ANOVA & Paired t-Test Exam 2 Flashcards

1
Q

When would you use Independent groups t-test?

A

xContinuous variable compared across two discrete independent groups that are part of one variable

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2
Q

When would you use Analysis of variance (ANOVA)?

A

Continuous variable compared across three or more discrete independent groups that are part of one variable

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3
Q

When would you use Dependent groups (paired) t-test?

A

Continuous variable compared across matched measurements in two discrete dependent groups that are part of one variable

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4
Q

What are the assumptions that must be met for ANOVA?

A
  • samples are random
  • a person is only in one group (independent samples)
  • there are independent observations within groups (one observation per person)
  • data is normally distributed,
  • variances are similar to one another
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5
Q

What are the assumptions that must be met for Dependent groups (paired) t-test?

A
  • one group is measured twice (ex. baseline and post-treatment)
  • there may be a correlation between those two values
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6
Q

t-statistic value

A
  • As difference between the means increase, the value of t increases
  • As variability increases (in the denominator; aka the more dispersion), the value of t decreases,
  • as sample size increases, the value of t increases,
  • as the correlation increases, the value of t increases
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7
Q

What is the F test?

A

measures if there is a difference between the group means

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8
Q

What is the null hypothesis for the F test?

A

there is no difference among group means

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9
Q

In a F-test, what is the degrees of freedom?

A

N-1

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10
Q

What is is n^2?

A

tells you what percentage of the variance that we see is explained by our one grouping variable

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11
Q

Planned comparison technique used in ANOVA

A
  • Hypotheses specified before the analysis commences

* Typically involve all possible comparisons

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12
Q

Post-hoc comparison technique used in ANOVA

A
  • Performed after some significant difference has been found via F test
  • Tukey’s HSD (honest significance difference) test corrects for inflated alpha
  • Further exploration of data after a significant effect has been found
  • Typically involve two comparisons at a time
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