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6.6: Summary

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    76215
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    Summary of Section 6.1: Introduction

    The first step in conducting research is not to data collection but making decisions about how you will go about providing evidence to support your theory. This first step is known as research design and can be compared to the blueprint of a house. The research design you utilize will be dependent on the purpose of your research: exploration, description, and explanation.

    Summary of Section 6.2: Designs

    The gold standard in political science is the experimental design. In the classic experiment, a treatment (or the independent variable) is administered to a group called the experimental group and observations of the experimental group are compared to a control group. This design is ideal for establishing causality, but experiments are not always feasible. Nonexperimental designs may be used to try to also allow the researcher to draw causal inferences, but it does not have key components of experiments: random assignment, manipulation of the treatment, and a control group.

    Summary of Section 6.3: Components: Sampling

    When conducting research, there is usually a population of interest that is identified. While it may seem ideal to be able to include every case of the population in the study, this is not exactly feasible. Instead, cases from the population are pulled out to create a sample of the population, either through probabilistic or non-probabilistic sampling methods. To provide results that can be generalized back to the population, it is ideal to have a large sample and a sample that reflects the characteristics of the population.

    Summary of Section 6.4: Components: Observations

    An additional research design component is collecting observations. Observations can be collected through multiple tools, but two popular tools are surveys and interviews. Another aspect of observation collection that needs to be considered is how often observations will be collected. When observations are collected only once, this is called a cross-section. When observations are collected multiple times on the same cases in a set time period, this is known as longitudinal data.


    This page titled 6.6: Summary is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by Josue Franco, Charlotte Lee, Kau Vue, Dino Bozonelos, Masahiro Omae, & Steven Cauchon (ASCCC Open Educational Resources Initiative (OERI)) via source content that was edited to the style and standards of the LibreTexts platform.

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