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Cars decat over me the accompanying dats show the prices of certains type of cared for sale by exis a sepaper One coluna gives the king ce in thousands of dedasi anda second cokane qen the son os Capas through DA OR OD He sai Ay egor Estimated Pro in meum of 1- Round to three decal peaces in needed) If there was a problem with the trear equation on part (C), do the residues bom this the p DO Do the reduggest a proten with the requ OA Yes because there is a cieved bent in the da Obecane thenea near hond in the da OCNo because there is a near bed in the da OD No because there a curved trendthed 10) Ft the equation Estimated Pice begge Make sure to ase natural logarth when bong the dats if there was a probem with the near egestion in pet ), o te redan from the the probem Ay Time Remaining
Cas deprecates over time The accompanying data show the pas of a cute type of card for sale by navduas in a newspaper Decke ges the skrg price on thousands of core and a second can gives the ag in years). Conpepar through Cack the son to vw the data there was a problem with the Ineer equation in pot (C do the reason this the prope OA There was no problem s the titt in partic OB No. because the residus from the log/Age) t appear more random OcYes, because the resda rom the logge a it appear more random O.D. Yes because carved poems can always be seed with a logice, or out anon (e) Compare the ted values from his equation with those from the fear model Show both the same cater. What does the graph have to say about the effects of increasing eg on sisate value? Choose the content graph OA Oc COD SUO What does the graph have to say abou cts of increasing ag OA The gestion eplin thuat price changes at a constant sate as cars age res? (C) from date o (c) APP BOLE
Gare depreciate over time The accompanying data show the prices of acetan type of car sted for se through h What does the graph have to say about the effects of excreasing agree? OA Thegion imples that price changes at a constant ac OB Tengation impes that price changes more pty among older used cars and remains nearly stacang used can OC The log equamples that price changes at an increasing rate as carsa cashensown as can ap in compare the values of and s between these two equations Does this comparson agree with your piss of the beer mode Should these smary seco logor Age 0-2 housand dlound to three decal places One nges the king pece On Boansodan anda second coume poes the age and Compa popt The gartress has Does the companon agree with you impression of the better model? OA Yes because tegession imples less unexplained variation even though , mes that the unexponed varian O Nobecaner in the game regression imples more unexplained vanation even though simples that the unplaned variation hty gee a sighly saler sca
CK the con tu view the d OA in because in the gathegression ingesuneplaned van even thom the the inexplaned vaaton sighty larger so sightly a sea Yes because in the games less et vanation and OD. No. because in the togethe regression amptes more unplaned variation and Should these summary states be compared Since the us interpret the intercept and open the equation Estimated Pre OA The copt should not be donated because it is 1 the e car that your or Thes OF THE should not be interpreted because in the poor OD. The intercept is the price of a car mats Y-year old The slop thi Compare the change in asking The price drop m moes that the unexplained vann o tes that he usoaned vrati compare these sy blogilos Choose the correct awer below 2 years old t cars that a or these tee changes because the ingedic region equation gerak And of an anda sem gives the new Compe car. The sope sh none in aga nuts a prce change of approately th, 100) and doar at ca The slope shows that a 1% no rests in a price change of prom noase age rutina p dience between cars that a 10 and 11 years old Use the equation with the tug of age as the explanatory vase this difference De tre or difere 100) da
pare these summ Age. Choose the variation even though se implies that the unexplained variation is on a slightly larger scale. variation even though s implies that the unexplained variation is on a slightly smaller scale. variation and se im - X variation and se in r old car. The slop t a 1% increase in old car. The slop a 1% increase in difference betwe on equation is Data table Age (years) 1 7 6 5 7 8 4 16 16 15 *** 10 14 14 12 16 Asking Price ($000) 21.1 8 7.3 12.5 6.1 5.1 12 0.6 0.5 2.15 3.2 3.55 1.75 1.75 2.95 4 n pproximately b, tho hd dollars. pproximately (b₁/10 lars. og of age as the ex
Cars depreciate over time. The accompanying data show the prices of a certain type of car listed for sale by individuals in a newspaper. One column gives the asking price (in thousands of dollars) and a second column gives the age (in years) Complete parts a through h Click the icon to view the data table CODE (a) Do you expect the resale value of a car to drop by a fixed amount each year? OA. No, because the resale value of a car is a random variable OB. No, because targer drops are expected in the first few years OC. Yes, because the resale value of a car depreciates at a fixed rate each year OD. Yes, because the resale value of a car is a random variable (b) Fit a linear equation with price as the response and age as the explanatory variable. What do the slope and intercept tell you, if you accept this equation's description of the pattern in the data? Estimated Price (in thousands of $) - Age (Round to three decimal places as needed) What do the slope and intercept tell you, if you accept this equation's description of the pattern in the data? OA. This equation's description of the pattern in the data is not accepted because the data appear to be strongly linear OB. This equation's description of the pattern in the data is not accepted because the data do not appear to be linear OC. This equation's description of the pattern in the data is accepted. The slope is the expected increase in price given an increase of 1 in age. The intercept is the expected value of price if age is zero Dint in nichts fem the line to this eidemanat a nezklame with thin bonne santion Chan the oth
