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Hypothesis Testing: One Sample Inference

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Diabetes

Plasma-Glucose levels are used to determine the presence of diabetes. Suppose the mean in (plasma-glucose) concentration (mg/dL) in 35 to 44-year-olds is 4.86 with standard deviation = 0.54. A study of 100 sedentary people in this group is planned to test whether they have a higher or lower level of plasma glucose than the general population.

7.7 If the expected difference is 0.10 in units, then what is the power of such a study if a two-sided test is to be used with ?= .05?
7.8 Answer problem 7.7 if the expected difference is 0.20 in units.
7.9 How many people would need to be studied to have 80% power under the assumptions in Problem 7.7?

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The expert examines one sample inference for hypothesis testing.

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Plasma-Glucose levels are used to determine the presence of diabetes. Suppose the mean in (plasma-glucose) concentration (mg/dL) in 35 to 44-year-olds is 4.86 with standard deviation = 0.54. A study of 100 sedentary people in this group is planned to test whether they have a higher or lower ...

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  • BSc , Wuhan Univ. China
  • MA, Shandong Univ.
Recent Feedback
  • "Your solution, looks excellent. I recognize things from previous chapters. I have seen the standard deviation formula you used to get 5.154. I do understand the Central Limit Theorem needs the sample size (n) to be greater than 30, we have 100. I do understand the sample mean(s) of the population will follow a normal distribution, and that CLT states the sample mean of population is the population (mean), we have 143.74. But when and WHY do we use the standard deviation formula where you got 5.154. WHEN & Why use standard deviation of the sample mean. I don't understand, why don't we simply use the "100" I understand that standard deviation is the square root of variance. I do understand that the variance is the square of the differences of each sample data value minus the mean. But somehow, why not use 100, why use standard deviation of sample mean? Please help explain."
  • "excellent work"
  • "Thank you so much for all of your help!!! I will be posting another assignment. Please let me know (once posted), if the credits I'm offering is enough or you ! Thanks again!"
  • "Thank you"
  • "Thank you very much for your valuable time and assistance!"
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