Ch 50: MTEL Math: Statistics

About This Chapter

Utilize the lessons in this chapter to review statistical concepts. Refresh your understanding of interpreting and exhibiting scientific data so you can feel prepared for the MTEL Math exam.

MTEL Math: Statistics - Chapter Summary

The lessons in this chapter will help you study for the MTEL Math exam by examining methods for calculating and presenting statistical data. You'll review:

  • Measures of central tendency
  • Calculating mean, median, mode and range
  • Dispersion and skewness measures
  • Quantitative data
  • Statistical variables
  • Categorizing and ranking data
  • Data set center
  • Visual representations of data
  • Normal distributions
  • Unimodal and bimodal distributions
  • Data set spread
  • Data maximums, minimums and outliers
  • Range between quartiles
  • Calculating percentiles
  • Determining standard deviation
  • Regression Analysis

The lessons in this chapter have been formulated by professionals in the field to provide you with several methods for learning. Each lesson contains a short video to help illustrate the material for visual learners. The video's transcript is included as a great resource for taking notes. You can take a self-assessment quiz at the end of each lesson to test your knowledge. If you'd like to review a particular portion of the lesson, use the timeline below the video for easy navigation.

MTEL Math: Statistics - Objectives

The MTEL Math exam is a requirement for educators hoping to teach math courses in Massachusetts. The exam covers five major areas of content related to mathematical concepts. The information covered in this chapter will prepare you for questions regarding data analysis, statistics and probability, which account for 10% of the total score.

The MTEL Math exam is a computer-based test that consists of 100 multiple-choice questions and 2 open-ended response questions. The open-ended response questions account for 20% of the total score and could be related to any of the five major areas of content. You will have four hours to complete the exam, and must receive a score 240 or higher to qualify for professional certification.

16 Lessons in Chapter 50: MTEL Math: Statistics
Test your knowledge with a 30-question chapter practice test
Mean, Median & Mode: Measures of Central Tendency

1. 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

2. 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.

Measures of Dispersion and Skewness

3. 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.

What is Quantitative Data? - Definition & Examples

4. What is Quantitative Data? - Definition & Examples

Watch this video lesson to find out the difference between saying you have seven apples and saying that those apples are delicious. You will learn about quantitative data and why it is useful.

Continuous, Discrete & Categorical Variables: Definition and Examples

5. Continuous, Discrete & Categorical Variables: Definition and Examples

When doing research, variables come in many types. In this lesson, we'll explore the three most common types of variables: continuous, discrete, and categorical.

Ordering & Ranking Data: Process & Example

6. Ordering & Ranking Data: Process & Example

Ordering and ranking data can often be more important than you might think. In addition to being an important part of competitions, ranking data can be another way of analyzing and evaluating research.

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

7. 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!

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

8. 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.

Normal Distribution: Definition, Properties, Characteristics & Example

9. Normal Distribution: Definition, Properties, Characteristics & Example

In this lesson, we will look at the Normal Distribution, more commonly known as the Bell Curve. We'll look at some of its fascinating properties and learn why it is one of the most important distributions in the study of data.

Unimodal & Bimodal Distributions: Definition & Examples

10. 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

11. 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

12. 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

13. 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

14. 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

15. 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.

Regression Analysis: Definition & Examples

16. Regression Analysis: Definition & Examples

Watch this video lesson to learn about regression analysis and how you can use it to help you analyze and better understand data that you receive from surveys or observations. Learn what is involved in regression analysis and what to look out for.

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.
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