Cars depreciate over time. The accompanying data show the prices of a certain type of car listed for sale by individuals in a newspaper One column gives the asking price (in thousands of dollars) and a second column gives the age (in years) Complete parts a through h Click the icon to view the data table. (c) Plot the residuals from the linear equation on age. Do the residuals suggest a problem with the linear equation? Choose the correct graph below OA О в. OC. ite Age (years) 00000 20 C Age (years) Do the residuals suggest a problem with the linear equation? ܟܐܐܚ 0000 Age (years) OD. 10 00006 Age (rear) 20 OA. Yes, because there is a curved trend in the data OB. Yes, because there is a linear trend in the data OC. No, because there is a linear trend in the data OD. No, because there is a curved trend in the data (d) Fit the equation Estimated Price bo+b,logAge Make sure to use natural logarithms when transforming the data. If there was a problem with the linear
Cars depreciate over time The accompanying data show the prices of a certain type of car listed for sale by individuals in a newspaper One column gives the asking price (in thousands of dollars) and a second column gives the age (in years) Complete parts a through h Click the icon to view the data table (d) Fit the equation Estimated Price=bo blogAge Make sure to use natural logarithms when transforming the data. If there was a problem with the linear equation in part (c), do the residuals from this fit for the problem? Estimated Price (in thousands of $)=+MogAge (Round to three decimal places as needed) If there was a problem with the linear equation in part (c), do the residuals from this fit "to the problem? OA. There was no problem with the linear fit in part (c). OB. No, because the residuals from the log(Age) fit appear more random OC. Yes, because the residuals from the log(Age) it appear more random OD. Yes, because curved patterns can always be fixed with a logarithmic, inverse, or root transformation (0) Compare the fitted values from this equation with those from the linear model Show both in the same scatterplot. What does this graph have to say about the effects of increasing age on resale value? Choose the correct graph below OA loos Q OB. Q OC. ✓ ✓ O D. a
Cars depreciate over time. The accompanying data show the prices of a certain type of car listed for sale by individuals in a newspaper One column gives the asking price (in thousands of dollars) and a second column gives the age (in years). Complete parts a through h Click the icon to view the data table (e) Compare the fitted values from this equation with those from the linear model Show both in the same scatterplot. What does this graph have to say about the effects of increasing age on resale value? Choose the correct graph below OA OB. Age (years) OC. NNNN Age (years) OD. Age (years) Age (years) What does this graph have to say about the effects of increasing age on resale value? OA. The log equation implies that price changes at a constant rate as cars age OB. The log equation implies that price changes more rapidly among older used cars, and remains nearly static among newer used cars OC. The log equation implies that price changes at an increasing rate as cars age OD. The log equation implies that price changes more rapidly among newer used cars, then slows as cars age Compare the values of ands hetween these fun anuatione Dnes this ronarienn anrop with unur impraction of the hotter model? Should theca comman
(1) Compare the values of r² and s between these two equations Does this comparison agree with your impression of the better model? Should these summary statistics be compared? Age S₂ = $thousand logAge 2 = Se = $thousand (Round to three decimal places as needed) and a The logarithmic regression has a Se Does this comparison agree with your impression of the better model? OA. Yes, because in the logarithmic regression implies less unexplained variation even though se implies that the unexplained variation is on a slightly larger scale OB. No, because in the logarithmic regression implies more unexplained variation even though s implies that the unexplained variation is on a slightly smaller scale OC. Yes, because in the logarithmic regression implies less unexplained variation and se implies that the unexplained variation is on a smaller scale D. No, because in the logarithmic regression implies more unexplained variation and s, implies that the unexplained variation is on a larger scale
Should these summary statistics be compared? Since the to compare these summary statistics. (g) Interpret the intercept and slope in the equation Estimated Price=bo + blogAge: Choose the correct answer below are it is OA. The intercept should not be interpreted because it is the price of a 0-year old car. The slope shows that a 1% increase in age results in a price change of approximately b, thousand dollars OB. The intercept is the price of a car that is 1-year old. The slope shows that a 1% increase in age results in a price change of approximately (b/100) thousand dollars OC. The intercept should not be interpreted because it is the price of a 0-year old car. The slope shows that a 1% increase in age results in a price change of approximately (b,/100) thousand dollars OD. The intercept is the price of a car that is 1-year old. The slope shows that a 1% increase in-age results in a price change of approximately b, thousand dollars (h) Compare the change in asking price for cars that are 1 and 2 years old to the difference between cars that are 10 and 11 years old. Use the equation with the log of age as the explanatory variable. Is this difference the same or different? The price drop is for these two changes because the logistic regression equation is
Data table Age (years) 1 7 6 5 7 8 4 16 16 15 10 14 14 12 16 Asking Price ($000) 21.1 8 7.3 12.5 6.1 5.1 12 0.6 0.5 2.15 3.2 3.55 1.75 1.75 2.95 - X