About This Chapter
Probability and Statistics for Business Math - Chapter Summary and Learning Objectives
The lessons in this chapter present you with a variety of formulas and measurements for determining probability. You'll learn terms related to statistical and probability measures and find out their relevance and uses in a business setting. In addition, you'll study different categories of events, such as dependent and independent, and see how calculating statistical probabilities among them differ. When you finish this chapter, you should be able to do the following:
- Determine various measures of central tendency
- Calculate standard deviation
- Establish probabilities for various types of events
- Discern statistical significance
- Know what a probability distribution is
- Understand the purpose of percentiles
|How to Calculate Mean, Median, Mode, and Range||Learn the definitions of and how to calculate these four measures of central tendency.|
|Standard Deviation and Shifts in the Mean||Know the five steps to finding the standard deviation for any data set.|
|Probability of Simple, Compound, and Complementary Events||Learn how distinguish among and determine the probability of each of these three event types.|
|Probability of Independent and Dependent Events||Understand how to differentiate between dependent and independent events. Know how to calculate probabilities for each.|
|Statistical Significance||Define and calculate statistical significance.|
|Expected Value||Learn to calculate expected value from a probability distribution table. Know how to discern residual error by comparing the expected value and the actual result.|
|Probability Distributions||Define quartile and probability distribution. Understand the characteristics of normal distribution.|
|Weighted Averages||Learn how to calculate a weighted average.|
|Percentiles||Understand the definition and use of a percentile.|
1. 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.
2. Calculating the Standard Deviation
In this lesson, we will examine the meaning and process of calculating the standard deviation of a data set. Standard deviation can help to determine if the data set is a normal distribution.
3. Probability of Simple, Compound and Complementary Events
Simple, compound, and complementary events are different types of probabilities. Each of these probabilities are calculated in a slightly different fashion. In this lesson, we will look at some real world examples of these different forms of probability.
4. Probability of Independent and Dependent Events
Sometimes probabilities need to be calculated when more than one event occurs. These types of compound events are called independent and dependent events. Through this lesson, we will look at some real-world examples of how to calculate these probabilities.
5. Statistical Significance: Definition & Calculation
Watch this video lesson to learn about statistical significance, and how it relates to surveys and other real world events. Also, learn how it is calculated, and how you can describe it to others.
6. Expected Value in Probability: Definition & Formula
After watching this video lesson, you will understand what expected value means. You will learn how to use this value to decide whether a certain action is worth taking or not.
7. Normal Distribution & Shifts in the Mean
In this video lesson, you will see what a normal distribution looks like and you will learn about the mean of a normal distribution. You will also see what happens when the mean is shifted.
8. Identifying & Calculating Averages
After watching this video lesson, you will be able to calculate any kind of average, even the average of certain events when some events repeat. Learn the general formula to use to calculate any average.
9. Finding Percentiles in a Data Set: Formula & Examples
Percentiles are often used in academics to compare student scores. Finding percentiles in a data set can be a useful way to organize and compare numbers in a data set.
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