About This Chapter
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.
1. 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.
2. 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.
3. Summarizing Categorical Data using Tables
Watch this video lesson to find out why data tables are an excellent way to summarize your categorical data. Learn what you need to do to your data before constructing a table and the two ways you can show your data.
4. How to Calculate Percent Increase with Relative & Cumulative Frequency Tables
In statistics, one way to describe and analyze data is by using frequency tables. This lesson will discuss relative and cumulative frequencies and how to calculate percent increase using these two methods.
5. What is a Two-Way Table?
Do you believe in Martians? Do you watch football on television? A Two-Way Table or Contingency Table is a great way to show the results of all kinds of survey questions. In this video we will learn how to read a two-way table.
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.
7. What is Quantitative Data? - Definition & Examples
Watch this video lesson to find out the difference between saying you have seven apples and saying that those apples are delicious. You will learn about quantitative data and why it is useful.
8. What is a Histogram in Math? - Definition & Examples
Watch this video lesson to see how useful a histogram can be when you need to show a bunch of data in an easy to read format. Also, learn how you can easily gather the information you need from looking at a histogram.
9. What are Center, Shape, and Spread?
Center, shape, and spread are all words that describe what a particular graph looks like. Watch this video lesson to see how you can identify and explain each.
10. 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.
11. 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.
12. Reading and Interpreting Line Graphs
Watch this video lesson to find out how useful line graphs can be and how much information you can gain just from looking at one. Learn how you can apply that information in your own life to help you make better decisions.
13. 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.
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