For a MR model with 4 predictors, we have: SSE = 288 and SST = 957 What percentage of the variation in Y is accounted for by its assumed relationship with the predictors?
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- please answer the question!Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the date and the least-squares regression line. The equation for this line is y=82.84-0.49x. Birthrate, x (number of births per 1000 people) 24.6 50.1 40,6 20.0 50.7 28.1 143 49.0 31.9 14.8 33.6 46.5 Send data to calculator Send data to Excel Female life expectancy, y (in years) 74.3 54.4 66.2 73.6 58.9 72.7 76.1 61.5 62.4 71.4 68.0 57:5 Based on the sample data and the regression line, complete the following. Female life expectancy (in years) Birthrate (number of births per 1000 people)Given that the systolic blood pressure in the right arm is 90 mm Hg, the best systolic blood pressure in the left arm is how many mm Hg?
- 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: уах+ b a = -1.098 b = 37.154 r2 = 0.444889 r = -0.667 Use this to predict the number of situps a person who watches 11 hours of TV can do. situps = [one decimal accuracy]Based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and number of views? A popular television show recently released a video preview for the upcoming season on its website. As fans of the show discover the video, the number of views of the preview video has grown each day during the last 2 weeks. The number of days since the release of the video and the natural log of the number of video views is shown in the scatterplot. O An exponential model is appropriate because the residual plot does not show a clear pattern. O A linear model is appropriate because the scatterplot shows a strong, positive linear relationship. In(Views) vs. Days O A power model is appropriate because the scatterplot of days and natural log of views is strong and linear. 10 9.5 An exponential model is appropriate because the relationship between days and the natural log of views is linear, and the residual plot does not show a clear…Below is some of the regression output from a regression of the amount various customers paid for a new car (expressed in dollars) versus the age of the customer (expressed in years), the number of previous cars the customer had purchased from the dealership in the past, a dummy variable indicating the gender of the customer (=1 for a Man and = 0 for a woman), and an interactive term the multiplies the age of the customer with the gender dummy variable. Regression Statistics Multiple R 0.963 R Square Adjusted R Square Standard Error Observations 20 ANOVA df SS MS F Significance F Regression 24686354.49 6171589 47.8 2.3289E-08 Residual 129243 Total 26625000…
- A researcher interested in explaining the level of foreign reserves for the country of Barbados estimated the following multiple regression model using yearly data spanning the period 2001 to 2016: FR=a+B01L+YEXP+8FDI Where FR = yearly foreign reserves (So000's), OIL = annual oil prices, EXP = yearly total exports (S000's) and FDI = annual foreign direct investment ($000's). The sample of data was processed using MINITAB and the following is an extract of the output obtained: Predictor Coef StDev t-ratio p-value Constant 5491.38 2508.81 2.1888 0.0491 OIL 85.39 18.46 4.626 0.0006 EXP -377.08 112.19 0.0057 FDI -396.99 160.66 -2.471 s - 2.45 R-sq = 96.3% R-sq(adj) = 95.3% Analysis of Variance Source DF MS F Regression 3 1991.31 663.77 ?? Error 12 43. רר 6.45 Total 15 a) What is dependent and independent variables? b) Fully write out the regression equation c) Fill in the missing values **', **', '?'and *??"A regression line for predicting test scores has an r.m.s. error of 8 points. When this result is used to predict test scores, about 95% of the predictions will be right to within how many points.The line of best fit through a set of data is y = 41.762 2.926x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 50? y = Round to 1 decimal place.
- A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy).The results of the regression were:y=ax+b a=-1.364 b=32.282 r2=0.398161 r=-0.631 Use this to predict the number of situps a person who watches 4 hour(s) of TV can do, and please round your answer to a whole number.The line of best fit through a set of data is y = – 27.749 + 1.474x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 30? y = Round to 1 decimal place.A patient is classified as having gestational diabetes if their average glucose level is above 140 milligrams per deciliter (mg/dl) one hour after a sugary drink is ingested. Rebecca's doctor is concerned that she may suffer from gestational diabetes. There is variation both in the actual glucose level and in the blood test that measures the level. Rebecca's measured glucose level one hour after ingesting the sugary drink varies according to the Normal distribution with μ=140+5 mg/dl and σ=5+1 mg/dl. Using the Central Limit Theorem, determine the probability of Rebecca being diagnosed with gestational diabetes if her glucose level is measured: Once? n=5+2 times n=5+4 times Comment on the relationship between the probabilities observed in (a), (b), and (c). Explain, using concepts from lecture why this occurs and what it means in context.