Q1. A college bookstore store sells hoodies. They want to price their hoodies to sell as many as possible during homecoming week. The table below gives the price (in $) of their hoodies and the weekly quantity they would sell at this price. Find the linear regression equation that gives the quantity of hoodies sold as a function of the price. Price 18 22 25 29 35 50 Quantity 175 153 140 131 115 95 Use your calculator to find the linear regression equation for this set of data. (a) The slope coefficient (rounded to 2 decimal places) is ????  (b) The y-intercept is ???? (c) Use the regression equation with coefficients as indicated above to determine the number of hoodies the bookstore can sell if the price is $39. (round your answer to the nearest whole number)

The table contains price-supply data and   price-demand data for corn. Find a linear regression model for the price-supply data where x is supply​ (in billions of​ bushels) and y is price​ (in dollars). Do the same for the price-demand data. Find the equilibrium price for corn.   Price ($/bu) Supply (billion bu) Price ($/bu) Demand (billion bu) 2.14 6.41 2.06 9.96 2.25 7.38 2.15 9.42 2.34 7.51 2.26 8.33 2.41 7.78 2.32 8.08 2.46 8.13 2.36 7.86 2.57 8.35 2.48 6.96   ...   Question content area right Part 1 Find a linear regression model for the price-supply data where x is supply​ (in billions of​bushels) and y is price​ (in dollars).   y=enter your response here ​(Type an equation using x as the variable. Round to two decimal places as​ needed.)

We run the following regression using a sample of 148 women living in the western states. The variable wage is the hourly wage ( in USD) and educ is the number of years of education completed.             wage  =  -3.07   +   1.52 educ         Which statement best described the estimated slope coefficient? Group of answer choices A 1.52 extra years of education is predicted to increase wage by 1 USD An extra year of education is predicted to increase hourly wage by 1.52 USD A 1 percent increase in education is predicted to increase wage by 1.52 percent A 1.52 percent increase in education is predicted to increase wage by 1

B-4 A toy store manager would like to know how the price can affect the sales of toys. In his data, he obtained 100 pairs of prices (unit: £) and volume of sales (unit: hundreds) for the toys. A simple linear regression was run with Sales as the dependent variable and Price as the independent variable with the following results. Regression Statistics R Square Adj. RSqr StErr of EST 0.876 0.767 0.701 4.184 Summary Table Variable Coeff. Std. Err Intercept 64.742 11.310 Price -2.645 0.602 (a) Write down the estimated regression equation. Explain this regression equation. (b) What's the value for R Square? Explain the meaning of this value. (c) Test the significance of the model at a=0.05 level. Write down the hypothesis you are testing, the statistic you use to evaluate the test, and your conclusion. (d) Use the regression output to construct a 99% confidence interval for the predicted sales when the price is set to be 15. (e) A colleague in the toy store claims that £1 increase in the…

Below is the actual data on the speed a person walks or runs in miles/hour and the calories the person burns per lap. Find the linear equation of best fit for this data. Compare the model to the data. Does the model seem to fit the data? Explain. What is the significance of the y-intercept? What is the slope and what does it mean? What is the x-intercept and what does it mean? What is the correlation coefficient and what does it mean? Speed (mph) Calories/lap 1 42 2 31 3 27 4 41 5 40 6 40 7 39 8 38 r answers to the nearest hundredth. The y-intercept means that if a person runs at ----------mph they will burn__________ per lap. The slope means that for each mph you increase your speed, you will burn an additional------------calories pay lap

Use the following information to answer the question. The following linear regression model can be used to predict ticket sales at a popular water park. Ticket sales per hour = -631.25 + 11.25(current temperature in °F) What is the predicted number of tickets sold per hour if the temperature is 86°F? Round to the nearest whole ticket. O About 336 tickets O About 252 tickets O About 276 tickets About 301 tickets

What is the explanatory variable,   what is the response variable. What is the regression equation for this data.   Plot the regression line in your calculator and draw it on your graph.   Interpret in context the slope.   Interpret in context the y-intercept.   What is the residual at 45 years of age.   Plot the residual plot on the axis to the right