# Ch 51: PLACE Mathematics: Summarizing Data

### About This Chapter

## PLACE Mathematics: Summarizing Data - Chapter Summary

Use our self-paced video lessons and transcripts in this chapter to get ready for answering questions related to analyzing data sets and dividing data into groups. Let us help you master the statistical concepts you'll need to know for the exam, including:

- Determining the center in a data set
- Calculating mean, median and mode
- Identifying visual representations of a data set like shape, symmetry and skewdness
- Applying measures of dispersion and skewness
- Using unimodal and bimodal distributions
- Finding spread in data sets
- Working with maximums, minimums, outliers and percentiles in a data set
- Calculating quartiles and the interquartile range
- Recognizing standard deviation and shifts in the mean
- Determining the effect of linear transformations on measures of center and spread
- Measuring population and sample variance

Get the practice you need answering similar questions by using our multiple-choice quizzes at the end of each lesson. Our subject-matter experts can answer any additional questions you may have to help you pass this test.

### Objectives of the PLACE Mathematics: Summarizing Data Chapter

The PLACE Mathematics exam may include questions that analyze your capacity to solve problems about data sets. The topics in the Summarizing Data chapter fall under the Statistics and Probability portion of the exam, which constitutes 19% of the total math test. All of the questions are multiple-choice and require you to select one correct answer.

### 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.

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### Other Chapters

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

- PLACE Mathematics: Properties of Real Numbers
- PLACE Mathematics: Fractions
- PLACE Mathematics: Decimals & Percents
- PLACE Mathematics: Ratios & Proportions
- PLACE Mathematics: Measurements & Conversions
- PLACE Mathematics: Logic
- PLACE Mathematics: Mathematical Reasoning
- PLACE Mathematics: Vector Operations
- PLACE Mathematics: Matrices & Determinants
- PLACE Mathematics: Exponents & Exponential Expressions
- PLACE Mathematics: Algebraic Expressions
- PLACE Mathematics: Linear Equations
- PLACE Mathematics: Inequalities
- PLACE Mathematics: Absolute Value Problems
- PLACE Mathematics: Quadratic Equations
- PLACE Mathematics: Polynomials
- PLACE Mathematics: Rational Expressions
- PLACE Mathematics: Radical Expressions
- PLACE Mathematics: Systems of Equations
- PLACE Mathematics: Complex Numbers
- PLACE Mathematics: Functions
- PLACE Mathematics: Graphing Piecewise Functions
- PLACE Mathematics: Exponential and Logarithmic Functions
- PLACE Mathematics: Continuity of Functions
- PLACE Mathematics: Limits
- PLACE Mathematics: Rate of Change
- PLACE Mathematics: Calculating Derivatives & Derivative Rules
- PLACE Mathematics: Graphing Derivatives & L'Hopital's Rule
- PLACE Mathematics: Applications of Derivatives
- PLACE Mathematics: Area Under the Curve & Integrals
- PLACE Mathematics: Integration & Integration Techniques
- PLACE Mathematics: Integration Applications
- PLACE Mathematics: Foundations of Geometry
- PLACE Mathematics: Introduction to Geometric Figures
- PLACE Mathematics: Properties of Triangles
- PLACE Mathematics: Triangles, Theorems & Proofs
- PLACE Mathematics: Parallel Lines & Polygons
- PLACE Mathematics: Quadrilaterals
- PLACE Mathematics: Circular Arcs & Circles
- PLACE Mathematics: Conic Sections
- PLACE Mathematics: Geometric Solids
- PLACE Mathematics: Analytical Geometry
- PLACE Mathematics: Using Trigonometric Functions
- PLACE Mathematics: Trigonometric Graphs
- PLACE Mathematics: Solving Trigonometric Equations
- PLACE Mathematics: Trigonometric Identities
- PLACE Mathematics: Sequences & Series
- PLACE Mathematics: Graph Theory
- PLACE Mathematics: Set Theory
- PLACE Mathematics: Overview of Statistics
- PLACE Mathematics: Tables & Plots
- PLACE Mathematics: Probability
- PLACE Mathematics: Discrete Probability Distributions
- PLACE Mathematics: Continuous Probability Distributions
- PLACE Mathematics: Sampling
- PLACE Mathematics: Hypothesis Testing
- PLACE Mathematics: Regression & Correlation
- PLACE Mathematics Flashcards