A regression was run to determine if there is a relationship between the happiness inde expectancy in years of a given country (x). The results of the regression were: ŷ=a+bx a=-1.042 b=0.186

Does how long young children remain at the lunch table help predict how much they eat? Twenty toddlers were observed over several months at a nursery school. "Time" is the average number of minutes a child spent at the table when lunch was served. "Calories" is the average number of calories the child consumed during lunch, calculated from careful observation of what the child ate each day. A regression was run and the results were: = 114 + 2.4*x R² = 0.68 r = 0.822 Predict the number of calories a toddler consumes who remains at the table for 14.5 minutes (round your answer to two decimal places)

While attempting to measure its risk exposure for the upcoming year, an insurance company notices a trend between the age of a customer and the number of claims per year. It appears that the number of claims keep going up as customers age. After performing a regression, they find that the relationship is (claims per year) = 0.385*(age) + 5.218. If a customer is 44.315 years old and they make an average of 11.239 claims per year, the residual is -11.04. Interpret this residual in terms of the problem.   Question 10 options:   1)  The number of claims per year is 11.04 claims less than what we would expect.   2)  The age is 11.04 years larger than what we would expect.   3)  The age is 11.04 years less than what we would expect.   4)  The number of claims per year is 11.239 claims less than what we would expect.   5)  The number of claims per year is 11.04 claims…

The coefficient of correlation in a simple regression analysis is = -0.6. The coefficient of determination for this regression would be 0.36 - 0.36 0.6 0.13 O 0.6 or + 0.6

For a particular red wine, the auction selling price for a 750-milliliter bottle and the age of the wine (in years) was recorded and used to regress the Auction Selling Price (the y-variable) on the Age (the x-variable). The Excel regression analysis showed that the estimated regression equation was: y with hat on top equals 9.02 plus 6.95 x Use this estimated regression equation to predict the Auction Selling Price of a 750-milliliter bottle of this red wine that is 15 years old. Give the EXACT value. The predicted Auction Selling Price of a 750-milliliter bottle of this red wine that is 15 years old is $

Listed below are systolic blood pressure measurements (in mm Hg) obtained from the same woman. Find the regression equation, letting the right arm blood pressure be the predictor (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 85 mm Hg. Use a significance level of 0.05 Right Arm 101 100 94 75 Left Arm 174 167 146 144 Click the icon to view the critical values of the Pearson correlation coefficient r The regression equation is (Round to one decimal place as needed.) 76 144 CRITS

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.271 b=39.101 ²-0.407044 r=-0.638 Assume the correlation is significant, and use this to predict the number of situps a person who watches 14 hours of TV can do (to one decimal place) Aft

Listed below are systolic blood pressure measurements​ (in mm​ Hg) obtained from the same woman. Find the regression​ equation, letting the right arm blood pressure be the predictor​ (x) variable. Find the best predicted systolic blood pressure in the left arm given that the systolic blood pressure in the right arm is 95 mm Hg. Use a significance level of 0.05   Right Arm 100 99 92 76 76   Left Arm 175 169 143 143 143

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y-ax+b a=-1.108 b-34.092 r2-0.736164 r=-0.858 Assume the correlation is significant, and use this to predict the number of situps a person who watches 4 区 hours q TV can do (to one decimal place) 72222392 口 D

The mall has a set of data with employee age (X) and the corresponding number of annual on-the-job-accidents(Y). Analysis on the set finds that the regression equation is Y=100-3X. What is the likely number of accidents for someone aged 30?     97     100     10     none of the above