About This Chapter
HiSET Mathematics: Summarizing Data- Chapter Summary
Make the most of this study guide by watching lesson videos that detail the different ways to group and analyze data sets. Our transcripts also highlight key terms that you'll see on the HiSET, including:
- The center in a data set
- Mean, mode, median and range
- Shape, symmetry and skewdness
- Dispersion and skewness
- Unimodal and bimodal distributions
- Spread, maximums, minimums and outliers in a data set
- Quartiles and the interquartile range
- Percentiles in a data set
- Standard deviation
- The relationship between linear transformations and measures of center and spread
- Population and sample variance
Trained instructors present the video lessons in a humorous style. They use real-world examples so you can enjoy the process as you learn about and master this material.
Objectives of the HiSET Mathematics: Summarizing Data Chapter
Questions related to this Summarizing Data chapter are found in the Data Analysis/Probability Statistics portion of the HiSET. This portion makes up 18% of the entire math test; so of the 50 total questions, roughly nine will be on data analysis and probability statistics.
All of the questions are multiple-choice, so you can use our multiple-choice quizzes to gain confidence and experience with these types of questions.
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. 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.
12. 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 HiSET Mathematics: Prep and Practice course
- HiSET Mathematics: Mathematical Reasoning
- HiSET Mathematics: Properties of Real Numbers
- HiSET Mathematics: Fractions
- HiSET Mathematics: Decimals and Percents
- HiSET Mathematics: Ratios and Proportions
- HiSET Mathematics: Vector Operations
- HiSET Mathematics: Matrices and Determinants
- HiSET Mathematics: Exponents and Exponential Expressions
- HiSET Mathematics: Absolute Value Problems
- HiSET Mathematics: Rational Expressions
- HiSET Mathematics: Radical Expressions
- HiSET Mathematics: Imaginary and Complex Numbers
- HiSET Mathematics: Measurements and Conversions
- HiSET Mathematics: Foundations of Geometry
- HiSET Mathematics: Introduction to Geometric Figures
- HiSET Mathematics: Properties of Triangles
- HiSET Mathematics: Triangle Theorems and Proofs
- HiSET Mathematics: Parallel Lines and Polygons
- HiSET Mathematics: Quadrilaterals
- HiSET Mathematics: Circular Arcs and Circles
- HiSET Mathematics: Geometric Solids
- HiSET Mathematics: Probability
- HiSET Mathematics: Probability Distributions
- HiSET Mathematics: Sampling
- HiSET Mathematics: Regression and Correlation
- HiSET Mathematics: Algebraic Expressions
- HiSET Mathematics: Linear Equations
- HiSET Mathematics: Inequalities
- HiSET Mathematics: Quadratic Equations
- HiSET Mathematics: Polynomials
- HiSET Mathematics: Functions
- HiSET Mathematics Flashcards