Data Collection and Experimental Design 1.3 SECTION 1.3 Data Collection and Experimental Design 17 What You Should Learn How to design a statistical study and how to distinguish between an observational study and an experiment How to collect data by using a survey or a simulation How to design an experiment How to create a sample using random sampling, simple random sampling, stratified sampling, cluster sampling, and systematic sampling and how to identify a biased sample Design of a Statistical Study Data Collection Experimental Design Sampling Techniques Design of a Statistical Study The goal of every statistical study is to collect data and then use the data to make a decision. Any decision you make using the results of a statistical study is only as good as the process used to obtain the data. When the process is flawed, the resulting decision is questionable. Although you may never have to develop a statistical study, it is likely that you will have to interpret the results of one. Before interpreting the results of a study, however, you should determine whether the results are reliable. In other words, you should be familiar with how to design a statistical study. Designing a Statistical Study 1. Identify the variable(s) of interest (the focus) and the population of the study. 2. Develop a detailed plan for collecting data. If you use a sample, make sure the sample is representative of the population. 3. Collect the data. 4. Describe the data, using descriptive statistics techniques. 5. Interpret the data and make decisions about the population using inferential statistics. 6. Identify any possible errors. GUIDELINES A statistical study can usually be categorized as an observational study or an experiment. In an observational study, a researcher does not influence the responses. In an experiment, a researcher deliberately applies a treatment before observing the responses. Here is a brief summary of these types of studies. • In an observational study, a researcher observes and measures characteristics of interest of part of a population but does not change existing conditions. For instance, an observational study was conducted in which researchers measured the amount of time people spent doing various activities, such as volunteering, paid work, childcare, and socializing. (Source: U.S. Bureau of Labor Statistics) • In performing an experiment, a treatment is applied to part of a population, called a treatment group, and responses are observed. Another part of the population may be used as a control group, in which no treatment is applied. (The subjects in both groups are called experimental units.) In many cases, subjects in the control group are given a placebo, which is a harmless, fake treatment that is made to look like the real treatment. The responses of both groups can then be compared and studied. In most cases, it is a good idea to use the same number of subjects for each group. For instance, an experiment was performed in which rats in a treatment group were given trimethylamine oxide, a substance present in seafood, while rats in a control group were given water. After performing testing, researchers concluded that trimethylamine oxide reduced mortality related to heart disease in rats that had heart disease. (Source: eLife)
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