vely.Use younger children as population 1. (a) Do you think that it is reasonable to assume that these data are Normally distributed? Explain why or why not. (Hint: Think about the 68-95-99.7 rule.) O The distributions appear to be Normal according to the 68-95-99.7 rule. We can see that the groups have means and standard deviations, two characteristics of Normal distributions. • The 68-95-99.7 rule suggests that the distributions are not Normal. If they were, we would expect some of the children to drink negative amounts of sweetened drinks, which does not make sense. (b) Using the methods in this section, test the null hypothesis that the two groups of children consume equal amounts of sweetened drinks versus the two-sided alternative. Report all details of the significance-testing procedure with your conclusion. (Round your answers to three decimal places.) SED = 4.516 t= -1.329 df =8 P-value = (c) Give a 95% confidence interval for the difference in means. (Round your answers to four decimal places.) (d) Do you think that the analyses performed in parts (b) and (c) are appropriate for these data? Explain why or why not. O The t procedures are questionable for these data because the distributions are not Normal and the samples are small. O The t procedures are annronriate for these data because the distributions are Normal and the samples are large enough
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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