A scatter diagram is given with one of the points drawn in blue (large point) The line drawn inred (dashed line) is the least-squares regression line with the point in blue (the large point)excluded. The line drawn in blue (solid line) is the least-squares regression line with the point inblue (large point) included. On the basis of these graphs, do you think the point in blue is influential?CHEIs the point in blue (large point) influential?Yes, because the point significantly affects the least-squares regression line.Yes, because the point does not significantly affect the least-squares regression line.No, because the point does not significantly affect the least-squares regression line.No, because the point significantly affects the least-squares regression line.2015104S0$25D 1015oRO

The regression shows a relationship between two variables.

Answered: A scatter diagram is given with one of…

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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A least squares line for a sample with 11 observations has an SSE = 192; calculate and s. Please show your work So i can understand how you arrived at the answer
Please answer as many as your allowed too. Thank you :) A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.68b=0.168 (a) Write the equation of the Least Squares Regression line of the formˆyy^= + x(b) Which is a possible value for the correlation coefficient, rr? -1.417 1.417 0.702 -0.702 (c) If a country increases its life expectancy, the happiness index will increase decrease (d) If the life expectancy is increased by 0.5 years in a certain country, how much will the happiness index change? Round to two decimal places.(e) Use the regression line to predict the happiness index of a country with a life expectancy of 69 years. Round to two decimal places.
A random sample of eight drivers insured with a company and having similar auto insurance policies was selected. The following table lists their number of driving violations (in past two years) and monthly auto insurance premiums. Number of Driving Violations Monthly Insurance Premium ($) 44 (a) Find the estimated least squares regression line. (b) Interpret the estimated slope value. (c) Calculate the coefficient of determination (r) and interpret the result. (d) Test the regression coefficient with six necessary steps mentioning appropriate hypothesis at the 1% significance level. 4 1 3 7 24 68 20 33 28 50 70
The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4 months: Month Number of Accidents Jan 25 Feb 40 Mar 60 Apr 90 Using the least-squares regression method, the trend equation for forecasting is (round your responses to two decimal places): ŷ-0-0x Using least-squares regression, the forecast for the number of accidents that will occur in the month of May = accidents (enter your response as a whole number).
An article on the cost of housing in California that appeared in the San Luis Obispo Tribunet included the following statement: "In Northern California, people from the San Francisco Bay area pushed into the Central Valley, benefiting from home prices that dropped on average $4000 for every mile traveled east of the Bay area." If this statement is correct, what is the slope of the least-squares regression line, ý = a + bx, where y = house price (in dollars) and x = distance east of the Bay (in miles)? Your answer cannot be understood or graded. More Information
You forgot to JUSTIFY THE ANSWRRS LAST TIME
A scientific foundation wanted to evaluate the relation between y= salary of researcher (in thousands of dollars), x1= number of years of experience, x2= an index of publication quality, x3=sex (M=1, F=0) and x4= an index of success in obtaining grant support. A sample of 35 randomly selected researchers was used to fit the multiple regression model. Parts of the computer output appear below. The least squares line fitted to the data is: salary = 2.001 + 0.33 x1 + 0.04 x2 + 0.69 x3 + 0.30 x4 + ε salary = 17.85 + 1.10 x1 + 0.32 x2 + 1.59 x3 + 1.29 x4 + ε salary = 2.001 + 0.33 x1 + 0.04 x2 + 0.69 x3 + 0.30 x4 salary = 17.85 + 1.10 x1 + 0.32 x2 + 1.59 x3 + 1.29 x4
A financial analyst is examinıng the Pela each the company's current stock price and the company's earnings per share reported for the past 12 months. Her data are given below, with x denoting the earnings per share from the previous year, and y denoting the current stock price (both in dollars). Based on these data, she computes the least-squares regression line to be y = -0.147+0.043x. This line, along with a scatter plot of her data, is shown below. Earnings per Current stock price, y (in dollars) share, x (in dollars) 36.55 1.64 14.18 0.57 41.79 1.37 39.16 1.10 2.5+ 57.70 2.71 26.95 0.90 32.65 1.70 41.94 1.17 52.79 2.56 42.72 2.01 16.89 0.76 22.46 0.58 Earnings per share, x (in dollars) 58.88 2.19 30.13 1.48 50.08 1.73 28.92 0.81 Submit Assi Continue D 2021 McGraw-H Education. All Rights Reserved. Terms of Use Privacy e to search 近 Current stock price, y (in dollars)
Explain why it can be dangerous to use the least-squares line to obtain predictions for x values that are substantially larger or smaller than those contained in the sample. The least-squares line is based on the x values ---Select--- ✓the sample. We do not know that the same linear relationship will apply for x values ---Select--- the range of values in the sample. Therefore the least-squares line should not be used for x values ---Select--- the range of values in the sample.
An engineer is testing a new car model to determine how its fuel efficiency, measured in L/(100 km), is related to its speed, which is measured in km/hour. The engineer calculates the average speed for 30 trials. The average speed is an example of a (statistic or parameter) The engineer would like to find the least squares regression line predicting fuel used (y) from speed (x) for the 30 cars he observed. He collected the data below. Speed 62 65 80 82 85 87 90 96 98 100 Fuel 12 13 14 13 14 14 15 15 16 15 Speed 100 102 104 107 112 114 114 117 121 122 Fuel 16 17 16 17 18 17 18 17 18 19 Speed 124 127 127 130 132 137 138 142 144 150 Fuel 18 19 20 19 21 23 22 23 24 26 The regression line equation is Round each number to four decimal places.

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