For years, many people thought that the mean body temperature of healthy adults was 98.6 degrees. A study was conducted of 106 healthy adults. t=-6.6 p=1.4e-9 x(bar)=98.2 sx=.62 n=106 If the value of αα =0.05, the conclusion is: There is not enough evidence to support the claim that the mean temperature is not 98.2 There is evidence to support the claim that the mean temperature is not 98.6 There is evidence to support the claim that the mean temperature is not 98.2 There is not enough evidence to support the claim that the mean temperature is not 98.6
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!
For years, many people thought that the
t=-6.6
p=1.4e-9
x(bar)=98.2
sx=.62
n=106
If the value of αα =0.05, the conclusion is:
- There is not enough evidence to support the claim that the mean temperature is not 98.2
- There is evidence to support the claim that the mean temperature is not 98.6
- There is evidence to support the claim that the mean temperature is not 98.2
- There is not enough evidence to support the claim that the mean temperature is not 98.6
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