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Statistics LibreTexts

1: Sampling and Data

[ "article:topic-guide", "OpenStax", "authorname:openstax" ]
  • Page ID
    690
  • Included in this chapter are the basic ideas and words of probability and statistics. You will soon understand that statistics and probability work together. You will also learn how data are gathered and what "good" data can be distinguished from "bad."

    • 1.0: Introduction
      Included in this chapter are the basic ideas and words of probability and statistics. You will soon understand that statistics and probability work together. You will also learn how data are gathered and what "good" data can be distinguished from "bad."
    • 1.1: Definitions of Statistics, Probability, 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.
    • 1.2: Data, Sampling, and Variation in Data and Sampling
      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.
    • 1.3: Frequency, Frequency Tables, and Levels of Measurement
      Some calculations generate numbers that are artificially precise. It is not necessary to report a value to eight decimal places when the measures that generated that value were only accurate to the nearest tenth. Round off your final answer to one more decimal place than was present in the original data. This means that if you have data measured to the nearest tenth of a unit, report the final statistic to the nearest hundredth.
    • 1.4: Experimental 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.
    • 1.5: 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.
    • 1.6: 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.E: Sampling and Data (Exercises)
      These are homework exercises to accompany the Textmap created for "Introductory Statistics" by OpenStax.

    Contributors

    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.