occurred naturally. In the context of experiments, the control group consists of subjects who do not receive a treatment, but who are otherwise handled identically to those who do receive the treatment. learn by doing Causation and Experiments The purpose of this activity is to explore the effectiveness of randomization in creating similar treatment groups, in the sense that it balances the groups with respect to other variables that we didn't control for.
Background A local internet service provider (ISP) created two new versions of its software, with alternative ways of implementing a new feature. To find the product that would lead to the highest satisfaction among customers, the ISP conducted an experiment comparing users' preferences for the two new versions versus the existing software. The ISP ideally wants to find out which of the three software products causes the highest user satisfaction. It has identified three major potential lurking variables that might affect user satisfaction—gender, age, and hours per week of computer use. In this activity, we will use adults in a hypothetical city as the population of interest to the ISP. We will: • create a simple random sample as the basis for the experimental study of the population, • use randomization to assign individuals to treatment groups, and • verify that randomization prevented the three treatment groups from being different with respect to the most obvious lurking variables. StatCrunch Instructions Tip: Alternative versions are available, click the arrow to switch. To open this file in StatCrunch you must first right-click here and choose "Save Target As" to download the file to your computer. Next click here to open StatCrunch in a separate window and login using your username and password. • Click on the link “Open StatCrunch” at the top of the My StatCrunch page. • To open the data set select the “My computer” link under Load a data set from box on the left side of the page. • Select the "Browse" or “Choose File” (depending on which browser you're using and select the data set you downloaded • Scroll to the bottom of the page and click on “Load File” Our dataset contains the values of the three possible lurking variables: • age: in years • gender: female or male • comp: hours per week of computer use StatCrunch Instructions Tip: Alternative versions are available, click the arrow to switch. The company must rely upon sampling to study its customers' preferences, since the entire population cannot be assigned to treatments. Therefore, we will first choose a simple random sample (SRS) of 450 people for the subjects in the study. To do this in StatCrunch:
• Choose: Data → Sample Columns • Select columns: Age, Gender, Comp • Sample size: 450 • Check: Sample all columns at one time • Store samples: Split across columns • Press: Sample Columns Note that three columns are added called: Sample(Age), Sample(Gender), Sample(Comp) Now we will randomly assign our SRS of 450 subjects to treatment groups, one for each of the three versions of the ISP's software. Let's denote the versions "1," "2," and "3," and create a categorical variable to identify the treatment for each
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