Basic statistical principles Flashcards

1
Q

definition: statistics that assumes a normal distribution (bell curve) and needs a large # of subjects (n > 30)

A

parametric stats

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2
Q

definition: statistics that does not require a normal distribution or if the distribution is unknown (usually has n<30)

A

non-parametric stats

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3
Q

definition: the probability that the findings occurred due to chance

A

p values

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4
Q

definition: the range of scores in which the true score for the variable is estimated to lie within a specific probability

A

confidence interval (CI)

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5
Q

definition: the probability that a statistical test will detect a relationship between 2 or more variables OR a difference between 2 or more groups of scores

A

power

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6
Q

What % of power is common in most studies?

A

80%

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7
Q

definition:
- Rejecting the null hypothesis when a relationship does NOT exist
- Saying there is a difference when there is not

A

type I error (false positive)

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8
Q

definition: Accepting the null hypothesis when a relationship DOES exist

A

type 2 error (false negative)

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9
Q

definition: “there will not be a difference between the two groups”

A

null hypothesis

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10
Q

definition: “ there will be a difference between the two groups”

A

directional hypothesis

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11
Q

definition: A test used when you are trying to determine differences
- Assuming normal distribution with population size >30

A

independent t-test

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12
Q

definition: A test that compares the two populations with the subject being the control

EX: balance test/timed test (4-square test) before therapy vs. after therapy

A

paired T-test

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13
Q

(true/false) you can use a t-test when there is more than one group

A

FALSE

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14
Q

With ANOVA (parametric stat), you have to use a _____ test if there is statistical difference between the groups due to ANOVA not indicating which group had a difference

A

post hoc

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15
Q

definition: Similar to ANOVA but controls for or a co-variable, only 1 dependent variable

A

ANCOVA

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16
Q

definition: parametric stat that has more than one dependent variable/outcomes

EX: comparing balance and strength between low intensity vs. moderate intensity. vs high intensity

A

MANOVA

17
Q

What are non-parametrics stats used to test differences?

A

mann-whitney U
wilconxon Rank Sum
Wilcoxon Signed Rank Test (similar to paired t-test)
kruskal-wallis H (similar to ANOVA- compares 3+ groups and required post hoc test)
Freidman’s ANOVA (ANOVA w/ repeated measures, requires post hoc)

18
Q

definition: difference between the mean of the 2 groups examined / SD

A

effect size

19
Q

What is considered as a good effect size?

A

0.8 +

20
Q

What is considered as a bad effect size?

A

0.2