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1st Year Research Methods > statistical power > Flashcards

statistical power Flashcards

1
Q

whats the most commonly used inferential statistical method

A

hypothesis test

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2
Q

whats does the hypothesis test begin with

A

a null hypothesis

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3
Q

whats the purpose of the hypothesis test

A

to rule out chance as an explanation of the results

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4
Q

what does the outcome of a hypothesis test depend on

A

the sample size

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5
Q

what happens if you increase the sample size of a hypothesis test

A

increases the likelihood of obtaining a significant result

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6
Q

what is recommended that researchers provide when reporting a statistically significant effect

A

an independent measure of effect size

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7
Q

type 1 error

A

rejecting the true hypothesis

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8
Q

type 11 error

A

accepting a false hypothesis

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9
Q

what is statistical power

A

the probability of correctly identifying an effect

-rejecting a false null hypothesis

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10
Q

when would researchers attend to power

A

at the design stage

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11
Q

what can power analysis be used for

A

to calculate the minimum sample size required to accept the outcome of a statistical test with a particular level of confidence

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12
Q

practical significance

A

a result or treatment that is large enough to have value in practical application

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13
Q

what is needed for practical significance

A

the size of the effect

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14
Q

what is a statistically significant result

A

one thats unlikely to be due to chance

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15
Q

what is a practically significant result

A

one thats meaningful in the real world

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16
Q

effect size

A

the measured magnitude of a treatment effect or relationship that is not influenced by factors such as sample size

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17
Q

what is the estimation of effect size essential for

A
  • practical significance
  • desired sample size
  • comparison across different studies
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18
Q

the d family

A

effect sizes assessing the difference between groups on continuous variables

19
Q

what are effect sizes for continuous variables

A

standardised mean differences

20
Q

how is effect size for continuous variables calculated

A

subtract mean of one group from the other and divide result by the SD of population
*the bigger the score the bigger the effect

21
Q

cohens d

A

the size of the mean difference between two treatments can be standardised by measuring the mean difference in terms of SD

22
Q

what does d mean in cohens d

A

sample mean difference divided by sample SD

23
Q

what does d=2 in cohens d indicate

A

mean difference is twice as big as SD

24
Q

what does d=0.50 indicate in cohens d

A

mean difference is half as large as the SD

25
Q

the r family

A

effect sizes measuring the strength of a relationship between 2 or more variables

26
Q

what are egs of the r family

A
  • correlation coefficients
  • standardized regression weights
  • regression measures of variance explained
27
Q

context of interpretation of effect sizes

A

small effects can be important if they trigger big consequences, accumulate into larger effects or lead to technological breakthroughs and new discoveries

28
Q

contribution to knowledge - interpreting effect sizes

A
  • interpret results in context of current evidence

* does the observed effect differ from what others have found

29
Q

whats a small standardised mean difference for cohens criteria

30
Q

whats a medium standardised mean difference for cohens criteria

31
Q

whats a large standardised mean difference for cohens criteria

32
Q

whats a very large standardised mean difference for cohens criteria

33
Q

whats a small correlation for cohens criteria

34
Q

whats a medium correlation for cohens criteria

35
Q

whats a large correlation for cohens criteria

36
Q

whats a very large correlation for cohens criteria

37
Q

how to increase statistical power - effect size

A

increasing effect size increases power

38
Q

how to increase statistical power - alpha level

A
  • usual value p= 0.05

* increasing alpha increases power

39
Q

how to increase statistical power - sample size

A

increasing sample size increases power

40
Q

what are the 4 main parameters of power analysis

A
  1. effect size
  2. sample size
  3. alpha significance criterion
  4. power of the statistical test
41
Q

how to obtain the effect size for power analysis - a literature review

A
  • estimate the effect size based on published studies similar
  • relevant values are not entirely clear
42
Q

how to obtain the effect size for power analysis - a pilot study

A
  • rough estimate of effect size

* info extracted from a small sample is limited and bias

43
Q

how to obtain the effect size for power analysis - cohens reccomendations

A

*small effects - large effects reccomendations

1st Year Research Methods (15 decks)

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