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Ben
Ben
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One-way ANOVA (analysis of variance) is typically used when you have a categorical independent variable (with two or more categories) and a normally distributed continuous dependent variable (DV). It allows you to test for differences in the mean of the DV across the levels of the independent variable. So, in your case, it would allow you to test the hypothesis that for a particular obstacle variable, students who encountered that obstacle had a different mean exam score than students who did not.

You can read about the assumptions of this test and how to deal with situations when one or more of those assumptions is not met here: https://statistics.laerd.com/statistical-guides/one-way-anova-statistical-guide.phphere

There. There was also a previous question about ANOVA assumptions:   Checking ANOVA assumptionshere.

One-way ANOVA (analysis of variance) is typically used when you have a categorical independent variable (with two or more categories) and a normally distributed continuous dependent variable (DV). It allows you to test for differences in the mean of the DV across the levels of the independent variable. So, in your case, it would allow you to test the hypothesis that for a particular obstacle variable, students who encountered that obstacle had a different mean exam score than students who did not.

You can read about the assumptions of this test and how to deal with situations when one or more of those assumptions is not met here: https://statistics.laerd.com/statistical-guides/one-way-anova-statistical-guide.php

There was also a previous question about ANOVA assumptions: Checking ANOVA assumptions

One-way ANOVA (analysis of variance) is typically used when you have a categorical independent variable (with two or more categories) and a normally distributed continuous dependent variable (DV). It allows you to test for differences in the mean of the DV across the levels of the independent variable. So, in your case, it would allow you to test the hypothesis that for a particular obstacle variable, students who encountered that obstacle had a different mean exam score than students who did not.

You can read about the assumptions of this test and how to deal with situations when one or more of those assumptions is not met here. There was also a previous question about ANOVA assumptions  here.

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AlexK
AlexK
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One-way ANOVA (analysis of variance) is typically used when you have a categorical independent variable (with two or more categories) and a normally distributed continuous dependent variable (DV). It allows you to test for differences in the mean of the DV across the levels of the independent variable. So, in your case, it would allow you to test the hypothesis that for a particular obstacle variable, students who encountered that obstacle had a different mean exam score than students who did not.

If your exam score values are not normally distributed, you may first needYou can read about the assumptions of this test and how to perform a transformationdeal with situations when one or more of those values to make yourassumptions is not met here: https://statistics.laerd.com/statistical-guides/one-way-anova-statistical-guide.php

There was also a previous question about ANOVA results valid.assumptions: Checking ANOVA assumptions

One-way ANOVA (analysis of variance) is typically used when you have a categorical independent variable (with two or more categories) and a normally distributed continuous dependent variable (DV). It allows you to test for differences in the mean of the DV across the levels of the independent variable. So, in your case, it would allow you to test the hypothesis that for a particular obstacle variable, students who encountered that obstacle had a different mean exam score than students who did not.

If your exam score values are not normally distributed, you may first need to perform a transformation of those values to make your ANOVA results valid.

One-way ANOVA (analysis of variance) is typically used when you have a categorical independent variable (with two or more categories) and a normally distributed continuous dependent variable (DV). It allows you to test for differences in the mean of the DV across the levels of the independent variable. So, in your case, it would allow you to test the hypothesis that for a particular obstacle variable, students who encountered that obstacle had a different mean exam score than students who did not.

You can read about the assumptions of this test and how to deal with situations when one or more of those assumptions is not met here: https://statistics.laerd.com/statistical-guides/one-way-anova-statistical-guide.php

There was also a previous question about ANOVA assumptions: Checking ANOVA assumptions

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AlexK
AlexK
  • 1.2k
  • 7
  • 12

One-way ANOVA (analysis of variance) is typically used when you have a categorical independent variable (with two or more categories) and a normally distributed continuous dependent variable (DV). It allows you to test for differences in the mean of the DV across the levels of the independent variable. So, in your case, it would allow you to test the hypothesis that for a particular obstacle variable, students who encountered that obstacle had a different mean exam score than students who did not.

If your exam score values are not normally distributed, you may first need to perform a transformation of those values to make your ANOVA results valid.