# Ch 3: Tables and Plots: Help and Review

### About This Chapter

## Who's it for?

Anyone who needs help learning or mastering college statistics material will benefit from taking this course. There is no faster or easier way to learn college statistics. Among those who would benefit are:

- Students who have fallen behind in understanding the various types of tables and plots or working with univariate and bivariate data
- Students who struggle with learning disabilities or learning differences, including autism and ADHD
- Students who prefer multiple ways of learning math (visual or auditory)
- Students who have missed class time and need to catch up
- Students who need an efficient way to learn about tables and plots
- Students who struggle to understand their teachers
- Students who attend schools without extra math learning resources

## How it works:

- Find videos in our course that cover what you need to learn or review.
- Press play and watch the video lesson.
- Refer to the video transcripts to reinforce your learning.
- Test your understanding of each lesson with short quizzes.
- Verify you're ready by completing the Tables and Plots chapter exam.

## Why it works:

**Study Efficiently**: Skip what you know; review what you don't.**Retain What You Learn**: Engaging animations and real-life examples make topics easy to grasp.**Be Ready on Test Day**: Use the Tables and Plots chapter exam to be prepared.**Get Extra Support**: Ask our subject-matter experts any tables and plots question. They're here to help!**Study With Flexibility**: Watch videos on any web-ready device.

## Students will review:

This chapter helps students review the concepts in a Tables and Plots unit of a standard college statistics course. Topics covered include:

- Frequency and relative frequency tables
- Cumulative frequency tables
- Stem and leaf displays
- Histograms, frequency polygons, dot plots and box plots
- Bar graphs and pie charts

### 1. Frequency & Relative Frequency Tables: Definition & Examples

Frequency and relative frequency tables are useful ways to understand data. Further explore the definition of frequency and relative frequency tables are and how to create and interpret them with examples.

### 2. Cumulative Frequency Tables: Definition, Uses & Examples

Cumulative frequency tables are charts that display the mode of a set of data and the likelihood that a specific event will fall below the frequency distribution. Learn about the definition, practical uses, and examples of cumulative frequency tables.

### 3. How to Calculate Percent Increase with Relative & Cumulative Frequency Tables

Statistics often are expressed as percentages. Learn how to calculate percent increase using relative and cumulative frequency tables by exploring relative and cumulative frequencies, reviewing how to organize frequency data in a frequency table, and applying formulas to calculate percent increases.

### 4. Creating & Reading Stem & Leaf Displays

Creating and reading stem-and-leaf displays are relevant to understanding how to interpret visual data sets. Learn to identify what a stem-and-leaf display is and why it is useful.

### 5. Creating & Interpreting Histograms: Process & Examples

A histogram is a diagram that provides a graphical picture of the points in a data set. Learn about creating and interpreting histograms by exploring the process and examples. Understand the purpose of histograms, practice interpreting a histogram, and recognize when data is skewed and what this means.

### 6. Creating & Interpreting Frequency Polygons: Process & Examples

A frequency polygon is a graphing device used to aid in understanding shape distributions. This lesson explores that concept, discussing how they are created and how they can be interpreted.

### 7. Creating & Interpreting Dot Plots: Process & Examples

Dot plots allow for the visualization of frequency distribution from a given data set. Explore the use of dot plots, steps in creating them from data, and the process of interpreting them through examples provided.

### 8. Creating & Interpreting Box Plots: Process & Examples

A box plot is an essential tool to help with statistical analysis by using both graphs and number lines to assist in visualizing the data. Discover how to create and interpret box plots by learning each separate element in the process and work through real-world examples.

### 9. Understanding Bar Graphs and Pie Charts

Bar graphs and pie charts are some of the most used graphical ways to present data. Learn how to read bar graphs and pie charts, and explore some examples to understand how they are interpreted.

### 10. Making Arguments & Predictions from Univariate Data

Univariate data can be analyzed with measures, such as the mean, median, and mode, to make arguments and predictions. Learn what univariate data is, understand how the measures of central tendency are used, and explore data analysis with graphs and tables.

### 11. What is Bivariate Data? - Definition & Examples

The primary purpose of bivariate data is to compare two sets of data or to find a relationship between two variables. Read more about the usage, definition, and examples of bivariate data.

### 12. What is a Two-Way Table?

A two-way table, also known as a contingency table, is used to display the frequency data of two categorical variables. Learn some tips on how to use and how to analyze two-way tables.

### 13. Joint, Marginal & Conditional Frequencies: Definitions, Differences & Examples

Categorical variables can be analyzed by using joint, marginal, and conditional relative frequencies. Explore the concept of the frequencies, how to define the terms and discuss the differences between the frequencies, and learn how they work by investigating examples.

### Earning College Credit

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### Other Chapters

Other chapters within the Introduction to Statistics: Help and Review course

- Overview of Statistics: Help and Review
- Summarizing Data: Help and Review
- Probability: Help and Review
- Discrete Probability Distributions: Help and Review
- Continuous Probability Distributions: Help and Review
- Sampling: Help and Review
- Regression & Correlation: Help and Review
- Hypothesis Testing in Statistics