Discussion questions only please 4RFV%52. Graph the regression line on the same axes as your scatterplot.Discussion Questions1.Is the relationship a positive or a negative one? Explain how you can tell and what this means interms of weight and fuel efficiency.TInterpret the slope of the least squares line in terms of weight and fuel efficiency.Predict the fuel efficiency of a vehicle that weighs 4000 pounds. Include units.Should we predict the fuel efficiency of a vehicle that weighs 10000 pounds using the leastsquares line? Explain why or why not?5.Does the line seem to fit the data? Why or why not?6. What percentage of the variation in fuel efficiency is explained by its linear relationship withweight?G Search or type URL2.3.4.(06MacBook ProYHV RO7MUJ*800→I(-09K<O)ɔ.OP<>LEO11? 3E$RFV%65TGLab 12.3 Regression (Fuel Efficiency)Student Learning Outcomes• Calculate and construct the line of best fit between two variables.• Evaluate the relationship between two variables.Collect the Data1. 19 new vehicles were randomly selected. Their weight in pounds and fuel efficiency in miles pergallon were recorded in the following table:Weight (lbs) Fuel Efficiency (mpg)262021.0287523203215344034603570319031503440344040703730378052505424534522001615Table 12.11B21.022.821.418.718.114.324.422.82. Which variable should be the dependent variable, and which should be the independentvariable? Why?3. Construct a scatterplot of weight versus fuel efficiency. Plot the points. Label and scale the axes.Analyze the DataIEnter the data into your calculator. Write the linear equation, rounding to 4 decimal places.19.217.816.417.315.210.410.414.732.433.961. Calculate the following:a. a =b.b =C. T =d. n =e. 9=YMacBook ProH&7NUJ8MI(9KOV*OLP:;+tell[16●1

Since you have posted a question with multiple subparts, we will solve first three subparts for you. To get remaining subparts solved, please repost the question and mention the subparts to be solved. Regression is used to predict the variable based on the another. It has two regressors, they are slope and intercept. Slope is the changing variable in the regression equation. Intercept is the constant value in the regression equation. Given : The weight and fuel efficiency is calculated. Enter the data in excel - Click data - data analysis - Regression - Input X and Y and click ok. Output will be : Thus, the regression equation will be : y^=38.0110-0.0053x1. Given : From the output, R square is 0.7698 Then, r will be 0.7698=±0.877 Also, the slope sign is negative. Which shows the correlation value will be negative. Thus, there exist negative relationship between the weight and fuel efficiency. I.e. There exist strong positive correlation between the weight and fuel efficiency. 2. Given : From the output, The regression equation will be y^=38.0110-0.0053x Slope is -0.0053 Interpretation : If there exist one unit of weight in lbs then there exist decrease of 0.0053 times in fuel efficiency in mpg. 3. Given : The weight as 4000 pounds. Regression equation form the output will be : y^=38.0110-0.0053x Now, y^=38.0110-0.00534000=16.811 i.e. As the weight is 4000 pounds then the predicted value of fuel efficiency is 16.811 mpg