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Ch 49: TExMaT Master Mathematics Teacher 8-12: Summarizing Data

About This Chapter

Let us show all the important elements of summarizing data, as you prepare for the TExMaT Master Mathematics Teacher 8-12 exam. Our video lessons and self-assessment quizzes offer you several different approaches for studying so that you are ready to answer the test questions correctly.

TExMaT Master Mathematics Teacher 8-12: Summarizing Data - Chapter Summary

You can use the lessons contained within this chapter to organize your review of summarizing data in preparation for the TExMaT Master Mathematics Teacher 8-12 exam. The video lessons go over all the material you need to know for the test, including:

  • Data sets
  • Measures of central tendency and how to calculate them
  • How to visually represent a data set
  • Measuring dispersion and skewness
  • Unimodal and bimodal distributions
  • Spread in data sets
  • Quartiles and percentiles
  • Calculating standard deviation
  • Linear transformations
  • Population and sample variance

Our knowledgeable instructors guide you through each point, making it clear and understandable. By using a combination of the videos, quizzes and written transcripts, you are exposed to the information in more than one way, making studying it more effective and easier to retain.

Objectives of the TExMaT Master Mathematics Teacher 8-12: Summarizing Data Chapter

The TExMaT Master Mathematics Teacher 8-12 exam is an evaluation of your knowledge and understanding of all mathematics topics taught within grades 8-12. Your score determines if you can become a Master Mathematics Teacher in the state of Texas, which involves teaching students and mentoring and supervising other teachers. There are 90 multiple-choice questions on the exam. Each one presents a problem or question followed by several response alternatives. From these, you must select the correct answer. There is also one case-study assignment, which allows you to show the depth of your knowledge in an area of 8-12 grade mathematics.

The topic in this Summarizing Data chapter fall within Domain V: Probability and Statistics: Content, Instruction and Assessment, which makes up 14% of the test items. You can check on how well you grasp this content, and gain valuable experience answering questions like those on the test by completing the self-assessment quizzes that accompany the video lessons.

13 Lessons in Chapter 49: TExMaT Master Mathematics Teacher 8-12: 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.
Not Taken
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 TExMaT Master Mathematics Teacher 8-12 (089): Practice & Study Guide course

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