Category MGMT 1050

• Chapter 12: Inference About a Population...

by Jason 7 Lessons

24 learners taking this course

This chapter provides us with the methods to make inferences about a single population with an unknown parameter – Either the population mean when (unlike Chapter 11) σ is not given, the population variance, or the population proportion (for nominal data). As well – two new statistics ( t and χ²) are introduced including descriptions of their distributions, required conditions, formulas, and standard tables.

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• Chapter 7: Random Variables and Discrete Probability Distributions...

by Jason 20 Lessons

34 learners taking this course

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 1: What is Statistics?

by Jason 6 Lessons

39 learners taking this course

This chapter is short and simple. Several basic concepts are introduced here – each one plays a key role role throughout the course.

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• Chapter 5: Sampling Methods

by Jason 6 Lessons

38 learners taking this course

You’ll need data to apply all of the procedures that you learn in statistics. Making sure that the data properly represents the population you’re targeting is key – Learn about the factors that go into making this happen.

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• Chapter 13: Inference about Comparing Two Populations...

by Jason 8 Lessons

24 learners taking this course

This chapter is HUGE. To compare two populations, we learn six new tests, four new formulas for degrees of freedom, five new confidence interval estimators, and a new statistic – the F statistic. The questions are long, complex, and very frequently on the exam!

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• Chapter 2: Graphical Descriptive Techniques I

by Jason 6 Lessons

35 learners taking this course

Want to know what’s fun and easy? Graphing nominal data! What’s nominal data? Don’t worry – I’ll explain all that in the video. Also, I may have exaggerated the ‘fun’ part a bit.

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• Chapter 14: Analysis of Variance...

by Jason 4 Lessons

24 learners taking this course

ANOVA is used when comparing two or more groups of interval data – however – the t-tests from Chapter 13 did a good job of comparing two groups, so ANOVA is mainly just used to compare 3+ groups. The concepts in this Chapter are simple, but the mathematics are long.

• Chapter 8: Continuous Probability Distributions...

by Jason 8 Lessons

34 learners taking this course

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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• Chapter 3: Graphing Interval Data

by Jason 7 Lessons

33 learners taking this course

Ok, so the bar charts in Chapter 2 were lots of fun after all, but you’re really not going to like what happens in Chapter 3… We switch to studying ‘interval’ data, bar charts become histograms, and suddenly we’re doing lots of math. Uggh.

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• Chapter 16: Simple Linear Regression and Correlation...

by Jason 11 Lessons

24 learners taking this course

This will be the single most important chapter on the final exam. In this set of lessons I teach the entire chapter from scratch using a past exam question to guide you through all of the theory and calculations.

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