Statistics 2037 - Chapter 5 Experiments and Observational Studies.docx

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Department
Statistical Sciences
Course
Statistical Sciences 2037A/B
Professor
Emad Mohammad
Semester
Fall

Description
Chapter 5 – Experiments and Observational Studies Explanatory Variable – attempts to explain/cause differences in response variable Response Variable – the response/outcome Treatment – combination of categories of the explanatory variable assigned by the experimenter, incorporates a collection of conditions Randomized Experiment – create differences in the explanatory variable Observational Study – observe differences in explanatory variable and see if it is related to response variable We may use observational study over an experiment because the experiment may be unethical or explanatory variable can’t be randomly assigned (what hand do you write with) Confounding variable – one that has 2 properties. It is related to the explanatory variable (differ in explanatory variable means they will differ in the confounding variable). It also affects the explanatory variable (this effect cannot be separated). (Example: smoking affects IQ, nutrition affects IQ, smoking and nutrition are related) Interactions – between explanatory variables. The effect of one explanatory variable on a response variable depends on the state of another explanatory variable. Example: smoking affects IQ with no exercise) Experimental Units – smallest basic object to which we can assign different treatments in a randomized experiment Observational Units – the objects measured in a study Participants – used when observational units are people Volunteers – most participants in studies Passive Volunteer – those that sign a consent form and agree to participate When choosing a sample for a randomized example we need to worry about each participant having an equal amount of receiving each treatment. The decision on which treatment a participant receives should be random. Randomizati
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