# Ch 1: Overview of Statistics

Watch online video lessons and learn about quantitative, continuous and categorical data as well as ratio measurements, random allocation, convenience sampling and more.

## Overview of Statistics - Chapter Summary and Learning Objectives

Let our knowledgeable instructors introduce you to the mathematical science used for research and experimentation in a variety of fields. Begin by learning how to decipher inferential from descriptive statistics and progress through the lessons to discover the uses of categorical and quantitative data or examine the traits of a randomized experiment. Lessons in this chapter are designed to teach you the following:

• Statistical data types
• Levels of measurement
• Model selection methods
• Sources of statistical bias
• Experiment design and analysis

Video Objective
Descriptive and Inferential Statistics Outlines the differences between descriptive and inferential statistics.
What's the Difference Between Populations and Samples? Shows how to determine when a figure represents a population and when it represents a sample, or subset, of a population.
Defining the Difference Between Parameters and Statistics Distinguishes between numerical summaries that are parameters and those that are statistics.
Estimating a Parameter from Sample Data Demonstrates steps for estimating parameters using statistics.
What is Quantitative Data? - Definition & Examples Illustrates when data is quantitative rather than categorical.
What is Categorical Data? Shows how to distinguish categorical data from quantitative data.
Discrete and Continuous Data Outlines the differences between discrete and continuous data.
Nominal, Ordinal, Interval and Ratio Measurements Identifies different levels of measurement.
Evidence for the Strength of a Model through Gathering Data Demonstrates the use of data to provide evidence of a model.
Experiments vs. Observational Studies Contrasts the characteristics of experiments and observational studies.
Random Selection and Random Allocation Illustrates the differences between random selection and random allocation and describes the benefits of each.
Convenience Sampling: Definition and Limitations Explains convenience sampling and the problems associated with its use.
Designing Randomized Experiments Outlines the traits of a good experiment.
Analyzing and Interpreting the Results of Randomized Experiments Demonstrates how to analyze data from randomized experiments and explains which experimental traits are necessary for making inferences.
Confounding and Bias in Statistics Provides strategies for recognizing statistical bias and confounding.
Bias in Polls and Surveys Explains common sources of bias in polls and surveys.
Misleading Uses of Statistics Illustrates some of the common ways statistics are used to mislead.

19 Lessons in Chapter 1: Overview of Statistics
Test your knowledge with a 30-question chapter practice test
Chapter Practice Exam
Test your knowledge of this chapter with a 30 question practice chapter exam.
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Practice Final Exam
Test your knowledge of the entire course with a 50 question practice final exam.
Not Taken
More Exams
There are even more practice exams available in Overview of Statistics.

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