9 students were surveyed to see what their age is and what their income level is. Find the equation of the line using linear regression. Wewant to predict their age using their income.age182438221935281927income4567868358556452445871400975Just a side note, the 19 year old is making 1400, would be considered an outlier since they are making way more than everyone else.(y=-.0061x+34.9874 4 decimals)y=30.3709-.0064

Answered: Image /qna-images/answer/eb07430b-813f-4c0a-b902-337c0dc951c5.jpg

Answered: 9 students were surveyed to see what…

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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2. The table below lists the annual land-line phone cost per costumer: Year 2012 2013 2014 2015 Cost ($) a. 692 610 Find a linear regression model for this data b. Interpret the slope of the model 580 C. Predict the annual land-line phone cost per customer in 2022 495 2016 434
A researcher knows that people with higher annual salaries commit fewer crimes. He is creating a regression model to predict the number of crimes a person will commit based on their salary Based on this information alone which of the following MUST be the slope of the regression line choose one 1.00 or 0.50 or -0.50
Answer d,e and f
Illustrate the importance of using regression models.
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
Most people know that their chances of getting cancer increase as they age. In fact, by looking at data compiled by the National Cancer Institute you can readily see that incidence of cancer increases dramatically between the ages of 35 and 80. Medicine Students initially assumed that this relationship is linear with R = 0.80. Are the students correct? Test if the data fits better to other models.
Below is the actual data on the speed a person walks or runs in miles/hour and the calories the person burns per lap. Find the linear equation of best fit for this data. Compare the model to the data. Does the model seem to fit the data? Explain. What is the significance of the y-intercept? What is the slope and what does it mean? What is the x-intercept and what does it mean? What is the correlation coefficient and what does it mean? Speed (mph) Calories/lap 1 42 2 31 3 27 4 41 5 40 6 40 7 39 8 38 r answers to the nearest hundredth. The y-intercept means that if a person runs at ----------mph they will burn__________ per lap. The slope means that for each mph you increase your speed, you will burn an additional------------calories pay lap
M3
Q1) A real estate consultant is considering developing a series of price models for residential houses in different areas of the province of Ontario, in Canada. The dataset, provided by the Windsor and Essex County Board, covers residential home sales in Windsor. To develop the model, the consultant performs a linear regression to estimate the price (in Canadian dollars) as a linear function of the size of the apartment (in square feet) and obtains the following Excel result. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.53580413 0.28708607 0.28577556 41101.9362 546 ANOVA df MS Significance F 1 3.70082E+11 3.7008E+11 219.065461 6.74643E-42 Regression Residual Total 544 9.19017E+11 1689369158 545 1.2891E+12 Coefficients Standard Error 62171.5874 4537.036582 13.7031268 6.2969E-37 53259.33066 71083.8441 t Stat P-value Lower 95% Upper 95% Intercept LOTSIZE 12.0187669 0.81203165 14.8008601 6.7464E-42 10.42366523 13.6138685 a) Write…
what slope represents the linear regression
Is it reasonable to interpret the y-intercept of the regression line? Why or why not? One home that is 1,750 square feet is listed at $590,000. Is this home's price above or below average for a home of this size? Use residuals and show your work to answer. footaget) ## (Intercept) 21.14411 136.31449 0.155 0.87954 ## footage 0.28388 0.08516 3.333 0.00667 ** ## Residual standard error: 71.64 on 11 degrees of freedom ## Multiple R-squared: 0.5025, Adjusted R-squared: 0.4573 ## F-statistic: 11.11 on 1 and 11 DF, p-value: 0.006671
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through o. Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs OxBillable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly Overhead Costs and Billable Hours Data Overhead Costs $385,000 Billable Hours 3,000 $425,000 4,000 $445.000 5,000 $497,000 6,000 $570,000 7,000 $590,000 8,000

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