The following data give the times of 15 girls when they were put on ultraheavy rope-jumping program. Someone thought that such a program would increase their speed in the 40-yard dash. Let D equal the different in time run the 40-yard dash – the "before program time (x)" minus the "after-program time (v)". Assume that the distribution of D is approximately normal, N(µp, oß). Test the null hypothesis Ho: Hp = 0 against the alternative hypothesis H1: µp > 0. Use a = 0.05 24.97 23.98 22.93 22.83 22.38 22.39 22.76 21.66 22.98 23.17 25.76 23.63 23.41 22.75 22.91 22.34 22.82 21.68 23.80 22.53 25.80 23.61 22.10 22.74 22.08 21.95 21.80 21.58 22.84 23.58 OLUTION: ind the following value. Do calculations in 3 decimal places. D Sp Test statistic, to Critical value (i) (ii) (iii) (iv) Vrite your answer here: i) ii) iv) conclusion:
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!
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