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Ch 11: Big Ideas Math Algebra 2 - Chapter 11: Data Analysis and Statistics

About This Chapter

The Data Analysis and Statistics chapter of this Big Ideas Math Algebra 2 Companion Course aligns with the same chapter in the Big Ideas Math Algebra 2 textbook. These simple and fun video lessons are about five minutes long and help you learn the essential lessons about formulating hypotheses, sampling methods and drawing conclusions from data sets.

How It Works:

  • Find the lesson within this chapter that corresponds to what you're studying in the Data Analysis and Statistics chapter of your textbook.
  • Watch fun videos that cover the data analysis and statistics concepts you need to learn or review.
  • Complete the quiz after watching each video lesson to test your understanding.
  • If you need additional help, rewatch the videos until you've mastered the material, or submit a question for one of our instructors.

Chapter Topics

You'll learn all of the algebra topics covered in the textbook chapter, including:

  • The properties of the Bell Curve
  • What terms like standard score, stanines, z-score, percentile rank and cumulative percentage mean
  • Determining the difference between populations and samples
  • How to develop and write a hypothesis
  • What the types of probability sampling and non-probability sampling are
  • How to avoid biased sampling
  • Choosing data collection techniques and collecting data
  • The advantages and disadvantages of different experimental designs
  • How to draw conclusions from results
  • Using sample proportion

Big Ideas Math is a registered trademark of Larson Texts, Inc., which is not affiliated with Study.com.

14 Lessons in Chapter 11: Big Ideas Math Algebra 2 - Chapter 11: Data Analysis and Statistics
Test your knowledge with a 30-question chapter practice test
Normal Distribution: Definition, Properties, Characteristics & Example

1. Normal Distribution: Definition, Properties, Characteristics & Example

In this lesson, we will look at the Normal Distribution, more commonly known as the Bell Curve. We'll look at some of its fascinating properties and learn why it is one of the most important distributions in the study of data.

Summarizing Assessment Results: Comparing Test Scores to a Larger Population

2. Summarizing Assessment Results: Comparing Test Scores to a Larger Population

Assessment results can yield valuable information about the individual test-taker and the larger population of test-takers. This lesson will describe how to compare test scores to a larger population by explaining standard score, stanines, z-score, percentile rank and cumulative percentage.

Difference between Populations & Samples in Statistics

3. Difference between Populations & Samples in Statistics

Before you start collecting any information, it is important to understand the differences between population and samples. This lesson will show you how!

What is a Hypothesis? - Definition & Explanation

4. What is a Hypothesis? - Definition & Explanation

A hypothesis is an educated prediction that can be tested. You will discover the purpose of a hypothesis then learn how one is developed and written. Examples are provided to aid your understanding, and there is a quiz to test your knowledge.

Probability Sampling Methods: Definition & Types

5. Probability Sampling Methods: Definition & Types

Choosing a sample is one of the most important steps in research. But how should you choose? In this lesson, we'll look at three types of probability sampling: simple random, systematic, and stratified sampling.

Non-Probability Sampling Methods: Definition & Types

6. Non-Probability Sampling Methods: Definition & Types

There are many different ways to choose a sample for a research study. In this lesson, we'll look at three types of non-probability sampling: convenience, quota, and judgmental (or purposive sampling) and when to use each type.

What is a Biased Sample? - Definition & Examples

7. What is a Biased Sample? - Definition & Examples

One goal of research is to obtain the best estimate for a population. The best estimate is an unbiased statistic representative of the population of interest. In this lesson, learn what biased samples are and how to avoid them in your research.

Bias in Statistics: Definition & Examples

8. Bias in Statistics: Definition & Examples

Statistics can be a powerful tool in research. Unfortunately, statistics can also have faults. In this lesson, you will learn about the faults in statistics and how to critically examine potential biases in research.

Strategies for Choosing a Data Collection Technique

9. Strategies for Choosing a Data Collection Technique

After figuring out what you are going to study, you, as the researcher, will need to figure out how to study it. This lesson discusses popular ways a researcher can collect data as well as why a researcher would chose a particular data collection technique.

How Randomized Experiments Are Designed

10. How Randomized Experiments Are Designed

When reading research or when conducting your own, it is important to understand the basic concepts of randomized experimental design that are covered in this lesson.

Advantages & Disadvantages of Various Experimental Designs

11. Advantages & Disadvantages of Various Experimental Designs

There are many different options for researchers when deciding how to run a study. In this lesson, we'll look at some of the advantages and disadvantages of some common experimental designs.

Drawing Logical Conclusions from Experimental Data

12. Drawing Logical Conclusions from Experimental Data

Experimental results are what scientists like to share with each other, but it's important to understand what those data mean. We do this in the final step of the experimental process, when we draw meaningful conclusions from the results we obtained.

Estimating a Parameter from Sample Data: Process & Examples

13. Estimating a Parameter from Sample Data: Process & Examples

One of the most useful things we can do with data is use it to describe a population. Learn how in this lesson as we discuss the concepts of parameters and samples.

Sample Proportion in Statistics: Definition & Formula

14. Sample Proportion in Statistics: Definition & Formula

This lesson talks about the definition, formula, and use of the sample proportion. We also see a brief intro into the concept of margin of error and selection of sample size. After completing the lesson, take a short quiz to see what you have learned.

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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