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Chapter 7 continues with probability calculations, but this time for multiple discrete outcomes. How does this differ from Chapter 6? What is the difference between Random Discrete and Binomial variables? Come check out my simple lessons and full step-by-step solutions.
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Chapter 8 shows us how to handle the probabilities associated with individual outcomes when the measured variable is continuous in scale. Understanding these techniques will be crucial since they are used repeatedly for the remainder of the course.
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This is a fairly easy chapter. If you understand how to solve problems in Chapter 8, then Chapter 9 is just a simple extension of the same techniques. Don’t get too comfortable though – The “Central Limit Theorem” introduced here is an important bit of theory that will be tested on in the multiple choice. Also, the calculations and table references you learn here will will play a big role in Chapters 10, 11, and 12.
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With this chapter, we finally move on from simply describing our observations, and start making inferences about the population. Using only two sample statistics (the sample mean and size) and one population parameter (the population standard deviation), we can now estimate the unknown population mean.
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Chapter 11 is the foundation for all of the remaining chapters in the course. The steps you learn in the first hypothesis test presented here will be repeated (with some variation) many times throughout Chapters 12 to 16. Also contained here is a lot of theory that will be focused on heavily during the exam. A solid understanding of this chapter is a must!
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Get full access to all of my Midterm #2 prep materials: Full Chapter Lessons, Solved Past Exams, Tons of MCQ… plus Your Questions Answered Online! Up-to-date for the Winter 2020 semester.
