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each of the following: MMM confidence interval for the mean price at this age and 30% prediction interval for the price of an individual ear

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each of the following: MMM confidence interval for the mean price at this age and 30% prediction interval for the price of an individual ear at this won. Wren sentences that carefully interpert rach of the intervals (in tomine of car prices). 10. Experiment with sama transformations to attringt to find one that seems to do a better job of satisfying the larar model condition. Include the summary output for filing that model and a scatterplot of the criminal chin with the now mould (which is likely a curve on the original data). Explain why you think that this transformation does a does not improve satisfying the linear marked conditions. Il. According to your transformed marked, is there an age at which the car should be free? Ifan, and this nen and comment on what the "free car phenomenon says about the appropriateres of your model. 12. Apin sapper that you are interested in purchasing a car of this model that is four years old (in MIT). Determine each of the billowing using your model contracted in question it 907 confidence interval far the mean price at this age and 12 prediction interval for the price of an individual car at this up. Write salemers that carefully interpent each of the intervals (in terms of car prices]. MODEL #2: Van Milange as a predictor for Price 13. Cakedate the least sooners regression lime that but fits your data ( with Afilmage now is the predictor) and produce a semiburplot of the relationship with the regression linn on it. 14. Produce appropriate maidual plats and comment on how well your data appear to fit the caralitimes for a emple linger model Dha't worry about doing transformations at this point if there are problems with the 16. Experiment with some transformations to attempt to find one that seems to do a better job of satisfying the Three model condition. Include the summary output bar filing that model and a prattesplot of the original chain with this mow mould (which is bkaly a curve on the original data). Explain why you think that this transformation does or does not improve satisfying the linear model conditions. 10. How do the models, using ritter Agr or Afiimage as the predictor compare? Does one of the models worm "briser" or do they mam similar in their shillty to predict Print Explain

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