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Ch 29: ACT Math: Data and Statistics

About This Chapter

Get ready for the ACT Math exam by using this chapter to review data and statistics. Make sure you understand how to view and display data effectively with these lessons and quizzes.

ACT Math: Data and Statistics - Chapter Summary

Use this chapter to ensure you're familiar with the uses of data and statistics as you prepare for the ACT Math exam. These lessons will help you go over:

  • Statistical analysis with data
  • Bar graphs, pie charts, line graphs, histograms and tables
  • Two-way, relative and cumulative frequency tables
  • Estimating and making predictions from categorical and quantitative data
  • Categorical and quantitative data
  • Center, shape, spread, mean, median, mode and range
  • Relationships between quantitative variables

We offer short video lessons that will walk you through each of these mathematical concepts. A text transcript with key terms and a self-assessment quiz accompanies each lesson. If you have any difficulties with these lessons, our expert instructors are available to answer your questions.

10 Lessons in Chapter 29: ACT Math: Data and Statistics
Test your knowledge with a 30-question chapter practice test
How to Interpret Information From Graphs

1. How to Interpret Information From Graphs

Graphs are an excellent way to condense a lot of information into an easily readable format. In this lesson, you'll learn about reading and interpreting information from graphs.

Visual Representations of a Data Set: Shape, Symmetry & Skewness

2. 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.

Statistical Analysis with Categorical Data

3. Statistical Analysis with Categorical Data

Learn why percentages are so important when analyzing categorical data in this video lesson. Watch as the data is turned into a data table and a visual bar graph as ways to analyze the data.

What is Bivariate Data? - Definition & Examples

4. What is Bivariate Data? - Definition & Examples

In this lesson, you will be learning about the definition and uses of bivariate data. We will also compare and contrast the characteristics of univariate data and bivariate data.

Understanding Bar Graphs and Pie Charts

5. Understanding Bar Graphs and Pie Charts

In this lesson, we will examine two of the most widely used types of graphs: bar graphs and pie charts. These two graphs can provide the reader with a comparison of the different data that is displayed.

Make Estimates and Predictions from Categorical Data

6. Make Estimates and Predictions from Categorical Data

Categorical data can be estimated but not predicted. Learn why in this video lesson along with how to read and gather information from a bar graph of categorical data.

How to Calculate Mean, Median, Mode & Range

7. 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.

Spread in Data Sets: Definition & Example

8. 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.

Describing the Relationship between Two Quantitative Variables

9. Describing the Relationship between Two Quantitative Variables

In this video lesson, you will learn about quantitative variables, what they are, and how one variable relates to another. You will learn why this is important and why it can sometimes even save lives.

Making Estimates and Predictions using Quantitative Data

10. Making Estimates and Predictions using Quantitative Data

Watch this video lesson to learn how you can read a scatter plot to learn more about a particular situation. Also learn how you can make estimates within the range of data you have and predict what may happen outside the range of data.

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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