A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Data from a portion of this study follow. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker. *image for data* Using age, blood pressure, and whether a person is a smoker, develop an estimated regression equation that can be used to predict risk. Use x1 for age, x2 for blood pressure, and x3 for whether a person is a smoker. (Round your constant term to one decimal place and coefficients to three decimal places.)
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Data from a portion of this study follow. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10-year period. For the smoker variable, 1 indicates a smoker and 0 indicates a nonsmoker.
*image for data*
Using age, blood pressure, and whether a person is a smoker, develop an estimated regression equation that can be used to predict risk. Use x1 for age, x2 for blood pressure, and x3 for whether a person is a smoker. (Round your constant term to one decimal place and coefficients to three decimal places.)
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The previous multiple regression model is significant to what level?
by Bartleby ExpertHow much does the risk increase for each year of age advance?
by Bartleby ExpertWhat is the most significant independent variable?
Smoker
Age
Blood Pressure
by Bartleby Expert
