In regression, the variable predicted is called the regression variable independent variable dependent variable predictor

Regression analysis is a powerful statistical tool that helps us uncover relationships between…

Answered: In regression, the variable predicted…

Understanding Business

12th Edition

ISBN:9781259929434

Author:William Nickels

Publisher:William Nickels

Chapter1: Taking Risks And Making Profits Within The Dynamic Business Environment

Section: Chapter Questions

Problem 1CE

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Stores in Minneapolis were looted and damaged in May of 2020 due to rioting caused by police killing of George Floyd. Many stores will be closed while remodeling resulting in a loss of sales. This type of variation in sales is called Multiple Choice cylical seasonal episodic residual
Which of the following is TRUE regarding the two smoothing constants of the Forecast Including Trend (FIT) model? Select one: a. One constant smoothes the regression intercept, whereas the other smoothes the regression slope. b. One constant is positive, while the other is negative. c. They are called MAD and cumulative error. d. Their values are determined independently. e. Alpha is always smaller than beta.
answer a,b,c
Consider the following OLS regression results, 9-10.46+0.271x, R² -0.13. Calculate the predicted value of y when x is equal to 16. Round to the nearest tenth (one decimal place).
bex Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 3.136512 0.964065 0.985521 0.971252 0971252 Given the above regression statistics, what is the value of the coefficient of determination? 0.964065 3.136512
Regression analysis is a powerful and commonly used tool in business research. One important step in regression is to determine the dependent and independent variable(s). In a bivariate regression, which variable is the dependent variable and which one is the independent variable? What does the intercept of a regression tell? What does the slope of a regression tell? What are some of the main uses of a regression? Provide an example of a situation wherein a bivariate regression would be a good choice for analyzing data. Justify your answers using examples and reasoning.
A company hires you to develop a linear regression forecasting model. Based on the company's historical sales information, you determine the intercept value of the model to be 1,500. You also find the slope value is -25. If after developing the model you are given a value of X = 8, which of the following is the resulting forecast error using this model if the actual sales is 1250?
The number of auto accidents in Athens, Ohio is related to the regional number of regisgtered automobiles in thousands (X1) alcholic beverage sales in $10,000 (X2) and rainfall in inches (X3). Furthermore the regression formula has been calculated as: y=a+b1X1+b2x2+b3X3 where y= number of automobile accidents a= 8.0 b1= 3.5 b2=5.0 b3= 2.4 For the given values of X1,X2, and X3, the expected number of accidents will be ( round your responses to one decimal place) X1 X2 X3 # of accidents 6.0 7.0 0.0 [__]
Please help me with thirdly part 1,2, and 3
Solve for the y-intercept and the slope. Form the equation of the regression line that describes the relationship between the two variables. Predict the profit of the fashion boutique business when the store measures 3,800 square feet. Explain the result.
In multiple regression analysis, testing the significance of individual regression coefficients is based on A t statistic A z statistic An F statistic

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		regression variable
		independent variable
		dependent variable
		predictor