3. Correlation and linear regression 3. An architect wants to determine the relationship between the heights (in feet) of a building and thenumber of stories in the building. The data for a sample of 10 buildings are shown below. Explainthe relationship.Stories 64 54 40 31 45 38 42 4137 40Height 841 725 635 616 615 582 535 520 511 485

make a table for the given data as follows Stories (x) height (y) 64 841 54 725 40 635 31…

Answered: An architect wants to determine the…

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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The least-squares regression equation is y = 743.3x+ 12,990 where y is the median income and x is the percentage of 25 years and older with at least a bachelor's degree in the region. The scatter diagram indicates a linear relation between the two variables with a correlation coefficient of 0.7921. Complete parts (a) through (d). 55000- 20000- 15 20 25 30 35 40 45 50 55 60 Bachelor's % (a) Predict the median income of a region in which 20% of adults 25 years and older have at least a bachelor's degree. $ (Round to the nearest dollar as needed.) Median Income
Demand for Smartphones The following table shows worldwide sales of a type of phone and their average selling prices in 2012, 2013, and 2017. Year 2012 2013 2017 Selling Price p ($100) 4 3 2 Sales q (billions) 0.7 1 2 Find the regression line (round coefficients to one decimal place). q(p) = Use the regression line to estimate the demand (in millions of units sold) when the selling price was $350. million
How do you check the equal spread condition for simple linear regression? O Check to see if the normal quantile plot has a funnel shape. O Check to see if the normal quantile plot displays a line. O Check to see if the residual versus predicted plot displays a curve. O Check to see if the residual vs. predicted plot has a funnel shape.
The tables show the amount of revenue (y) in billions for different companies x years after 2005. Match the table with the correct description of its regression model and correlation. Negative Linear Regression 1. a0 1 2 3 4 5 6 78 9 10 Strong Negative Correlation y 12 12 13 14 15 16 18 19 21 22 25 Positive Linear Regression * 0 1 2 3 4 5 6 7 89 10 y 20 18 17 15 13 14 16 18 21 25 28 2. Strong Positive Correlation Quadratic Regression * 0123 4 5 6 7 8 9 10 3. Strong Positive Correlation y 5679 13 15 18 24 25 28 30 Increasing Exponential Regression 4. x0 1 2 3 4 5 6 789 10 Strong Positive Correlation y 20 20 19 18 16 15 12 8765 Decreasing Exponential Regression z0 1 2 3 4 5 6 7 8 9 10 5. Strong Negative Correlation y 20 19 20 18 16 15 13 11 10 11 10
1. Sue is conducting a regression analysis to predict the amount of salaries expense using the number of employees and the average rate of pay. This type of regression analysis is called a(n) independent regression. linear regression. multiple regression. dependent regression.
can you please help with questions a-e i need help
A statistical program is recommended. Consider the following data for two variables, x and y. 24 26 30 22 35 40 y 13 22 33 34 41 35 (a) Develop an estimated regression equation for the data of the form ŷ = b, + b,x. (Round b, to one decimal place and b, to three decimal places.) (b) Use the results from part (a) to test for a significant relationship between x and y. Use a = 0.05. Find the value of the test statistic. (Round your answer to two decimal places.) F = Find the p-value. (Round your answer to three decimal places.) p-value = Is the relationship between x and y significant? O Yes, the relationship is significant. O No, the relationship is not significant. (c) Develop a scatter diagram for the data. y 45 y 45 y 45 y 45 T 40 40- 40 40 35 35- 35 35 30 30 30 30 25 25 25 25 20 20 20 20 15 15 15 15 10 10 10 10 5. 5. 5. 5 20 25 30 35 40 45 20 25 30 35 40 45 20 25 30 35 40 45 20 25 30 35 40 45 Does the scatter diagram suggest an estimated regression equation of the form ý = b, + b,x…
(1) Write out the regression equation (2) What is the sample size used in this investigation? (3) Determine the values of *, ** and ***, ****
The correlation coefficient between midterm and final scores in a large statistics class is r=0.6. A scatterplot of the two variables is football shaped. A particular student has a midterm score that is 0.5 SDs below the average midterm score of all students. Using regression, we would predict that the student's final score is _________ SDs _________ the average final score of all students and therefore at the _________ percentile of final scores of all students.
Simple linear regression model helps to adjust out the effects of confounding factors in a statistical analysis. A. TrueB. FalseC. None of the above choices
Oil Recovery A U.S. state's Bureau of Economic Geology published a study on the economic impact of using carbon dioxide enhanced oil recovery (EOR) technology to extract additional oil from fields that have reached the end of their conventional economic life. The following table gives the approximate number of jobs for the citizens that would be created at various levels of recovery. Percent Recovery (%) 20 Jobs Created (Millions) Find the regression line. ()-0.135x+5.15 x Need Help? Submit Answer Use the regression line to estimate the number of jobs (in millions) that would be created at a recovery level of 70%. x million jobs Read It 8 Watch It 40 80 100 11 14 20
Independent variable data is listed in cells B2 through B100, and dependent variable data is in cells C2 through C100. Which spreadsheet function would calculate the slope of a linear regression model of this data? Group of answer choices =SLOPE(B2:B100,C2:C100) =SLOPE(C2:C100,B2:B100) =SLOPE(B2,C2) =SLOPE(C2,C100,B2,B100)

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An architect wants to determine the relationship between the heights (in feet) o number of stories in the building. The data for a sample of 10 buildings are she the relationship. Stories 64 54 40 31 45 38 42 41 37 40