Ch 16: MCAS ST&E Chemistry: Mathematics Principles in Chemistry

About This Chapter

The short lessons in this chapter can simplify the process of studying for the MCAS - Science and Technology/Engineering High School Chemistry test. Review mathematics principles in chemistry, then test your knowledge with short quizzes.

MCAS ST&E Chemistry: Mathematics Principles in Chemistry - Chapter Summary

This comprehensive overview of mathematics principles in chemistry can ensure you have the knowledge needed to answer related questions on the MCAS - Science and Technology/Engineering High School Chemistry test. After reviewing the lessons in this chapter, you will be prepared to:

  • Define data set in math, frequency distributions, scientific notation, ratios and proportions
  • Analyze bar graphs and pie charts, and create and interpret histograms
  • Describe how to express relationships as algebraic expressions and evaluate simple algebraic expressions
  • Explain the measures of central tendency and measures of variability
  • Differentiate between correlation and causation
  • Share the formula and significance of the Pearson correlation coefficient
  • Discuss the chi-square test

Our quality instructors have created entertaining videos that provide an in-depth look at the subject area, while additional experts are available to answer any questions you have about the lessons. Take self-assessment quizzes to gauge your readiness to tackle the subject area on the test. A chapter exam is also available to provide you with a broader review of the lessons.

13 Lessons in Chapter 16: MCAS ST&E Chemistry: Mathematics Principles in Chemistry
Test your knowledge with a 30-question chapter practice test
Data Set in Math: Definition & Examples

1. Data Set in Math: Definition & Examples

In this lesson, learn about data sets and how to use the operations of mean, median, and mode to manipulate the data. Then, test your knowledge with a brief quiz.

Understanding Bar Graphs and Pie Charts

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.

Creating & Interpreting Histograms: Process & Examples

3. Creating & Interpreting Histograms: Process & Examples

Creating histograms can help you easily identify and interpret data. This lesson will give you several examples to better understand histograms and how to create them.

Frequency Distributions: Definition & Types

4. Frequency Distributions: Definition & Types

This lesson explores the process of creating frequency distributions and histograms to give readers of your future scientific articles a numerical or visual way to understand the data you have presented.

Expressing Relationships as Algebraic Expressions

5. Expressing Relationships as Algebraic Expressions

What do you do when you don't know what a number is but you do know how it relates to something else? You use an algebraic expression. In this lesson, we'll learn how to express relationships as algebraic expressions.

Evaluating Simple Algebraic Expressions

6. Evaluating Simple Algebraic Expressions

In this lesson, we'll learn how to evaluate algebraic expressions, which involves substituting numbers for variables and following the order of operations. By the end of the lesson, you'll be an algebraic expression expert.

Mean, Median & Mode: Measures of Central Tendency

7. 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.

Measures of Variability: Range, Variance & Standard Deviation

8. Measures of Variability: Range, Variance & Standard Deviation

Looking specifically at range, variance, and standard deviation, this lesson explores the relationship between these measures and samples, populations, and what it says about your data.

Correlation vs. Causation: Differences & Definition

9. Correlation vs. Causation: Differences & Definition

When conducting experiments and analyzing data, many people often confuse the concepts of correlation and causation. In this lesson, you will learn the differences between the two and how to identify one over the other.

Pearson Correlation Coefficient: Formula, Example & Significance

10. Pearson Correlation Coefficient: Formula, Example & Significance

The Pearson correlation coefficient is just one of many types of coefficients in the field of statistics. The following lesson provides the formula, examples of when the coefficient is used, its significance, and a quiz to assess your knowledge of the topic.

The Chi-Square Test

11. The Chi-Square Test

What if you expect one thing, but get another? The chi-square test is a method of statistical analysis that can help us identify if the results from a genetic cross are simply due to chance, or if something else is happening. Learn about the chi-square test in this lesson.

Scientific Notation: Definition and Examples

12. Scientific Notation: Definition and Examples

Scientific notation is a special way of writing numbers so they are easier to work with. This lesson will define scientific notations and show some examples of how to convert numbers from standard notation to scientific notation and back.

Ratios and Proportions: Definition and Examples

13. Ratios and Proportions: Definition and Examples

Watch this video lesson to learn how ratios and proportions are related. Also, learn how ratios and proportions are used in real life and how you can apply them to yours.

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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