Controlling Type 1 error and encouraging reproducible research are important in clinical and translational research. These concepts are frequently discussed in lectures with mathematical language, analytic examples, and probability distributions that demonstrate the issues. However, first-time learners in biostatistics courses focusing on…

Binary logistic regression is one of the most widely used statistical tools. The method uses odds, log odds, and odds ratios, which are difficult to understand and interpret. Understanding of logistic regression tends to fall down in one of three ways: (1) Many students and researchers come to believe that an odds ratio translates directly into…

Thinking probabilistically is an essential part of thinking statistically, and the probability learning objectives that this article focuses on are those that are important in the underpinning of statistics and statistical models. Like mathematical statistics, probability can be considered purely from a mathematical viewpoint, but the focus here…

Some situations are presented with perplexing properties, which become clearer by looking at contingency tables. This in turn leads to problems that can be solved using conditional frequencies and thus leading to the Bayes formula with natural frequencies or probabilities.

Providing opportunities for students to express ideas in their own words is key to promoting authentic disciplinary engagement and robust conceptual understanding. In this article, we discuss our experiences and observations related to students' informal vocabulary in the context of a middle school probability unit. We noticed that students'…

Pearson's product-moment correlation can be explained by means of the probability of concordant pairs of observations on two continuous variables (ie, the order of the observations from two randomly selected individuals is the same between the two variables). The probability of concordant pairs features relatively easy computation and offers an…

The topic of Bayesian updating is explored using standard and non-standard dice as an intuitive and motivating model. Details of calculating posterior probabilities for a discrete distribution are provided, offering a different view to P-values. This article also includes the stars and bars counting technique, a powerful method of counting that is…

The "Borel" board game consists of a series of experiments involving dice rolls, coin flips, or drawing colored balls from bags. Before each experiment is conducted, each player bets for or bets against a statement regarding the random outcome. We suggest that the collection of "Borel" experiments be used as a resource to…

A formula is derived for a 'two-dice horse race', in which two ordinary dice are thrown repeatedly and each time the sum of the scores determines which horse (numbered 2 to 12) moves forward one space. This paper answers a question posed in a former "Teaching Statistics" article, and demonstrates the value of simulation.

There is much debate about the place of probability in an introductory statistics course. While students may or may not use probability distributions in their post-collegiate lives, they will likely be faced with day-to-day decisions that require a probabilistic assessment of risk and reward. This paper describes an innovative way to teach…

We describe how we used puppets as tools to draw 9 to 10-year-old students into conversations about probability. Puppets supported classroom discourse by putting forth probabilistic arguments for critique, introducing extreme and unusual examples of concepts, and introducing an element of surprise.

Students are typically introduced to probability through calculating simple events like flipping a coin. While these calculations can be done by hand, more complex probabilistic events, both in class and in the real world, require the use of computers. In this paper, we introduce a new tool--an R shiny web app and associated CRAN package based on…

Stochastic independence is not an easy notion. Because it is part of the probability structure, it can have some surprising non-properties, which is beneficial for teachers and students to see illustrated. Neither is the relationship to causal independence an easy one.

The transition from the probability mass function for discrete random variables to the probability density function for continuous random variables is not straightforward, especially to students from the health and social sciences. An R Shiny application was created to assist the learning process of probability density function.

Probability and chance are essential concepts, not just in statistics but in real life. We present an adaptable activity which investigates what we mean by bias, how we can identify bias, and how we can use it to our advantage!