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1: Naming, Collecting Data and Research Design

  • Page ID
    39712
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    In today’s society, we are bombarded with data on all forms of media. The question is who, how and where does the data originate. That’s why I am excited about this unit because we will explore types of data and its’ influences of collecting the data.

    • 1.1: Introduction
      Included in this chapter are the basic ideas of statistics. You will soon understand how to classify data in statistics. You will also learn how data are gathered and what "good" data can be distinguished from "bad."
    • 1.2: Definitions of Statistics and Key Terms
      The mathematical theory of statistics is easier to learn when you know the language. This module presents important terms that will be used throughout the text.
    • 1.3: Sampling Strategy
      Data are individual items of information that come from a population or sample. Data may be classified as qualitative, quantitative continuous, or quantitative discrete. Because it is not practical to measure the entire population in a study, researchers use samples to represent the population. A random sample is a representative group from the population chosen by using a method that gives each individual in the population an equal chance of being included in the sample.
    • 1.4: Levels of Measurement
      It is necessary to classify data based on its level of measurement in order to organize, display and describe. In this section, we will define the different level of measurements.
    • 1.5: Research Design and Ethics
      A poorly designed study will not produce reliable data. There are certain key components that must be included in every experiment. To eliminate lurking variables, subjects must be assigned randomly to different treatment groups. One of the groups must act as a control group, demonstrating what happens when the active treatment is not applied. Participants in the control group receive a placebo treatment that looks exactly like the active treatments but cannot influence the response variable.
    • 1.6: Data Collection Experiment (Worksheet)
      A statistics Worksheet: The student will demonstrate the systematic sampling technique. The student will construct relative frequency tables. The student will interpret results and their differences from different data groupings.
    • 1.7: Sampling Experiment (Worksheet)
      A statistics Worksheet: The student will demonstrate the simple random, systematic, stratified, and cluster sampling techniques. The student will explain the details of each procedure used.
    • 1.8: Sampling and Data (Exercises)
      These are homework exercises to accompany the Textmap created for "Introductory Statistics" by OpenStax.

    Contributors and Attributions

    Barbara Illowsky and Susan Dean (De Anza College) with many other contributing authors. Content produced by OpenStax College is licensed under a Creative Commons Attribution License 4.0 license. Download for free at http://cnx.org/contents/30189442-699...b91b9de@18.114.


    This page titled 1: Naming, Collecting Data and Research Design is shared under a CC BY-SA 1.3 license and was authored, remixed, and/or curated by OpenStax via source content that was edited to the style and standards of the LibreTexts platform.