Let x be a random variable that represents hemoglobin count (HC) in grams per 100 milliliters of whole blood. Then x has a distribution that is approximately normal, with population mean of about 14 for adult healthy women. Suspose that a female patient has taken 10 labrotory blood test during the past year. The HC data sent to the patients doctors are as follows: 15 18 16 19 13 13 15 17 17 10 A) x-bar = s = B) Does this information indicate that the population average HC for this patient is higher than 14? use alpha= 0.01 what is the level of significance? What is the value of the sample test statistic? Round to 3 decimal places estimate the P-value
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!
Let x be a random variable that represents hemoglobin count (HC) in grams per 100 milliliters of whole blood. Then x has a distribution that is approximately normal, with population
15 18 16 19 13 13 15 17 17 10
A) x-bar =
s =
B) Does this information indicate that the population average HC for this patient is higher than 14? use alpha= 0.01
what is the level of significance?
What is the value of the sample test statistic? Round to 3 decimal places
estimate the P-value
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