LINEAR REGRESSIONSean is hiking the Appalachian Trail from Georgia to Maine. The distance of his hike is 2200 miles. Ittook Sean 134 days to complete the hike. The data below represent the distance, D, he had hiked tdays after the start of his trip.19346791112134D()30857810701715190222001. Determine the linear regression equation for this data.Linear Regression Equation: D =Round to the nearest tenth as needed.2. Interpret the meaning of the slope of this regression model.Sean hiked at a rate of approximatelySelect an answer v3. Use your linear regression equation to estimate the total number of miles Sean had hiked in 63days. Round your answer to the nearest mile.In 63 days, Sean had hikedmiles.4. Use your linear regression equation to estimate the total number of days it took for Sean to hike309 miles. Round your answer to the nearest day.Indays, Sean had hiked 309 mniles.P Type here to search Linear Regression - Christmas TreesThe following table gives the total number of live Christmas trees sold, in millions, in the UnitedStates from 2004 to 2011. (Source: Statista.com).t=number of years since2004C= total number of24617Christmas trees sold in the27.128.628.22730.8U.S. (in millions)1. Use the TABLE to determine the number of live Christmas trees sold in the year 2008.In 2008, there were approximatelymillion live Christmas trees sold in theU.S.2. Determine the linear regression equation that models the set of data above. Use the indicatedvariables and proper function notation. Round to the nearest hundredth as needed.C =3. Interpret the meaning of the slope of your (rounded) regression model.From 2004 to 2011, the number of Christmas trees sold in the U.S. increased byapproximatelymillion trees each year.4. Use the REGRESSION EQUATION to determine the number of live Christmas trees sold in theyear 2008.In 2008, there were approximatelymillion live Christmas trees sold in theUS.5. Your answers to parts 1 and 4 should be different. Why is this the case?O The data are not perfectly linear. The regression equation gives a more precise answer thanthe value from the table.O The data are linear. The regression equation gives a more precise answer than the valuefrom the table.O The data are not perfectly linear. The regression equation gives only an approximation ofthe actual value, not the exact value.O The data are linear. The regression equation gives only an approximation of the actualvalue, not the exact value.Type here to search

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