i need the answer quickly Q4// Evaluate the coefficient a, b from the below data using least square regression method, then computethe error of data.X234567y51015162714a21

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Answered: Q4// Evaluate the coefficient a, b from…

Elementary Linear Algebra (MindTap Course List)

8th Edition

ISBN:9781305658004

Author:Ron Larson

Publisher:Ron Larson

Chapter5: Inner Product Spaces

Section5.CM: Cumulative Review

Problem 21CM

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?
Cellular Phone Subscribers The table shows the numbers of cellular phone subscribers y in millions in the United States from 2008 through 2013. Source: CTIA- The Wireless Association Year200820092010201120122013Number,y270286296316326336 (a) Find the least squares regression line for the data. Let x represent the year, with x=8 corresponding to 2008. (b) Use the linear regression capabilities of a graphing utility to find a linear model for the data. How does this model compare with the model obtained in part a? (c) Use the linear model to create a table of estimated values for y. Compare the estimated values with the actual data.
Find the least-squares regression line treating square footage as the explanatory variable. y = (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.)
An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable. y=enter your response herex+enter your response here (Round the x coefficient to five decimal places as needed. Round the constant to two decimal places as needed.)
Interpret the least squares regression line of this data set. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. The correct least squares regression line for the data set is: y = 8.116x + 273.273 Use it to complete the following sentence: The least squares regression line predicts an additional annual rainfall if the average temperature of coastal waters increases by one degree millimetres of Celsius.
A company that manufactures computer chips wants to use a multiple regression model to study the effect that 3 different variables have on y, the total daily production cost (in thousands of dollars). Let B,, B,, and B, denote the coefficients of the 3 variables in this model. Using 22 observations on each of the variables, the software program used to find the estimated regression model reports that the total sum of squares (SST) is 485.84 and the regression sum of squares (SSR) is 229.91. Using a significance level of 0.10, can you conclude that at least one of the independent variables in the model provides useful (i.e., statistically significant) information for predicting daily production costs? Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places. (a) State the null hypothesis H, for the test. Note that the alternative hypothesis H, is given. H, :0 H, : at least one of the independent variables is useful…
An owner of a home in the Midwest installed solar panels to reduce heating costs. After installing the solar panels, he measured the amount of natural gas use y (in cubic feet) to heat the home and outside temperature x (in degree-days, where a day’s degree-days are the number of degrees its average temperature falls below 65F) over a 23-month period. He then computed the least squares regression line for predicting y from x and found it to be, ŷ=85+16x How much, on average, does gas used increase for each additional degree-day? The predicted amount of gas used when the outside temperature is 20 degree- days.
he scatter plot below shows the average cost of a patient staying one day in a hospital (with no surgery) in a sample of years between 2000 and 2015. The least squares regression line modeling this data is given by yˆ=−4815+3.765x. A scatterplot has a horizontal axis labeled Year from 2005 to 2015 in increments of 5 and a vertical axis labeled Price ($) from 2660 to 2780 in increments of 20. The following points are plotted: (2003, 2736); (2004, 2715); (2007, 2675); (2009, 2719); (2013, 270). All coordinates are approximate. Interpret the slope of the least squares regression line. Select the correct answer below: The average cost of a day in a hospital decreased by $3.765 each year between 2000 and 2015. The average cost of a day in a hospital increased by $3.765 each year between 2000 and 2015. The average cost of a day in a hospital decreased by $4815 each year between 2000 and 2015. The average cost of a day in a hospital increased by…
Isabelle is a crime scene investigator. She found a footprint at the site of a recent murder and believes the footprint belongs to the culprit. To help identify possible suspects, she is investigating the relationship between a person's height and the length of his or her footprint. She consulted her agency's database and found cases in which detectives had recorded the length of people's footprints, x, and their heights (in centimetres), y. The least squares regression line of this data set is: y = 2.488x + 114.001 omplete the following sentence: The least squares regression line predicts that someone whose footprint is one centimetre longer should be centimetres taller.
The least squares regression line for a set of data is calculated to be y = 24.8 + 3.41x. (a) One of the points in the data set is (4, 37). Calculate the predicted value. (b) For the point in part (a), calculate the residual.
To help schedule staffing and equipment needs, a large hospital uses a multiple regression model to predict its 'bed census' y, the number of beds occupied at the end of each day. Using hospital records from the most recent 29 days, a total of 4 independent variables are used to find the estimated regression model. Let B1, B2, B, denote the coefficients of the 4 variables in this model. A computer printout indicates that the error sum of squares (SSE) associated with the model is 35.42 and the corresponding regression sum of squares (SSR) is 35.66. Using a significance level of 0.10, can you conclude that at least one of the independent variables in the model provides useful (i.e., statistically significant) information for predicting daily bed census? Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places. (a) State the null hypothesis H, for the test. Note that the alternative hypothesis H, is given. 0. H, : at…

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Q4// Evaluate the coefficient a, b from the below data using least square regression method, then compute the error of data. X 2 3 4 6 7 y 5 10 15 16 21 27 1 4