Categorical Data: Chi-Square Flashcards

1
Q

What time of data is Chi-square used for?

A

Nominal/categorical data.

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2
Q

What is the Chi-square Goodness of Fit Test?

A

Chi-square with one variable.

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3
Q

What two types of frequency does the Goodness of Fit Test use?

A

It compares the observed frequencies and expected frequencies.

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4
Q

How do you calculate expected frequency in the Goodness of Fit Test?

A

It is the number of participants / number of categories.

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5
Q

What are the two ways to enter data in the Goodness of Fit Test?

A

By participant or total frequency count.

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6
Q

What should you weight cases by?

A

Frequency.

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7
Q

What is a weakness of Chi-square?

A

Unable to tell which categories differ from which.

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8
Q

What is the Chi-square Test of Association?

A

Chi-square with two variables (also known as Pearson’s Chi-square).

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9
Q

How do you calculate expected frequency in the Test of Association?

A

It is the (row total x column total) / grand total.

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10
Q

How do you calculate degrees of freedom for the Test of Association?

A

It is the (number of rows - 1) x (number of columns - 1).

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11
Q

How do you know if results are significant in the Chi-square tests?

A

The calculated statistic should be higher than the table value.

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12
Q

How would you calculate the Odds of females studying Psychology compared to Engineering?

A

Number of females studying Psychology / number of females studying Engineering.

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13
Q

How would you calculate the Odds Ratio of females studying Psychology compared to males?

A

Odds that females will study Psychology / Odds that males will study Psychology.

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14
Q

Name the two main assumptions of Chi-Square.

A

Observations must be independent (each participant should only contribute to one contingency cell).
There should be adequate expected frequencies in each cell.

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15
Q

What is the adequate expected frequencies in each cell?

A

No more than 20% of the expected frequencies should have a value of less than 5.

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16
Q

What is the solution for when expected frequencies exceed the 20% rule for contingency tables larger than 2x2?

A

Collapse variables together.

17
Q

What is the solution for when expected frequencies exceed the 20% rule for 2x2 contingency tables?

A

Use Fisher’s Exact Test statistic instead of Pearson’s Chi-square statistic (this can only be done when sample size is small).

18
Q

Why is categorical data seen as a weakness?

A

It gives us less information than data measured at other levels. We should always try and measure at higher levels.