Chi-Square Flashcards

1
Q

what do parametric tests make assumptions about?

A

population parameters

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2
Q

what do parametric tests require?

A

interval or ratio scale data

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3
Q

what can non-parametric tests be used as?

A

an alternative as distribution-free tests

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4
Q

what do non-parametric tests require?

A

nominal data, but they are not as powerful and may fail to detect differences

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5
Q

what does the goodness for fit test look at?

A

categories of one variable

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6
Q

what is the goodness for fit test used on?

A

used on unrelated data to answer questions about the proportions of a population distribution

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7
Q

X^2

A

the observed and expected frequencies

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8
Q

what are observed frequencies?

A

number of participants measured in individual categories

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9
Q

no preference null hypothesis

A

number of people would be predicted to be equal between the two categories

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10
Q

expected frequencies

A

(proportion x sample size)

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11
Q

x^2 formula

A

sigma (fO - fE) ^2 / fE

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12
Q

goodness of fit- degrees of freedom

A

(c-1)

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13
Q

what does the test of independence look at?

A

the relationship between two variables to observe whether they are independent or associated

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14
Q

what is compared in tests of independence?

A

frequency data to expected frequencies from the null hypothesis

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15
Q

test of independence- what does Ho state?

A

the two variables are completely independent and do not affect each other

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16
Q

test of independence- expected frequency

A

(column total x row total) / overall total

17
Q

test of independence- degrees of freedom

A

(r-1) x (c-1)

18
Q

obtained value should be _____ ____ the critical value in order to be significant

A

less than

19
Q

example of interpreting the results

A

there is no significant difference between males and females in smoking behaviour, x^2 (1) = 0.742, p= .389