Expert answer:Calculate the SSE for the quadratic regression fun

Answer & Explanation:Need help with the ones I got wrong. The other persons did not answer correctly.Question 10 / 20 pointsThe following table shows total forest and timber land in the United States in millions of acres in the indicated year.Year19621970197719871992Timberland759754737731737A scatter plot of this data is shown below.The horizontal variable is the number of years since 1962 and ranges between 0 and 30. Use quadratic regression to find a quadratic function to model the data. Enter your answer in the form y = ax^2+bx+c,where a, b, and c have been rounded to three decimal places.Important note: Do not include spaces in your answer and use the “^” symbol for exponentiation just as on the calculator.Answer:y=-65.504x^2+ 954.658x – 2114.460Question 20 / 20 pointsThe following table shows total forest and timberland in the United States in millions of acres in the indicated year.Year19621970197719871992Timber Land759754737731737Calculate the SSE for the quadratic regre

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ssion function (with coefficients rounded to three decimal places) from the previous question. Round your answer to one decimal place.Answer:0.036 X^2 -142.337 X +141432.488Question 30 / 20 pointsUse the quadratic regression function (with coefficients rounded to three decimal places) to estimate the acerage of timberland in 1982. Round your answer to one decimal place.Answer:627.2Question 420 / 20 pointsGiven four different data sets, a student calculates the quadratic regression as well as the R2 value for each using a TI-83. Which of these results models its respective data the best?Question options:a = 1.23b = -3.27c = 7.83R2 = 0.87394a = -3.745b = 9.524c = 12.105R2 = 0.1420a = 142.3629b = 204.2284c = -428.2079R2 = 0.9328a = 35.29b = 29.94c = -10.23R2 = 0.0139Question 520 / 20 pointsGiven the three points (0,2), (1,-3) and (2,-5) find the formula for the parabola that contains all three points.Question options:y = .05×2-.17x+.14y = .04×2-.16x+.14y = 1.5×2+6.5+2y = 1.5×2-6.5x+2

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