows. y = ecology score (higher values indicate a greater concern for ecology) x₁ = age times 10 x₂ = income (in thousands of dollars) x3 = gender (1 = male, 0 = female) X4 = race (1 = white, 0 = nonwhite) X5 = education (in years) x6 = ideology (4 = conservative, 3 = right of center, 2 = middle of the road, 1 = left of center, and 0 = liberal) X7 = social class (4 = upper, 3 = upper middle, 2 = middle, 1 = lower middle, 0 = lower) x8 = postmaterialist (1 if postmaterialist, 0 otherwise) x9 = materialist (1 if materialist, O otherwise) (a) Suppose you knew a person with the following characteristics: a 30 year old, white female with a college degree (20 years of…
4 A certified financial planner would like to examine the relationship between the age of her clients and the total amount of money they have in their investment accounts. The ages of clients and corresponding account balances for a sample of 15 clients appears in the table. Use the regression analysis output from Excel to determine if there is a positive linear relationship between age of client and investment account balance. Test using a significance level of .01. Balance Age ($1000s) 34 38 57 87 44 129 Coefficients Standard Error t stat 183.89 3.522 56 342 Intercept X variable -226.69 50 770 -1.23 2.87 10.104 44 200 54 430 39 55 67 453 29 76 43 230 76 427 m ib 43 188 70 546 275 Linear Regression and Correlation

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