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18 Cards in this Set
- Front
- Back
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z score |
Compare one individual’s score to a group |
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z test |
To compare a sample mean to a population mean. The population standard deviation must be provided |
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one sample t test |
To compare a sample mean to a population mean. The population standard deviation is not provided |
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independent groups t test |
To compare the means of two separate groups. These groups are not paired or matched. |
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matched group t test |
To compare the means of two groups, and the two groups arepaired. Or you can use this test to compare the means of the same group ofindividuals measured two times. |
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one factor ANOVA |
To compare the means of multiple groups, and there is one independent variable. |
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two factor ANOVA |
To compare the means of multiple groups. There are two independent variables. |
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correlation |
To determine the strength and direction of the relationship between two continuous variables. You can graph these data in a scatterplot.There are no means. |
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regression |
you can predict an individual’s Y score based on a given X score. |
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chi-square |
You have only categorical data, with no means. Participants fall into certain categories. Individuals fit into categories (number of people in different categories). |
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step 1 chi-square |
Ha: Ho: |
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step 2 chi-square |
n= |
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step 3 |
a) E(x^2)= b) not calculated c)x^2 distribution |
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step4 chi |
.05 |
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step 5 chi |
graph retention rejection E(x^2) df |
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step 6 |
x^2= (sum (fo-fe)^2)/fe |
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step 7 |
reject/retain |
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step 8 |
x/x ____________ (%) y/y ______________ (%) differs significantly X^2(df)= _______, p=.05 _________ more likely _________ |
