Ch 51: NMTA Math: Summarizing Data

About This Chapter

These quick, entertaining video lessons cover the data summarization principles and techniques you need for the NMTA Math certification assessment. Review how to find the center of a data set as well ways to calculate measures of central tendency.

NMTA Math: Summarizing Data - Chapter Summary

If you need help boosting your confidence with the data summarization concepts you're expected to know for the NMTA Math assessment, you've come to the right place. Short, engaging videos illustrate the following concepts:

  • Fnding the center, mean, median and mode of a data set
  • Methods for the visual display of data
  • Dispersion and skewness in a data set
  • Data spreads
  • Unimodal and bimodal distributions
  • Maximum, minimum, outliers, and quartiles
  • Calculating percentiles and standard deviation
  • Population and sample variance

Consult the video transcripts for a second look at the most important ideas, which are presented in bold so you can find them quickly. Work through the short self-assessment after each lesson to practice summarizing data and determine whether any concepts need more review.

Objectives of the NMTA Math: Summarizing Data Chapter

The quick, appealing videos in this chapter demonstrate the data summarization rules and methods you're expected to know for the NMTA Math certification exam. Lesson quizzes present a great opportunity to practice the techniques for better retention.

The four-hour-and-fifteen-minute NMTA Math assessment is computer administered and includes 150 selected-response questions. The exam is designed to evaluate your abilities in five areas, and the topics in this chapter are part of the statistics, probability and discrete math section. This section makes up 19% of the entire test.

13 Lessons in Chapter 51: NMTA Math: Summarizing Data
Test your knowledge with a 30-question chapter practice test
What is the Center in a Data Set? - Definition & Options

1. What is the Center in a Data Set? - Definition & Options

Finding the center in a data set can sometimes be a little confusing. This lesson will help you determine the correct method for finding the center in a data set, and when you are finished, test your knowledge with a short quiz!

Mean, Median & Mode: Measures of Central Tendency

2. Mean, Median & Mode: Measures of Central Tendency

By describing the data using central tendency, a researcher and reader can understand what the typical score looks like. In this lesson, we will explore in more detail these measures of central tendency and how they relate to samples and populations.

How to Calculate Mean, Median, Mode & Range

3. How to Calculate Mean, Median, Mode & Range

Measures of central tendency can provide valuable information about a set of data. In this lesson, explore how to calculate the mean, median, mode and range of any given data set.

Visual Representations of a Data Set: Shape, Symmetry & Skewness

4. Visual Representations of a Data Set: Shape, Symmetry & Skewness

Visual representations are a fantastic way of understanding and analyzing your data. Use this lesson to understand the characteristics of visual representations of data.

Measures of Dispersion and Skewness

5. Measures of Dispersion and Skewness

Watch this video lesson to learn how you can describe your data using two different statistical characteristics. Learn what it means for your graph to have variability and what it means for your graph to be skewed.

Unimodal & Bimodal Distributions: Definition & Examples

6. Unimodal & Bimodal Distributions: Definition & Examples

Sometimes a single mode does not accurately describe a data set. In this lesson, learn the differences between and the uses of unimodal and bimodal distribution. When you are finished, test your knowledge with a quiz!

Spread in Data Sets: Definition & Example

7. Spread in Data Sets: Definition & Example

Identifying the spread in data sets is a very important part of statistics. You can do this several ways, but the most common methods are through range, interquartile range, and variance.

Maximums, Minimums & Outliers in a Data Set

8. Maximums, Minimums & Outliers in a Data Set

When analyzing data sets, the first thing to identify is the maximums, minimums, and outliers. This lesson will help you learn how to identify these important items.

Quartiles & the Interquartile Range: Definition, Formulate & Examples

9. Quartiles & the Interquartile Range: Definition, Formulate & Examples

Quartiles and the interquartile range can be used to group and analyze data sets. In this lesson, learn the definition and steps for finding the quartiles and interquartile range for a given data set.

Finding Percentiles in a Data Set: Formula & Examples

10. Finding Percentiles in a Data Set: Formula & Examples

Percentiles are often used in academics to compare student scores. Finding percentiles in a data set can be a useful way to organize and compare numbers in a data set.

Calculating the Standard Deviation

11. Calculating the Standard Deviation

In this lesson, we will examine the meaning and process of calculating the standard deviation of a data set. Standard deviation can help to determine if the data set is a normal distribution.

The Effect of Linear Transformations on Measures of Center & Spread

12. The Effect of Linear Transformations on Measures of Center & Spread

Linear transformations can be a great way to manipulate and analyze data. This lesson will show you how those transformations affect the center and spread of data.

Population & Sample Variance: Definition, Formula & Examples

13. Population & Sample Variance: Definition, Formula & Examples

Population and sample variance can help you describe and analyze data beyond the mean of the data set. In this lesson, learn the differences between population and sample variance.

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

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Other Chapters

Other chapters within the NMTA Mathematics: Practice & Study Guide course

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