About This Chapter
Introduction to Business Statistics - Chapter Summary
There are many ways businesses use statistical analysis when making decisions. The lessons in this chapter provide an overview of these uses and introduce key statistics fundamentals. They explain how statistics are applied in business and detail some different types of statistical variables. These lessons quickly cover important concepts in an easy-to-follow way. They also include interactive quizzes to help you make sure you understood key points. The lessons can be accessed 24/7 on a computer, tablet or smartphone. Once you have completed this chapter, you should be able to:
- Differentiate between descriptive and inferential statistics
- Explain the purpose of statistical models
- Define bivariate data
- Compare and contrast qualitative and quantitative variables in statistics
- List types of random variables
- Share examples of bias and misleading uses of statistics
- Discuss differences between nominal, ordinal, interval and ratio measurements
- Describe the role of computer software in statistical analysis
- Outline ways to use formulas and functions in Excel
1. Application of Statistics in Business
Statistics is used every day in business. This lesson describes some of the more popular applications to business statistics and provides real life examples of how it is used. Key vocabulary and terminology will also be discussed.
2. Qualitative & Quantitative Variables in Statistics
Variables are assigned as a form of statistical measurement. The value of that measurement can take the form of anything from descriptions to numbers. In this lesson, we will discuss the difference between qualitative and quantitative variables.
3. Descriptive & Inferential Statistics: Definition, Differences & Examples
Descriptive and inferential statistics each give different insights into the nature of the data gathered. One alone cannot give the whole picture. Together, they provide a powerful tool for both description and prediction.
4. The Purpose of Statistical Models
Understanding statistics requires that you understand statistical models. This lesson will help you understand the purpose of statistics, statistical models, and types of variables.
5. 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.
6. Nominal, Ordinal, Interval & Ratio Measurements: Definition & Examples
Different types of data can be grouped and measured in different ways. In this lesson, you will learn about nominal, ordinal, interval, and ratio measurements.
7. Random Variables: Definition, Types & Examples
This lesson defines the term random variables in the context of probability. You'll learn about certain properties of random variables and the different types of random variables.
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.
9. Misleading Uses of Statistics
It can be too easy to present statistics in a way that is misleading. This lesson will cover the ways in which a statistic can be misleading and how to avoid and identify misleading statistics.
10. Computer Software in Statistical Analysis: Role & Examples
Making sense out of piles of research data can be a daunting prospect. This lesson looks at the computer software available to conduct analyses of research results.
11. How to Use Formulas & Functions in Excel
When you need Excel to do the math for you and run the calculations for totals and subtotals, formulas are your go-to feature. This lesson will introduce you to formulas, how they work and the different elements that make up a formula in Excel.
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Other chapters within the Business 212: Business Statistics course
- Introduction to Categorical Data
- Descriptive Statistics: Measurement
- Descriptive Statistics: Representation
- Measures of Dispersion in Business
- Measures of Association & Correlation in Business
- Probability for Business Statistics
- Probability Distributions for Business Statistics
- Sampling Methods for Statistics
- Confidence Intervals
- Hypothesis Testing in Business
- Analysis of Variance
- Nonparametric Methods in Statistics
- Regression Analysis
- Understanding Business Forecasting
- Using Control Charts in Business