Problem 4 Data Y = SBP X #Hrs Exercise 120 4 110 10 2 120 3 135 3 140 115 5 15 2 165 160 0 180 Problem 4 l of Hours (X-Ху(Ү - (Y-Y (X-Ху Y х-X Y-Y Exercise Y) -12.8 4 0.8 0.64 120 -16 -26 -176.8 10 6.8 46.24 110 2 -1.2 120 19.2 1.44 -16 3 -0.2 0.04 135 0.2 -1 3 .02 140 4 0.04 5 18 3.24 115 -2.2 1 115 2 -1.2 165 160 2 -1.2 -3.2 180 -32/10-3.2 1360/10 -367
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!
(Previous Problem for reference: A randomsample of 10 males 50 years of age is selected and their weights, heights, and systolic blood pressures are measured. Their weights and heights are transformed into body mass index scores and are given below. In this analysis, the independent variable is body mass index and the dependent variable is systolic blood pressure)
Problem 4
Suppose in the same study we also measure the number of hours of vigorous excercise per week. Is there a relationship between the number of hours of excercise and SBP in males 50 years of age?
Then using the completed table and equations listed, calculate the
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