write out the expression for the un-normalized log-posterior on S\mus. You may drop all cerms that do not involve S\mus. Your final result should may include the summation of the Tuadratic term.**

The regression analysis shows that r^2 = 0.4688. What would the correlation be? A. r = √0.4688 B. r = −√0.4688 C. Both A and B. D. None of the above.

3. Solve for B. The accompanying data are from a football league for one season. Use the regression tool to develop a model for predicting points/game as a function of yards/game. Explain the statistical significance of the model and the r^2 value.  Solve for B Develop a mod for predicting points/game as a function of yards/game. Points/game= -20.892 + (.131) x yards/game. To Explain the statistical significance of the model first state the appropriate null and alternative hypotheses. H0 : H1:  SEE PICTURE

I am completely lost please help

A study of king penguins looked for a relationship between how deep the penguins dive in meters xx to seek food and how long they stay underwater in minutes yy. Based on sample data, the regression line is found to be y^​=2.69+0.0116x Use the regression line to estimate how long a typical dive of 200 meters would last. Round your answer to two decimal points.

I have modeled adult worker's salaries based upon their work experience. After surveying 200 adults about their salary and years in the workforce, I have found the following model: y=12000+5000*x where y is the predicted salary and x is the years in the labor force. R^2 = 0.63.  What is the correlation for this model? (correlation between salary and years in the labor force)?  a. 0 b. 0.79 c. 0.63 d. 0.50 e. 1

You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). Questions: 1.Write down the population model that estimates BW based on variables AGE and BOROUGH(with the dummy variables). Make sure that it is clear what each predictor means. 2.How many parallel lines are computed by model from population model you created above? 3.Write down the population model that estimates BW based on variables AGE, MSS(with their dummy variables) and BOROUGH(with their dummy variables). Also write down the number of parrallel lines.…

Complete the missing information for this regression model.  Note:  N=26N=26. (Except for P-values, report all values accurate to 3 decimal places.  For P-values, report accurate to 4 decimal places.) ˆYY^ = 26.759 + 0.818X10.818X1 −- 2.999X22.999X2 + X3X3     2.382   0.547   1.674   0.734       Standard Errors     11.234   1.495               t-ratios                 0.0991       P-values

A frequent flyer was interested in the relationship between dollars spent on flying and the distance flown. She sampled 20 frequent flyers of a certain airline. She collected the number of miles flown in the previous year and the total amount of money the flyer spent. A regression line of distance flown on money spent was fit to the data: \hat y = 24000 + 10xy^​=24000+10x. A person who spent $1000 is predicted to have flown:

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