# Ch 36: Michigan Merit Exam - Math: Measures of Center & Variation

### About This Chapter

## Michigan Merit Exam - Math: Measures of Center & Variation - Chapter Summary

Watch quick and fun video lessons about the process of determining the mean, median, and mode. Take one of our quizzes to assess your knowledge of standard deviation. Your use of this chapter's study guides will enable you to answer exam questions based on the following:

- Definition of the center of a data set
- Ways to determine mean, median, and mode
- Distinction between the mean and median
- Definition and examples of spread in data
- Minimums, maximums, and outliers
- Definition of quartiles and interquartile range
- Examples of percentiles
- Standard deviation
- Definition of a population and sample variance

Every video lesson has a transcript that you can read through. They contain bold terms that place emphasis on the terms on which you need to focus. You can view the parts of the videos that address any of the correct answers of your quiz questions if you get any wrong. We have experts and instructors who can answer any questions you may have as you progress through the chapter.

### Michigan Merit Exam - Math: Measure of Center & Variation Objectives

The study guides found in this chapter link to the Statistics and Probability part of the math section of the Michigan Merit Exam. The whole math section is comprised of four segments that contain a total of 25 multiple-choice questions. Also, the exam may include questions asking you to state the benefits of concepts like the mean, median, and mode, and to identify them.

### 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. Calculating the Mean, Median, Mode & Range: Practice Problems

Calculating the mean, median, mode, and range of a data set is a fundamental part of learning statistics. Use this video to practice your skills and then test your knowledge with a short quiz.

### 5. The Mean vs the Median: Differences & Uses

Most people can find the mean and the median of a data set, but do you know when to use the mean and when to use the median to describe the information?

### 6. 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.

### 7. 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.

### 8. 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.

### 9. 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.

### 10. 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.

### 11. 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.

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### Other Chapters

Other chapters within the Michigan Merit Exam - Math: Test Prep & Practice course

- Michigan Merit Exam - Math: Number Systems & Number Sense
- Michigan Merit Exam - Math: Representations & Relationships
- Michigan Merit Exam - Math: Counting & Probabilistic Reasoning
- Michigan Merit Exam - Math: Using Real & Complex Numbers
- Michigan Merit Exam - Math: Sequences & Iteration
- Michigan Merit Exam - Math: Measurement Units, Calculations & Scales
- Michigan Merit Exam - Math: Understanding Error
- Michigan Merit Exam - Math: Mathematical Reasoning
- Michigan Merit Exam - Math: Language, Laws & Proof of Logic
- Michigan Merit Exam - Math: Using Algebraic Expressions
- Michigan Merit Exam - Math: Properties of Functions
- Michigan Merit Exam - Math: Working with Functions
- Michigan Merit Exam - Math: Lines & Linear Functions
- Michigan Merit Exam - Math: Absolute Values
- Michigan Merit Exam - Math: Inequalities
- Michigan Merit Exam - Math: Exponential & Logarithmic Functions
- Michigan Merit Exam - Math: Quadratic Functions
- Michigan Merit Exam - Math: Power Functions
- Michigan Merit Exam - Math: Polynomial Functions
- Michigan Merit Exam - Math: Rational Functions
- Michigan Merit Exam - Math: Trigonometric Functions
- Michigan Merit Exam - Math: Euclidean & Coordinate Geometry
- Michigan Merit Exam - Math: Triangles & Their Properties
- Michigan Merit Exam - Math: Triangles & Trigonometry
- Michigan Merit Exam - Math: Quadrilaterals & Their Properties
- Michigan Merit Exam - Math: Other Polygons & Their Properties
- Michigan Merit Exam - Math: Circles & Their Properties
- Michigan Merit Exam - Math: Conic Sections & Their Properties
- Michigan Merit Exam - Math: 3D Figures
- Michigan Merit Exam - Math: Comparing Area & Volume Formulas
- Michigan Merit Exam - Math: 2D & 3D Representations
- Michigan Merit Exam - Math: Congruence & Similarity
- Michigan Merit Exam - Math: Transformations & Isometries
- Michigan Merit Exam - Math: Dilations & Isometries
- Michigan Merit Exam - Math: Creating & Interpreting Plots
- Michigan Merit Exam - Math: The Normal Distribution
- Michigan Merit Exam - Math: Scatterplots & Correlation
- Michigan Merit Exam - Math: Linear Regression
- Michigan Merit Exam - Math: Data Collection & Analysis
- Michigan Merit Exam - Math: Probability
- Michigan Merit Exam - Math: Application & Representation
- Michigan Merit Exam - Math Flashcards