Using the revenue data for Yaster Inc. for the past few years, we apply linear regression to the datato find a modely = 33.2 x 78.75,where y is Yaster's annual revenue in billions of US dollars, and a is the number of years since 2010.Use this model, together with the revenue model you found for Amazon to answer the questionbelow.When will Yaster's revenue overtake Amazon?Note: I am asking for the year, not the number of years since 2010. This may happen between twoyears. Round to the nearest year. Amazon RevenueThe annual revenue of Amazon is given in the table below (source ).Year20202019201820172016201520142013201220112010Amazon AnnualRevenue(Billions of US dollars)386.064280.522232.887177.866135.987107.00688.98874.45261.09348.07734.204See the Regression page in the Chapter 1: Linear Equations and Graphs module for details oncreating a regression model.Apply linear regression to the data in the table to find a modely = mx + b,where y is Amazon's annual revenue in billions of US dollars, and is the number of years since2010.

The revenue data for Yaster Inc. for the past few years, the linear regression model is…

Answered: Using the revenue data for Yaster Inc.…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Suppose that the regression equation that estimates the value of a car (in dollars) based on its age (in years) is given by: Predicted Value = 21375 - 1215 Age. You have an 8-year old car. How much is it worth?
Imagine Daenerys Targaryen as a researcher concerned with the dragon species. The people of Westeros believed that dragons were decreasing in size due to captivity. Dragon size was normally measured as wingspan (meters) and captivity was normally measured in years. Daenerys used archival data and determined that the relationship between these two variables could be explained using the following regression equation: y-predicted = 453 - 2.5xInterpret this equation (i.e. What is its purpose? What is the intercept? What is the slope? What does it mean for dragons in Westeros?).
Please only answer “d” and “e” as I already have the other parts filled out. Thank you!
1. Develop a simple linear regression equation for starting salaries using an independent variable that has the closest relationship with the salaries. Explain how you chose this variable.
You estimate a regression equation that estimates individuals’ yearly income as a function of age (measured in years), years of education, and their score on a standardized intelligence exam (IQ test). The estimated coefficients are: I = 26.3 + 4.21*Age + 7.21*Education + .23 * IQ Where I is income measured in thousands of dollars. Based on the regression results, how much more should an individual earn after attending graduate school for two years? Explain your reasoning.
What needs to change in an overall problem if one wants to use linear regression?
Please answer parts d, e and f.
This question has do with linear regression.If I consider attendance in a class versus final grade in the class can you explain where there is a positive and when there is a negative relationship between them.
A professor in the School of Business in a university polled a dozen colleagues about the number of professional meetings they attended in the past five years (x) and the number of papers they submitted to refereed journals (y) during the same period. The summary data are provided. Fit a simple linear regression model between x and y by finding out the estimates of intercept and slope. Comment on whether attending more professional meetings would result in publishing more papers. n n n = 12, x = 4, y = 12, X₁Y₁ = 320 i=1 x² = 234, i=1 The estimated regression line is y = 36.4 + (-6.10 )x. (Round to two decimal places as needed.) Comment on whether attending more professional meetings would result in publishing more papers. Let it be unclear that attending more professional meetings affects the number of published papers if the value used to make that determination is between 1 and 1. Because the of the regression equation is it would appear that attending more professional meetings ▼
Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year. Year Number of Patients Robbery Rate per 1,000 Population The simple linear regression equation that shows the best relationship between the number of patients and the robbery rate is (round your responses to three decimal places) where y Number of Patients and x = Robbery Rate. = 1 2 3 4 6 7 36 33 40 41 55 60 58.3 61.1 73.4 75.7 81.1 89.0 101.1 5 40 8 54 94.8 9 58 103.3 10 61 116.2
The mall has a set of data with employee age (X) and the corresponding number of annual on-the-job-accidents(Y). Analysis on the set finds that the regression equation is Y=100-3X. What is the likely number of accidents for someone aged 30? 97 100 10 none of the above
The number of Master’s degrees granted at a particular university is given for selected years in the table below. Year 2005 2010 2015 2020 Number of Master’s Degrees 58 69 76 83 Use the linear regression equation for this data to predict the number of Master’s degrees that this university will grant in the year 2021. Blank 1. Calculate the answer by read surrounding text. Round to the nearest whole number of Master's degrees.

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