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by: A Jones

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Biostatistics Exam 2-Preview Heal 395

Marketplace > College of Charleston > Public Health > Heal 395 > Biostatistics Exam 2 Preview
A Jones
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This note is one week. ------------------------------- I have completed study guides for Exam 1 and 2!! I did very well in the course by creating and using these in depth notes. Good luck!
COURSE
Biostatistics
PROF.
Hart
TYPE
Class Notes
PAGES
3
WORDS
CONCEPTS
Biostatistics
KARMA
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This 3 page Class Notes was uploaded by A Jones on Friday September 9, 2016. The Class Notes belongs to Heal 395 at College of Charleston taught by Hart in Fall 2016. Since its upload, it has received 7 views. For similar materials see Biostatistics in Public Health at College of Charleston.

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Date Created: 09/09/16
9/9/2016 Exam 2 | Evernote Web Exam 2 Normal Distribution Probability Estimation https://www.evernote.com/Home.action#n=f1c2beec­f601­42cf­abe1­1595d1fe041f&b=3e793d12­1/10­48b5­aeeb­12b02ed6bc73&ses=4&sh=1&sds=5& 9/9/2016 Exam 2 | Evernote Web Standard deviation formula: What does the z score represent? relationship to the mean in a group of scores: can also be positive or negative, indicating whether it is above or below the mean and by how many standard deviations.     Negative: probability values are less than­  The Z score for a weight =100lbs is: ᵄᵄ(100) = (100−150) 30 = ­1.67 The probability associated with a Z score of ± 1.67 is 0.047. https://www.evernote.com/Home.action#n=f1c2beec­f601­42cf­abe1­1595d1fe041f&b=3e793d12­ce29­48b5­aeeb­12b02ed6bc72/10s=4&sh=1&sds=5& 9/9/2016 Exam 2 | Evernote Web Therefore, this probability means that based on these data, there is a 0.047 (4.7%) chance that a person will weigh less than 100 lbs.     Positive: probability values are more than­  How to calculate z score:     **** population: mu and sigma: μ & σ Example: μ = 150 mg/dL σ = 30 mg/dL  150­(2*30) = 90 150+(2*30) = 210 This means 68%of the values fall between 90 and 210  Central Limit Theorem­ as sample size increases the distribution of averages are more normal Binomial Distribution Probability Estimation ­Discrete Binomial Probabilities ­Cumulative Binomial Probabilities https://www.evernote.com/Home.action#n=f1c2beec­f601­42cf­abe1­1595d1fe041f&b=3e793d13/1029­48b5­aeeb­12b02ed6bc73&ses=4&sh=1&sds=5&

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