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EBP 2 > Week 2 > Flashcards

Week 2 Flashcards

1
Q

What is the simple confidence interval?

A

A range of values that we are confident contains the population parameter

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2
Q

What is point estimate?

A

A single value that represents the best estimate of the population value

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3
Q

In a confidence interval, the width concerns the ___ of the estimate

A

In a confidence interval, the width concerns the precision of the estimate

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4
Q

The point estimate is always in the ___ of the confidence interval

A

The point estimate is always in the middle of the confidence interval

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5
Q

What is the formal definition of a confidence interval?

A

If we repeated sampling an infinite number of times, 95% of the intervals would overlap the true mean

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6
Q

Not every value in a CI, is equally as ___

A

Not every value in a CI, is equally as probable

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7
Q

A more narrow confidence interval means that it is ____ precise

A

A more narrow confidence interval means that it is more precise

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8
Q

What are the factors that can narrow/increase a confidence interval?

A
  1. Larger sample size
  2. Less variance
  3. Lower selected level of
    confidence (90% vs. 95%)
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9
Q

The null hypothesis is ___. And it states that _____

A

The null hypothesis is a sampling error. And it states that the population means(not sample means) are equal so the difference seen is not real

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10
Q

The alternative hypothesis states that the difference seen, represents __.

A

The alternative hypothesis states that the difference seen, represents a real difference.

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11
Q

What is a type 1 error in hypothesis testing? What is its symbol? This is considered a liar

A

When the null hypothesis is true, and we choose to reject it.
Symbol: “Alpha”

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12
Q

What is a type 2 error in hypothesis testing? What is its symbol? This is considered to be blind

A

When the null hypothesis is false, and we do not reject it. (accept it)
Symbol: Beta

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13
Q

___ is the maximum probability of type 1 error that a researcher is willing to accept

A

Alpha is the maximum probability of type 1 error that a researcher is willing to accept

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14
Q

When does the researcher set the alpha?

A

Set before running statistics

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15
Q

What is alpha usually set to?

A

0.05. (5%)

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16
Q

What is the simple definition of a p-value?

A

The probability of type 1 error if the null hypothesis is true

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17
Q

True or false.

You can have a probability of type 1 error what the null hypothesis is false

A

False

You can NOT have a probability of type 1 error what the null hypothesis is false

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18
Q

When is the p-value calculated?

A

After research

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19
Q

What is the formal definition of a p-value?

A

Probability of observing a value more extreme than actual value observed, if the null hypothesis is true

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20
Q

If the p-value is less than or equal to alpha, we ___ the null hypothesis

A

If the p-value is less than or equal to alpha, we REJECT the null hypothesis

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21
Q

If the p-value is greater than or equal to alpha, we ___ the null hypothesis

A

If the p-value is greater than or equal to alpha, we ACCEPT the null hypothesis

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22
Q

If we “fail to reject” (accept) Ho, we attribute any

observed difference to ____ only

A

If we “fail to reject” (accept) Ho, we attribute any

observed difference to sampling error only

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23
Q

We don’t interpret non-significant differences as “__”

maybe not even as “trends”

A

• We don’t interpret non-significant differences as “real” (maybe not even as “trends”)

24
Q

We understand that a non-significant difference is

attributable only to __.

A

We understand that a non-significant difference is

attributable only to chance.

25
Q

How do you use confidence intervals for hypothesis testing?

A

Look at the 95% CI of the mean difference, and evaluate whether or not it includes zero

26
Q

If the confidence interval includes 0, it is ____ in hypothesis testing

A

If the confidence interval includes 0, it is nonsignificant in hypothesis testing

27
Q

If the confidence interval excludes 0, it is ____ in hypothesis testing

A

If the confidence interval excludes 0, it is significant in hypothesis testing

28
Q

What is the benefit of a CI over a p-value when hypothesis testing?

A

CIs give an estimate of effect size

29
Q

P-values and CIs tells us about ___ not ____

A

P-values and CIs tells us about statistical significance not clinical significance

30
Q

What is statistical power?

A

The probability of finding a statistically significant difference if such a difference exists in the real world

31
Q

What are the main things that affect the statistical power of a study?

A
  • Alpha
  • Effect size
  • Variance
  • Sample size
32
Q

Increasing alpha will ___ power

A

Increasing alpha will increase power

33
Q

An effect size is known as the ____

A

An effect size is known as the mean difference

34
Q

What is standardized effect size?

A

The mean difference divided by the variance

35
Q

___ is the spread of scores

A

Variance is the spread of scores

36
Q

Increasing the effect size will ___the power

A

Increasing the effect size will increase the power

37
Q

Increasing the sample size will ___the power

A

Increasing the sample size will increase the power

38
Q

___ is the best way to increase statistical power

A

Sample size is the best way to increase statistical power

39
Q

Increasing variance will ___ power

A

Increasing variance will decrease power

40
Q

What are the things that will decrease power?

A
  • Decreased alpha
  • Decreased effect size
  • Increased variance
  • Decreased sample size
41
Q

What are the two types of power analysis?

A
  • Power a priori

- Power post-hoc

42
Q

What is power a priori?

A

A power analysis done before we collect data, to determine if the design is powerful enough

43
Q

What is power post-hoc?

A

Power analysis done after the research is complete by the consumers to find if there was enough power/ if they failed to reject the null hypothesis

44
Q

If a difference is found post-hoc/the null hypothesis was rejected, then the power issue is ___

A

If a difference is found post-hoc/the null hypothesis was accepted/fail to reject, then the power issue is moot/not a problem

45
Q

If a difference not is found post-hoc/the null hypothesis was accepted/fail to reject, then the power issue is ___ and you have to do a ___

A

If a difference not is found post-hoc/the null hypothesis was accepted/fail to reject, then the power issue is huge and you have to do a post-hoc analysis

46
Q

A priori is used to figure out how many subjects to use ___

A

A priori is used to figure out how many subjects to use before a study is started

47
Q

What is the minimal accepted power during power a priori?

A

0.8

48
Q

What are the 2 ways to determine a post doc analysis?

A
  1. Compute with traditional cohen approach

2. Determine with confidence interval analysis of effect size

49
Q

What is involved in computing the post doc analysis with the traditional approach?

A 
• Continuous scale result: 0.0 – 1.0 ( > 0.8 is default)
• Based on:
   • Sample size
   • Alpha
   • Variance (observed)
   • Effect size (use MCID, not 
      observed)
50
Q

____ is the better way to determine the post hoc analysis, while with ____, the answer will probably be the same as a priori

A

Determine with confidence interval analysis of effect size is the better way to determine the post hoc analysis, while with compute with traditional cohen approach, the answer will probably be the same as a priori

51
Q

If the MCID is excluded from the CI, then it is definitively negative and ___ powered

A

If the MCID is excluded from the CI, then it is definitively negative and adequately powered

52
Q

If the MCID is included from the CI, then it is not definitive and ___ powered

A

If the MCID is included from the CI, then it is not definitive and inadequately powered/ underpowered

53
Q

A two tailed testis testing to see ____

A

A two tailed testis testing to see if your calculated value is either above or below where it is expected to be

54
Q

A one tailed test is testing to see if ____ or ___

A

A one tailed test is testing to see if your calculated value is above where it’s expected to be or below where it is expected to be

55
Q

___ is the assumption you’re beginning with and is opposite of what you’re testing

A

Null hypothesis(H0) is the assumption you’re beginning with and is opposite of what you’re testing

56
Q

___ is the claim you’re testing

A

Alternating hypothesis is the claim you’re testing

EBP 2 (7 decks)

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