- Congratulations, you made it.…You survived sampling and sample size.…You created confidence intervals,…and you performed some very basic hypothesis tests.…If you weren't already surprised, interested,…or perhaps skeptical of the statistics…that you encounter at work and in the media already,…you're probably now hypersensitive…to any statistics put in front of you.…You might even ask probing questions about sampling methods.…Perhaps you get excited when you see poll results listed…with their margins of error.…
And you're probably also keenly aware…when people misuse statistics,…or when they present data that is very likely unreliable.…Statistics Fundamentals Part 1 provided a really nice…foundation that allowed you to interpret data sets…and calculate basic probabilities.…And now Statistics Fundamentals Part 2 has given you…the ability to collect reliable data,…to establish confidence intervals, and to test hypotheses.…Again, congratulations…
Eddie Davila first provides a bridge from Part 1, reviewing introductory concepts such as data and probability, and then moves into the topics of sampling, random samples, sample sizes, sampling error and trustworthiness, the central unit theorem, t-distribution, confidence intervals (including explaining unexpected outcomes), and hypothesis testing. This course is a must for those working in data science, business, and business analytics—or anyone else who wants to go beyond means and medians and gain a deeper understanding of how statistics work in the real world.
- List the three primary issues addressed in Statistics Foundations: 2.
- Recognize two key characteristics associated with simple random samples.
- Apply the Central Limit Theorem to find the average of sample means.
- Analyze random samples during hypothesis testing.
- Assess individual situations to determine whether a one-tailed or two-tailed test is necessary.
- Define acceptance sampling.