hcistats:start

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hcistats:start [2014/04/22 08:50] Koji Yatani [Methods to Complement Null Hypothesis Significance Testing] |
hcistats:start [2014/04/22 14:36] (current) Koji Yatani [Experimental Design] |
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**My suggestion is that you should think about what statistical tests you will use when you think about the experimental design**. Although there are many kinds of statistical tests, some tests requires you to exercise lots of cautions to perform. Thus, it is better to design an experiment so that you can just do a simple or common statistical test. **It is also helpful to make the experiment simple** for the analysis. A simple experiment generally needs only simple statistical tests. If the experiment you are going to do doesn't look simple or is not commonly done in HCI research, make sure you can run an appropriate statistical test after the experiment. | **My suggestion is that you should think about what statistical tests you will use when you think about the experimental design**. Although there are many kinds of statistical tests, some tests requires you to exercise lots of cautions to perform. Thus, it is better to design an experiment so that you can just do a simple or common statistical test. **It is also helpful to make the experiment simple** for the analysis. A simple experiment generally needs only simple statistical tests. If the experiment you are going to do doesn't look simple or is not commonly done in HCI research, make sure you can run an appropriate statistical test after the experiment. | ||

- | Another thing you should be careful about is the type of data. **Try to make your dependent variable ratio or interval**. This allows you to do a much wider variety of statistical tests than ordinal and nominal data. If you cannot make it ratio or interval, think about making it ordinal. If this is not possible either, you have to give up and have nominal data, but make sure that you can do an appropriate analysis on them, and can test what you want to examine after the experiment. You can see more details about the types of data [[HCIstatsDataType|here]]. | + | Another thing you should be careful about is the type of data. **Try to make your dependent variable ratio or interval**. This allows you to do a much wider variety of statistical tests than ordinal and nominal data. If you cannot make it ratio or interval, think about making it ordinal. If this is not possible either, you have to give up and have nominal data, but make sure that you can do an appropriate analysis on them, and can test what you want to examine after the experiment. You can see more details about the types of data [[HCIstats:DataType|here]]. |

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hcistats/start.txt ยท Last modified: 2014/04/22 14:36 by Koji Yatani