# Ch 51: NMTA Math: Summarizing Data

### About This Chapter

## 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.

### 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!

### 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.

### 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.

### 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.

### 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.

### 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!

### 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.

### 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.

### 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.

### 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.

### 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.

### 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.

### 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.

### Earning College Credit

Did you know… We have over 160 college courses that prepare you to earn credit by exam that is accepted by over 1,500 colleges and universities. You can test out of the first two years of college and save thousands off your degree. Anyone can earn credit-by-exam regardless of age or education level.

To learn more, visit our Earning Credit Page

### Transferring credit to the school of your choice

Not sure what college you want to attend yet? Study.com has thousands of articles about every imaginable degree, area of study and career path that can help you find the school that's right for you.

### Other Chapters

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

- NMTA Math: Properties of Real Numbers
- NMTA Math: Fractions
- NMTA Math: Decimals & Percents
- NMTA Math: Ratios & Proportions
- NMTA Math: Units of Measure & Conversions
- NMTA Math: Logic
- NMTA Math: Reasoning
- NMTA Math: Vector Operations
- NMTA Math: Matrix Operations & Determinants
- NMTA Math: Exponents & Exponential Expressions
- NMTA Math: Algebraic Expressions
- NMTA Math: Linear Equations
- NMTA Math: Inequalities
- NMTA Math: Absolute Value
- NMTA Math: Quadratic Equations
- NMTA Math: Polynomials
- NMTA Math: Rational Expressions
- NMTA Math: Radical Expressions
- NMTA Math: Systems of Equations
- NMTA Math: Complex Numbers
- NMTA Math: Functions
- NMTA Math: Piecewise Functions
- NMTA Math: Exponential & Logarithmic Functions
- NMTA Math: Continuity of a Function
- NMTA Math: Limits
- NMTA Math: Rate of Change
- NMTA Math: Derivative Rules
- NMTA Math: Graphing Derivatives
- NMTA Math: Applications of Derivatives
- NMTA Math: Area Under the Curve & Integrals
- NMTA Math: Integration Techniques
- NMTA Math: Applications of Integration
- NMTA Math: Foundations of Geometry
- NMTA Math: Geometric Figures
- NMTA Math: Properties of Triangles
- NMTA Math: Triangle Theorems & Proofs
- NMTA Math: Parallel Lines & Polygons
- NMTA Math: Quadrilaterals
- NMTA Math: Circles & Arc of a Circle
- NMTA Math: Conic Sections
- NMTA Math: Geometric Solids
- NMTA Math: Analytical Geometry
- NMTA Math: Trigonometric Functions
- NMTA Math: Trigonometric Graphs
- NMTA Math: Solving Trigonometric Equations
- NMTA Math: Trigonometric Identities
- NMTA Math: Sequences & Series
- NMTA Math: Graph Theory
- NMTA Math: Set Theory
- NMTA Math: Statistics Overview
- NMTA Math: Tables, Plots & Graphs
- NMTA Math: Probability
- NMTA Math: Discrete Probability Distributions
- NMTA Math: Continuous Probability Distributions
- NMTA Math: Sampling
- NMTA Math: Regression & Correlation
- NMTA Mathematics Flashcards