In a calculus-based introductory statistics course, there is generally a lesson on some of the
named discrete distributions. This lesson often addresses the following distributions: Discrete
Uniform, Poisson, Binomial, Hypergeometric and Negative Binomial. Generally, all of these
distributions, except the Poisson, have already been utilized in a probability unit in the course
without the students even realizing it. That is, they have calculated probabilities “from scratch”
using the ideas of combinations, permutations, conditional probability, etc. For example, a
student may be asked to find the probability when a fair coin is tossed five times, that exactly
two are heads. Although this example follows a Binomial Distribution, students learn how to
construct this probability prior to ever hearing its name. Thus, the calculations of these
probabilities are not new, but the names and specific properties are. We may believe that the
application of these distributions should not be troublesome if students have already had
exposure to the calculations. However, students often struggle in the probability unit
distinguishing between permutations and combinations as well as “with replacement” and
“without replacement.” From our experience, adding the names and properties to these
distributions simply confuses students more. So, one might ask why add them? Three of the
motivational factors for students to learn the specific named distributions are:
In a calculus-based introductory statistics course, there is generally a lesson on some of thenamed discrete distributions. This lesson often addresses the following distributions: DiscreteUniform, Poisson, Binomial, Hypergeometric and Negative Binomial. Generally, all of thesedistributions, except the Poisson, have already been utilized in a probability unit in the coursewithout the students even realizing it. That is, they have calculated probabilities “from scratch”using the ideas of combinations, permutations, conditional probability, etc. For example, astudent may be asked to find the probability when a fair coin is tossed five times, that exactlytwo are heads. Although this example follows a Binomial Distribution, students learn how toconstruct this probability prior to ever hearing its name. Thus, the calculations of theseprobabilities are not new, but the names and specific properties are. We may believe that theapplication of these distributions should not be troublesome if students have already hadexposure to the calculations. However, students often struggle in the probability unitdistinguishing between permutations and combinations as well as “with replacement” and“without replacement.” From our experience, adding the names and properties to thesedistributions simply confuses students more. So, one might ask why add them? Three of themotivational factors for students to learn the specific named distributions are:
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