{"id":751,"date":"2023-03-08T17:53:58","date_gmt":"2023-03-08T17:53:58","guid":{"rendered":"https:\/\/content.one.lumenlearning.com\/introstatstest\/chapter\/experimental-design-learn-it-2\/"},"modified":"2025-10-05T15:03:21","modified_gmt":"2025-10-05T15:03:21","slug":"experimental-design-learn-it-2","status":"publish","type":"chapter","link":"https:\/\/content.one.lumenlearning.com\/introstatstest\/chapter\/experimental-design-learn-it-2\/","title":{"raw":"Experimental Design: Learn It 2","rendered":"Experimental Design: Learn It 2"},"content":{"raw":"

Different Explanatory Variables in One Study<\/h2>\r\n

The treatments<\/b> are the different levels of the factor of interest, or explanatory variable, that you are changing. For example, if the factor of interest is a vaccine, the treatments might be vaccine vs. no vaccine.<\/p>\r\n\r\n[caption id=\"attachment_3595\" align=\"aligncenter\" width=\"750\"]\"Diagram Figure 1. In an experiment, the explanatory variable is what you change, and the response variable is what you measure to see the effect.[\/caption]\r\n\r\n

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nuisance factors<\/h3>\r\n

Nuisance factors<\/strong> are variables that could affect the response variable but are not what the study is investigating.\u00a0These factors are NOT of interest in the study, but may affect a change in the response variable.<\/p>\r\n<\/section>\r\n

Researchers keep these variables constant (the same for everyone) to prevent them from interfering with results. For example, when testing if music affects concentration, researchers might have everyone take the test at the same time of day (controlling time as a nuisance factor) since time of day could also affect concentration.<\/p>\r\n

[ohm2_question hide_question_numbers=1]696[\/ohm2_question]<\/section>\r\n
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[ohm2_question hide_question_numbers=1]697[\/ohm2_question]<\/section>\r\n<\/section>","rendered":"

Different Explanatory Variables in One Study<\/h2>\n

The treatments<\/b> are the different levels of the factor of interest, or explanatory variable, that you are changing. For example, if the factor of interest is a vaccine, the treatments might be vaccine vs. no vaccine.<\/p>\n

\"Diagram
Figure 1. In an experiment, the explanatory variable is what you change, and the response variable is what you measure to see the effect.<\/figcaption><\/figure>\n
\n

nuisance factors<\/h3>\n

Nuisance factors<\/strong> are variables that could affect the response variable but are not what the study is investigating.\u00a0These factors are NOT of interest in the study, but may affect a change in the response variable.<\/p>\n<\/section>\n

Researchers keep these variables constant (the same for everyone) to prevent them from interfering with results. For example, when testing if music affects concentration, researchers might have everyone take the test at the same time of day (controlling time as a nuisance factor) since time of day could also affect concentration.<\/p>\n