I have a video on solving combination and permutations problems using StatCrunch, but here is the basic Excel solution for problem 3.4.51 in MyStatLab homework:
I may be a bit biased, but I believe our Excelsior quantitative courses are critical to our students. I found this article about an interview with Dr. Rebecca Goldin, Director of STATS and professor at George Mason University, about the importance of quantitative literacy:
You argue that statistical literacy gives citizens a kind of power. What do you mean?
What I mean is that if we don’t have the ability to process quantitative information, we can often make decisions that are more based on our beliefs and our fears than based on reality. On an individual level, if we have the ability to think quantitatively, we can make better decisions about our own health, about our own choices with regard to risk, about our own lifestyles. It’s very empowering to not be scared or bullied into doing things one way or another.
On a collective level, the impact of being educated in general is huge. Think about what democracy would be if most of us couldn’t read. We aspire to a literate society because it allows for public engagement, and I think this is also true for quantitative literacy. The more we can get people to understand how to view the world in a quantitative way, the more successful we can be at getting past biases and beliefs and prejudices. (Bleicher, 2017)
I have been making Excel-based “calculators” to help some of my students who are finding other technology limiting or difficult to use. Currently, I have seven up on this site under the BUS 233 tab. Check them out here. This is the Two-sample z-test for the difference between proportions.
Download a PDF with the step-by-step instructions for finding the confidence interval for a population mean, μ, using StatCrunch.
Excel calculator for problems involving the use of the Empirical Rule or Chebyshev’s Theorem:
One kind are “natural” pairings, such as spouses, siblings, and especially twins. This type of pairing is often used in medical observational research when it is difficult to construct a true experiment. (PennState, 2017)
But even more common are other types of pairing. A more accurate label for this two-sample test is a test for dependent samples. Samples are dependent when there is a relationship of some kind in play which causes the samples to not be independent.
I like this definition from the Minitab blog:
If the values in one sample affect the values in the other sample, then the samples are dependent. [Read more…] about Paired samples are not always obvious