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Find the Mean & Standard Error of the Sampling Distribution

Instructions:

Choose an answer and hit 'next'. You will receive your score and answers at the end.

question 1 of 3

Which of the following is equivalent to the mean?

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1. What is the standard error?

2. How do you find the mean of a data set?

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About This Quiz & Worksheet

This quiz and worksheet set will help you quickly assess your knowledge of standard error and mean in sampling distributions. Topics you'll need to know include the definitions of mean and standard error as well as what a large standard of error signifies.

Quiz & Worksheet Goals

The practice problems in this set of assessments cover the following objectives:

  • Recognize another term for mean
  • Identify a term for adding a collection of values and dividing it by the number of values
  • Recall the definition of standard error
  • Understand what a large standard error represents
  • Identify a term for dividing the standard deviation of a sample by the square root of the sample size

Skills Practiced

This quiz and worksheet is useful for practicing the following skills:

  • Reading comprehension - ensure that you draw the most important information from the related statistics lesson
  • Defining key concepts - ensure that you can accurately define main phrases, such as mean and standard error
  • Information recall - access the knowledge you've gained regarding how the mean and standard error are used to analyze a sampling distribution
  • Knowledge application - use your knowledge to answer questions about standard error to understand how to interpret it

Additional Learning

Find out more on the standard error and mean in sampling distributions in the related lesson Find the Mean & Standard Error of the Sampling Distribution. Objectives of this lesson include:

  • Recall the definition of mean and standard
  • Look at how to find the mean of sampling distributions
  • Understand why a mean may not accurately represent a sample of data
  • View the importance of the standard error when analyzing a sample distribution
  • Examine a real-world example of finding a standard error
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