Below is a scatter plot and a quadratic regression provided by desmos. What type of regression would be better to do for these points and why? Explain in terms of the peaks/valleys of different polynomials. X₁ 1 2 3 4 5 6 7 8 3 PARAMETERS a--0.327381 b-3.02976 c-0.839286 5 8 10 7 6 4 6 ₁~ax₁ + bx₁ + c STATISTICS R²-0.5247 RESIDUALS e plot X X 10 10
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The given data set is
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- A biologist wants to predict the height of male giraffes, y, in feet, given their age, x1, in years, weight, x2, in pounds, and neck length, x3, in feet. She obtains the multiple regression equation yˆ=7.36+0.00895x1+0.000426x2+0.913x3. Predict the height of a 12-year-old giraffe that weighs 3,100 pounds and has a 7-foot-long neck, rounding to the nearest foot.A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x). The results of the regression were: -a+bx a=-0.761 b-0.063 (a) Write the equation of the Least Squares Regression line of the formThe scatter plot below shows the average cost of a designer jacket in a sample of years between 2000 and 2015. The least squares regression line modeling this data is given by yˆ=−4815+3.765x. A scatterplot has a horizontal axis labeled Year from 2005 to 2015 in increments of 5 and a vertical axis labeled Price ($) from 2660 to 2780 in increments of 20. The following points are plotted: (2003, 2736); (2004, 2715); (2007, 2675); (2009, 2719); (2013, 270). All coordinates are approximate. Interpret the slope of the least squares regression line. Select the correct answer below: 1.The average cost of a designer jacket decreased by $3.765 each year between 2000 and 2015. 2.The average cost of a designer jacket increased by $3.765 each year between 2000 and 2015. 3.The average cost of a designer jacket decreased by $4815 each year between 2000 and 2015. 4. The average cost of a designer jacket increased by $4815 each year between 2000 and…
- Suppose you use regression topredict the height of a womanscurrent boyfriend by using her ownheight as the explanatory variable.Height was measured in feet from asample of 100 womenundergraduates, and their boyfriends,at Dalhousie University. Now, supposethat the height of both the womenand the men are converted tocentimeters. The impact of thisconversion on the slope is:Tire pressure (psi) and mileage (mpg) were recorded for a random sample of seven cars of thesame make and model. The extended data table (left) and fit model report (right) are based on aquadratic model Write out the estimated quadratic polynomial regression model.Tire pressure (psi) and mileage (mpg) were recorded for a random sample of seven cars of thesame make and model. The extended data table (left) and fit model report (right) are based on aquadratic model. Calculate R2. Describe what this value means in the context of the problem.
- A biologist is interested in predicting the brain weight (in grams) of a certain species of bird from its body weight (in grams). A least squares regression line was fit to data collected from a random sample of 28 birds of this species. The equation of the line is ŷ = 3.79 + 0.08x where ŷ is the predicted brain weight and x is the body weight of the bird. Which of the following gives the best interpretation of the slope of the regression line? (A) There is an increase of 0.08 grams in the predicted brain weight of this species of bird for every increase of 1 gram in body weight. (B) There is an increase of 0.08 grams in the predicted body weight of this species of bird for every increase of 1 gram in brain weight. (C) There is an increase of 3.79 grams in the predicted brain weight of this species of bird for every increase of 1 gram in body weight. (D) There is an increase of 3.79 grams in the predicted body weight of this species of bird for every increase of 1 gram in brain weight.…The age and height (in cm) of 400 adult women from Bolivia were measured. A researcher wants to know if age has any effect on height. A linear regression is carried out in Minitab and the following output obtained. Coefficients Term Constant Age (a) Write down the regression model. (b) Interpret the regression coefficient for the fitted model. (c) Use the output from Minitab to explain if the age of a participant affects their height. Percent (d) The normal probability plot of the residuals from this regression model is given below. Do the assumptions of the regression model seem reasonable? Justify your answer. 99.9 8 28 22299229 88 Coef SE Coef 152.94 7.69 0.022 0.231 01 -100 T-Value P-Value VIF 19.90 0.000 0.10 0.924 1.00 -50 Normal Probability Plot (response is Height) 0 Residual 50 ***** 100 150Tire pressure (psi) and mileage (mpg) were recorded for a random sample of seven cars of thesame make and model. The extended data table (left) and fit model report (right) are based on aquadratic model What is the predicted average mileage at tire pressure x = 31?
- The relationship between a number of beers consumed (x) and blood alcohol content (y) was studied in 16 male college students by using least squares regression. The following regression equation was obtained from this study: ?̂ = -0.0127 + 0.0180x The above equation implies that: each beer consumed increases blood alcohol by 1.27% on average it takes 1.8 beers to increase blood alcohol content by 1% each beer consumed increases blood alcohol by an average of the amount of 1.8% each beer consumed increases blood alcohol by exactly 0.018A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight = -5.69 + 0.1656 length. A newborn was 48cm long and weighed 33kg. According to the regression model, what was his residual? What does that say about him?A least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight = -5.25 +0.1696 length. A newborn was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him?
