12. The table below shows the distance travelled in an airplane flight as it relates to the ticket costfor that flight.Miles37511251525175021502400Ticket Cost ($)56.1131164226231263a) Based on this data, is there a correlation between the distance of the flight and the ticket cost? Ifso, describe the shape and strength of this correlation.b) Find the regression equation for this data.c) Put the regression equation into the context of the problem. What do you know about thisrelationship based on the equation?d) What do the r and r? values tell you about this equation. (Make sure to give the values for theseas well as the descriptions.)e) What would you estimate the ticket price for a 750-mile flight?

Data is given for miles and ticket cost, We have to calculate regression equation and correlation.

Answered: 12. The table below shows the distance…

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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i need computerized perfect solution not handdwritten
5. The table below shows varying prices of music sold on a streaming service. Determine the linear regression to estimate the weekly sales of albums sold, use your regression to estimate the weekly sales if the price is $9 per album, and state the correlation coefficient, r, and interpret its meaning in the context of this problem. Price ($) Weekly sales (in thousands) $8 440 $8.50 380 $10 $11.50 250 180
A researcher is investigating possible explanations for deaths in traffic accidents. He examined data from 2000 for each of the 52 cities randomly selected in the US. The variables were death and income. Deaths: The number of deaths in traffic accidents per cityIncome: The median income per city The researcher ran a simple linear regression model: Deaths = Bo+B1(Income). Results shown in photo below. Question: Please help me better understand how to use results from photo to find value of R-squared of this simple linear regression model.
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Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
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