# STAT 503 Quiz III

### Card Set Information

 Author: MRK ID: 264574 Filename: STAT 503 Quiz III Updated: 2014-03-10 12:14:32 Tags: Nominal Folders: Description: Chapter V, VI Show Answers:

Home > Flashcards > Print Preview

The flashcards below were created by user MRK on FreezingBlue Flashcards. What would you like to do?

1. When use Normal approximation
• When n is large, coefficients hard to calculate
• lots of possible values for Y
• and p isn't close to 0 or 1
2. Normal approximation equations
• u = np
• o = √np(1-p)
• as long as np and n(1-p) are both at least 5
3. Proportion of success in Normal approximation
• p-hat = Y/n
• µ = p
• sd = √p(1-p)/n
4. Continuity correction
interval is y - .5 and y + .5
5. Standard error
• SE = s/√n
• 'average' deviation when using the sample means as an estimate for the population mean
• description of the mean as applies to population mean
6. As n -> ∞
• y-bar -> µ
• s -> o
• SE -> 0
7. Confidence interval formulas
• y-bar +/- ta/2(o/√n)
• that area will contain (1-a)100% of all samples
8. t-distribution
• heavier tail
• more to z curve with larger samples
9. t-table
• gives t values in the table
• z-values on bottom
• alpha/2 is the given on top as the area to the right
10. cofidence interval contains the population...
x% of the time, and y-bar is always the middle value
11. Validity of CI construction models
• must be random samples
• if n is small the pop. needs to be normal
• if n is large the pop. can be t'whatever
12. observational study v. controlled experiment
observational - less certain of results
13. Pool v. unpooled
• pool when sd1 = sd2
• usually use unpooled, easier
14. unpooled SE
15. pooled SE
16. CI for µ1 - µ2
17. T-value Calc
(Y-bar - µ) / (s/√n)
18. if 95% CI contains Zero:
"no significant difference" btw µ1 and µ2 at 5% level of significance
19. If 95% CI does not contain zero
it implies statistical difference btw µ1 and µ2 at 5% level of significance.
20. Conditions for validity of hypothesis testing
• same for CI
• two independent random samples
• normal or large samples
21. H0
• null hypothesis
• default state (innocent)
22. HA
alternate hypothesis
23. Hypothesis
• either fail to reject H0
• or
• reject H0
24. Errors with hypo decision
• Type I error: rejected, when it was true
• low upper limit = alpha
• statements have = signs
• Type II error: fail to reject when Ha is true
• upper limit = beta
• Power of a test Pr(reject H0 | Ha is true)
• statements ≠ or < >

What would you like to do?

Home > Flashcards > Print Preview