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Biostatistics > Goodness of fit tests > Flashcards

Goodness of fit tests Flashcards

1
Q

what do goodness of fit tests compare

A

an observed frequency distribution with a theoretical expectation

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2
Q

what is a limit of binomial tests

A

limited to categorical variables with only TWO outcomes

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3
Q

what is the probability model

A

frequency of an event is proportional to the number of opportunities

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4
Q

what type of model is the proportional probability under

A

NULL model

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5
Q

what is the chai goodness of fit test

A

test that compares frequency data to a model stated by the null hypothesis UNDER THE PROPORTION PROBABILITY MODEL

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6
Q

observed vs expected frequency

A

observed - frequency based on actual data collected

expected - frequency based on null hypothesis generated by the proportion probability model

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7
Q

how to find the expected frequency in data

A

take the observed frequency and divide by total observations THEN multiply that proportion by the sample size (n)

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8
Q

how do calculate based on chai squared test

A
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9
Q

what is the test statistic for the chai squared test

A

measure of discrepancy between observed and expected frequencies

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10
Q

what is the formula for the test statistic for this test

A
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11
Q

does chai squared work on absolute or relative frequencies

A

absolute frequency (counted)

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12
Q

degrees of freedom specifies

A

which chai squared distribution to use as the null distribution

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13
Q

define degrees of freedom

A

the number of values in the calculations of a test statistic that may be varied independently

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14
Q

how to calculate degrees of freedom for Chai squared test

A
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15
Q

what is the P-value

A

the probability of getting a result as extreme or more extreme than the observed result under null hypothesis

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16
Q

what are two assumptions for the chai squared test

A
  1. individuals in the data set are random sample of population

2.no categories has EXPECTED frequency LESS than 1

  1. no more than 20% if the categories have EXPECETD frequency below 5
17
Q

what is to be done if the assumptions for this test is VIOLATED

A
  1. blend categories together (that are able to be)
  2. use an alterative test (like binomial test)
18
Q

what does the chai squared goodness of fit test assume

A
  1. random sample
  2. expected frequencies are sufficiently high
19
Q

what does the chai squared goodness of fit test compare

A

frequency data to a model stated by the null hypothesis (generally the proportion probability model)

20
Q

how to determine P value of the test `

A

compare with critical chai value in statistical table

21
Q

does a binomial test provide the exact P value

A

YES

22
Q

when is a binomial test better than a chai squared test

A

when there are only two categories and assumptions of chai squared test are NOT met

23
Q

what other model besides the proportional probability model is used to model the null hypothesis in goodness of fit test s

A

binomial distribution

24
Q

what does it mean if a data set is NOT binomially distributed

A

the assumptions of the binomial distribution must be violated

25
Q

what is the poisson distribution

A

describes the number of success in blocks of time or space

26
Q

contrast the poisson distribution from the binomial distribution

A

binomial
- describes the number of successes in N trials

poisson
- describes the number of successes in blocks or time or space

27
Q

does the poisson distribution have a set sample size

A

NO

28
Q

what are three subcategories for data in a poisson distribution

A
  1. clumped
  2. random
  3. dispersed
29
Q

dispersed vs clumped displays of poisson distribution

A

dispersed
- very little clumping of data
- could be territorial organisms or competition

clumped
- highly grouped data in an area
- could be offspring don’t migrate from parents or animals live in herds

30
Q

how to find mean number of each outcome in data for the poisson distribution

A

sum the products of each row and divide by the n

31
Q

how does variance associate with mean in poisson distribution

A

it EQULAS the mean

32
Q

what distribution results from the variance being GREATER than the mean (poisson distribution)

A

clumped distribution

33
Q

what distribution results from the variance being LESS than the mean (poisson distribution)

A

dispersed distribution

Biostatistics (9 decks)

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