Suppose a researcher is interested in investigating the effectiveness of a new diet plan at reducing BMI among a group of women with similar baseline weights after 1 year. Suppose the group of 45 women vary approximately according to a normal distribution with mean BMI (kg/m2) of 29.5 and a standard deviation of 1.6 kg/m2 after 1 year and the goal BMI was 28.5 kg/m2. A) Did the women meet their goal weight? Use an alpha level of 0.05.
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!
- Suppose a researcher is interested in investigating the effectiveness of a new diet plan at reducing BMI among a group of women with similar baseline weights after 1 year. Suppose the group of 45 women vary approximately according to a
normal distribution with mean BMI (kg/m2) of 29.5 and a standard deviation of 1.6 kg/m2 after 1 year and the goal BMI was 28.5 kg/m2.
- A) Did the women meet their goal weight? Use an alpha level of 0.05.
- B) State your null and alternative hypotheses, and interpret your pvalue.
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