About This Chapter
WEST Math: Summarizing Data - Chapter Summary
As you work through the quick, entertaining video lessons in this chapter, you'll cover the important data summarization concepts you'll likely encounter on your WEST Math assessment. As you navigate through the material, you will cover:
- The mean, median, mode, range and center of a data set
- Visual representations of data sets
- Unimodal and bimodal distributions, dispersion and skewness
- Maximums, minimums, outliers and quartile and interquartile ranges
- How to calculate percentiles and standard deviation in a data set
- Population and sample variance
Take the quiz after each lesson to assess your comprehension of the data summary concepts you've reviewed. Video transcripts highlight key terms and make it easy to get additional review. If you get hung up, reach out to our instructors for support.
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 within the NES Mathematics - WEST (304): Practice & Study Guide course
- WEST Math: Properties of Real Numbers
- WEST Math: Fractions
- WEST Math: Decimals & Percents
- WEST Math: Ratios & Proportions
- WEST Math: Units of Measure & Conversions
- WEST Math: Logic
- WEST Math: Reasoning
- WEST Math: Vector Operations
- WEST Math: Matrix Operations & Determinants
- WEST Math: Exponents & Exponential Expressions
- WEST Math: Algebraic Expressions
- WEST Math: Linear Equations
- WEST Math: Inequalities
- WEST Math: Absolute Value
- WEST Math: Quadratic Equations
- WEST Math: Polynomials
- WEST Math: Rational Expressions
- WEST Math: Radical Expressions
- WEST Math: Systems of Equations
- WEST Math: Complex Numbers
- WEST Math: Functions
- WEST Math: Piecewise Functions
- WEST Math: Exponential & Logarithmic Functions
- WEST Math: Continuity of a Function
- WEST Math: Limits
- WEST Math: Rate of Change
- WEST Math: Derivative Rules
- WEST Math: Graphing Derivatives
- WEST Math: Applications of Derivatives
- WEST Math: Area Under the Curve & Integrals
- WEST Math: Integration Techniques
- WEST Math: Applications of Integration
- WEST Math: Foundations of Geometry
- WEST Math: Geometric Figures
- WEST Math: Properties of Triangles
- WEST Math: Triangle Theorems & Proofs
- WEST Math: Parallel Lines & Polygons
- WEST Math: Quadrilaterals
- WEST Math: Circles & Arc of a Circle
- WEST Math: Conic Sections
- WEST Math: Geometric Solids
- WEST Math: Analytical Geometry
- WEST Math: Trigonometric Functions
- WEST Math: Trigonometric Graphs
- WEST Math: Solving Trigonometric Equations
- WEST Math: Trigonometric Identities
- WEST Math: Sequences & Series
- WEST Math: Set Theory
- WEST Math: Statistics Overview
- WEST Math: Tables, Plots & Graphs
- WEST Math: Probability
- WEST Math: Discrete Probability Distributions
- WEST Math: Continuous Probability Distributions
- WEST Math: Sampling
- NES Mathematics WEST Flashcards