2 T Test

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Author:
Trekofstarsx
ID:
298419
Filename:
2 T Test
Updated:
2015-03-15 00:12:57
Tags:
stat
Folders:
stat
Description:
2 sample t
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  1. By selecting a smaller alpha level, a researcher is
  2. The z score boundaries for a critical region are determined by
    the alpha level
  3. Two possible ways of comparing two samples means
    • -The two means could come from two completely separate groups of participants
    • -Two sets of data could be gathered from the same group
  4. Independent Measures t-test
    • -Two separate groups being tested 
    • -Also known as between subjects design
  5. t formula
    [(M1-M2)-(u1-u2)]/S(M1-M2)
  6. s(M1-M2)=
    sqrt[(s12/n1)+(s22/n2)]
  7. Estimated standard error is only true if
    both ns are the same
  8. Pooled variance formula
    Pooled variance formula with standard error
    see card
  9. H0 and H1 for two independent sample means
    u1-u2=0
  10. We use the sample mean difference to
    Estimate the population mean difference
  11. Condfidence interval for two independent sample means formula
    u1-u2=M1-M2+-t*SM1-M2
  12. Two-tailed hypothesis 

    Ho
    H1
    • u1-u2=0
    • u1-u2does not equal 0
  13. One-tailed (uppertail critical)

    HO
    H1
    see formula sheet
  14. One-tailed (lowertail critical)
    see formula sheet
  15. 3 Assumptions of t tests
    • -Observations within each sample must be independent
    • -The population from which the samples are selected must be approximately normal
    • -The two populations from which samples are selected must have the same variance
  16. Hartley F-max test

    -Tests?

    1.2.3.
    -Tests whether our sample variances are reasonably close

    • 1. Compute sample variance for each sample
    • 2. Select largest and smallest of these variances and compute s2(largest)/s2(smallest) to get F max 
    • 3.Compare F-max value with the critical value

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