A hypothetical data regarding consumption of fast food observed among the adults of a country is shown in the table below Gender Number (in thousand) Number (in thousand) People above 18 years Fast food consumers Male 62,384 28,689 Female 66,778 31,083 Use the data to calculate: 1. Sex ratio of male to female fast food consumers 2. Proportion of female who consume fast food 3. Prevalence per 1,000 of fast food consumption in: a) men only b) women only c) total population aged above 18 years
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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A hypothetical data regarding consumption of fast food observed among the adults of a country is shown in the table below
Use the data to calculate: 1. Sex ratio of male to female fast food consumers 2. Proportion of female who consume fast food 3. Prevalence per 1,000 of fast food consumption in: a) men only b) women only c) total population aged above 18 years |
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