About This Chapter
Statistics for Interpreting Data - Chapter Summary
Within this chapter you can review various statistics and formulas used for interpreting data. The lessons cover topics like the probability of dependent and independent events as well as using quality tools and the differences between mean, median and mode. By the end of this chapter, you should be able to:
- Analyze the used for different measures of central tendency
- Explain how to calculate confidence intervals, levels and coefficients
- Describe the probability of independent and dependent events
- Understand tools for interpreting data, like process flowcharts and a Pareto analysis
If you are stuck on a concept, use the timeline tags within the videos to review a concept, or use the Dashboard to seek help from one of our experienced instructors. Make sure to take the self-assessment quiz at the end of each lesson to make sure you grasp each concept.
1. 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.
2. Calculating Confidence Intervals, Levels & Coefficients
In this lesson, you're going to learn about confidence intervals, confidence levels, and coefficients, and how they relate to point estimates and interval estimates.
3. 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.
4. Quality Tools: Process Flowcharts, Pareto Analysis & More
Companies need tools to evaluate quality throughout their business processes. In this lesson, you will learn about the seven quality tools and how they help support operations management goals.
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