An train station has determined that the relationship between the number of passengers on a train and the total weight of luggage stored in the baggage compartment can be estimated by the least squares regression equation y = 125 + 21x. Predict the weight of luggage for a train with 149 passengers. Answer: pounds Preview My Answers Submit Answers
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- An bus station has determined that the relationship between the number of passengers on a bus and the total weight of luggage stored in the baggage compartment can be estimated by the least squares regression equation y=115+24xy=115+24x. Predict the weight of luggage for a flight with 60 passengers. Answer: pounds SpeakAn airline has determined that the relationship between the number of passengers on a flight and the total weight of luggage stored in the baggage compartment can be estimated by the least squares regression equation y= 217+22x. Predict the weight of luggage for a flight with 72 passengers. Answer: ? poundsAn train station has determined that the relationship between the number of passengers on a train and the total weight of luggage stored in the baggage compartment can be estimated by the least squares regression equation ?=134+26?y=134+26x. Predict the weight of luggage for a flight with 73 passengers.
- An automotive engineer computed a least-squares regression line for predicting the gas mileage (y) in miles per gallon of a certain vehicle from its speed (x) in miles per hour. The result is y = -0.14x+ 38.78. Predict the gas mileage when the vehicle is travelling at 55 miles per hour. Round your answer to one decimal place. Only write a number as your answer.Where is the quadratic model for the data?An airline has determined that the relationship between the number of passengers (x) on a flight and the total weight (y) (in pounds) of luggage stored in the baggage compartment can be estimated by the least-squares regression equation y = 250 + 27x. Predict the weight of luggage for a flight with 125 passengers.
- Write a multiple regression equation that can be used to analyze the data for a two-factorialdesign with two levels for factor A and three levels for factor B. Define all variables.A real estate company wanted to see the relationship between home prices and square footage of homes for sale. The regression line is ŷ = –802,456 + 144x, where x is the square footage of a home. Complete the statement based on the information. For every -square-foot increase, the predicted home price is predicted to increase by $The number of megapixels in a digital camera is one of the most important factors in determining picture quality. But, do digital cameras with more megapixels cost more? The following data show the number of megapixels and the price ($) for 10 digital cameras(Consumer Reports, March 2009). Would you feel comfortable using the estimated regression equation developed to predict the price of a digital camera given the number of megapixels? Explain. Brand and Model Megapixels Price (S) Canon PowerShot SD1100 IS Casio Exilim Card EX-510 180 200 230 8 10 Sony Cyber-shot DSC-170 Pentax Optio M50 Canon PowerShot Gl10 8 120 470 15 Canon PowerShot A590 IS 8 140 Canon PowerShot El Fujifilm FinePix FOOFD Sony Cyber-shot DSC-W170 Canon PowerShot A470 10 12 180 310 10 250 110
- Write the equation of the least-squares regression line. Use the full accuracy shown in the calculator output (do not round your answers).Explain the value of the coefficient of determination and the overall significance of the model. Write the resulting regression equation.Write down the different Multiple Regression Equations?