11. In this same article on sleep duration and start time, researchers also considered whether school start time was related to obtaining an adequate amount of sleep. An adequate amountbof sleep was considered at least 8.5 hours of sleep, as recommended by the National Sleep Foundation. The authors used logistic regression models to associate the probability of adequate sleep to school start time. Here are some adapted logistic regression results from this study: In(odds of adequate sleep) = where x = school start time, measured as the number of minutes after 7 AM that the school starts. For this model, B,-0.014; SE(B,)-0.005. - What Is the estimated odds ratio of adequate sleep, and 95% CI, for students who start at 8:30 AM compared to those who start at 7:30 AM? a. 1.01 (1.00, 1.02) b. 1.52 (1.13, 2.05) c. 2.32 (1.27, 4.22) d. 4.05 (1.49, 11.02)

11. In this same article on sleep duration and start time, researchers also considered whether school start time was related to obtaining an adequate amount of sleep. An adequate amountbof sleep was considered at least 8.5 hours of sleep, as recommended by the National Sleep Foundation. The authors used logistic regression models to associate the probability of adequate sleep to school start time. Here are some adapted logistic regression results from this study: In(odds of adequate sleep) = where x = school start time, measured as the number of minutes after 7 AM that the school starts. For this model, B,-0.014; SE(B,)-0.005. - What Is the estimated odds ratio of adequate sleep, and 95% CI, for students who start at 8:30 AM compared to those who start at 7:30 AM? a. 1.01 (1.00, 1.02) b. 1.52 (1.13, 2.05) c. 2.32 (1.27, 4.22) d. 4.05 (1.49, 11.02)

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

See similar textbooks

Similar questions

What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that y and x are positively correlated. True or false?
If the R-squared for a regression model relating the outcome y to an explanatory variable x is 0.9. This implies that y and x are positively correlated.
The following table contains statistics from a logistic regression analysis for a study on intravenous drug use among high school students in United States. Drug use is characterized as a dichotomous variable, where 1 indicates that an individual has injected drugs within the past year and 0 that he or she has not. Factors that might be related to drug use are instruction about the HIV in school (1 represents "had HIV education" and 0 represents "did not have HIV education"), age of the student (in years), and gender (1 represents male and 0 represents female). Statistics in the table are estimated coefficients of the logistic regression model and p-values for testing the significance of the coefficients. Choose proper answers using statistics in the following table. (THERE MAY BE MORE THAN ONE CORRECT ANSWER) Variable Coefficient p-value Intercept (Constant) -0.164 0.078 HIV instruction 0.019 0.928 Age 0.064 0.036 Gender 1.032 0.014…
Suppose you trained your logistic regression classifier which takes an image as input and outputs either dog (class 0) or cat (class 1). Given the input image x, the hypothesis outputs 0.2. What is the probability that the input image corresponds to a dog?
If the Pearson correlation between X and Y is r = .50, then the regression equation predicts 25% of the variance in the Y scores. True or false? Why?
If the coefficient of determination of a simple regression equation is 0.81, the correlation coefficient is
Whenever the slope of a regression line is zero, the correlation coefficient will also be zero. True False
1) What is the probability of a stroke over the next 10 years for John Smith, a 68-year-old smoker who has blood pressure of 175? What action might the physician recommend for John to reduce the risk of stroke? 2) Is there any multicollinearity problem in the above multiple regression model? How do you know?
a. Can you construct a 95% confidence interval for the y intercept for the regression equation then justify the correlation between time and duration? b. Also, what are the chances of seeing a relationship between time and duration as strong or stronger than this, when in fact there was none?
If other factors are held constant and the Pearson correlation value between X and Y is r = 0.80, then the regression equation will tend to produce more accurate predictions than would be obtained if the Pearson correlation value was r = 0.60. True or False