Chapter 1 · free to read

Sampling and Data

15 units from Introduction to Statistics, each written from the passage it teaches and checked against it. Practice questions and reviews come with a free account.

15 lessons in this chapter

Free to read, no account needed. Each one is a few minutes.

1Statistics and Data FundamentalsStatistics involves collecting and analyzing data, and key terms like population, sample, and data are defined and distinguished.
2Parameters and VariablesA parameter describes a population, a statistic describes a sample, and variables can be numerical or categorical.
3Qualitative DataQualitative data describe attributes or categories of a population and are also called categorical data.
4Quantitative Data TypesQuantitative data are numerical and can be classified as discrete if they result from counting or continuous if they result from measuring.
5Graphical displays for qualitative dataChoose and interpret pie charts, bar graphs, and Pareto charts for categorical data, and recognize when pie charts are inappropriate.
6Random sampling methodsApply simple random, stratified, cluster, and systematic sampling to select representative samples from a population.
7Sampling Methods and ErrorsDifferent sampling methods (convenience, with/without replacement) and errors (sampling, nonsampling, bias, self-selected) affect how representative a sample is of the population.
8Bias and Causality in EvaluationWhen evaluating studies, consider non-response bias, confounding variables, and the distinction between correlation and causation to judge whether conclusions are valid.
9Variation in Data and SamplesVariation is natural in data and samples, and larger random samples tend to be more representative of the population.
10Levels of MeasurementData can be classified into nominal, ordinal, interval, and ratio scales, which determine the appropriate statistical analyses.
11Levels of MeasurementClassify data into nominal, ordinal, interval, or ratio levels and identify which arithmetic operations are meaningful for each.
12Frequency tables and relative frequenciesConstruct frequency, relative frequency, and cumulative relative frequency tables from raw data and interpret them.
13Randomized Experiments and BlindingRandomized experiments with control groups and blinding establish causation by isolating explanatory and response variables and controlling lurking variables.
14Ethical Standards in Human ResearchHuman research must be reviewed by Institutional Review Boards and obtain informed consent to protect participants.
15Data collection and sampling experimentsDemonstrate systematic, simple random, stratified, and cluster sampling techniques and construct relative frequency tables from collected data.

Start the first lesson

Keep going with a free account

Practice questions for this chapter, spaced reviews that make it stick, and 12 more chapters:

Chapter 2: Descriptive Statistics
Chapter 3: Probability Topics
Chapter 4: Discrete Random Variables
Chapter 5: Continuous Random Variables
Chapter 6: The Normal Distribution
Chapter 7: The Central Limit Theorem
Chapter 8: Confidence Intervals
Chapter 9: Hypothesis Testing with One Sample
Chapter 10: Hypothesis Testing with Two Samples
Chapter 11: The Chi-Square Distribution
Chapter 12: Linear Regression and Correlation
Chapter 13: F Distribution and One-Way ANOVA

Source

Barbara Illowsky and Susan Dean

Licensed under CC BY 4.0. This course is an adaptation, not the original work.

Access for free at openstax.org/details/books/introductory-statistics-2e

Clear the page · $6.67/mo