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Linear Regression Analysis: Investigating Relationships Between Variables in Various Contexts - Document preview page 1

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Linear Regression Analysis: Investigating Relationships Between Variables in Various Contexts

Examination of linear regression for analyzing variable relationships.

Caleb Patterson
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Linear Regression Analysis: Investigating Relationships Between Variables in Various Contexts - Page 1 preview imageLinear Regression Analysis: Investigating Relationships Between Variables in VariousContextsProblem 1The Mean Corporation has been commissioned to conduct a study is into the relationship between the population of a city and thenumber of motorvehicle accidents in the city per year. A linear regression model is to be constructed. In the proposed regressionmodel, number of motor vehicle accidents per year is the response variable and population of the city is the explanatory variable.A random sample of 20 cities is selected and measurements are observed.Download the dataPopulation('000s)No. accidentsper year1,0304,1552,8906,6587402,9003,4407,3817303,2731,0103,7843,1906,6761,6205,0531,9005,2502,3106,2882,9607,1371,8405,0332,3806,2762,9407,3752,3905,5401,7905,2171,9805,6082,0105,7512,6205,9392,1206,076a)Calculate the point prediction for the valuex = 2,500. Give your answer as a whole number.y^=6197b)Give the 95% prediction interval for the valuex = 2,500. Give your answers as whole numbers.
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Linear Regression Analysis: Investigating Relationships Between Variables in Various Contexts - Page 3 preview image5429y^6966Problem 2An investigation has been conducted to determine whether there is a relationship between the salary paid toa Chief ExecutiveOfficer (CEO) and the productivity of that CEO as measured by the change in profits fromthe time the CEO was employed.The scatter plot plots the salary paid (x) against the change in profits (y) of a sample of CEOs. Withoutdoing any calculations and according only to this scatter diagram, a reasonable coefficient of correlation (r)between x and y would be:r =-1.25r =-0.59r = 0.68r = 1.35
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Linear Regression Analysis: Investigating Relationships Between Variables in Various Contexts - Page 4 preview image[2points]-3 of 11ID:MST.SLR.REE.07.0020Two variables (A and B) are hypothesisedto have a linear relationship with one another, as represented bythe following equation:A=β0+β1B +εData was gathered for these two variables and the correlation coefficient(r)was calculated to be-0.96.Select all from the followingstatements that are true:The graph of the linear relationship between A and B slopes up.Variable A is known as the explanatory variable, and variable B is known as the responsevariable.The linear regression line provides a strong fit to theobserved data.The proportion of variability in A that is explained by the regression model is equal to92.16%.Causation between A and B cannot be implied from the correlation that exists betweenthem.β0is known as the sampleintercept.Variable B causes variable A since B is the independent variable.
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