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Posts from the ‘9-12+’ Category

Why 0.05? Two Examples That Put Students in the Role of Decision Maker

Any teacher of Introductory Statistics has heard this question more times than they can remember: “Why 0.05?” Here, the value 0.05 refers to the significance level in a hypothesis test. I provide a brief review of the concepts of hypothesis test and significance level. Then, I describe two activities for teachers to proactively address the question of why 0.05 with their students.

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Lesson Plan: You Will Soon Analyze Categorical Data (Classifying Fortune Cookie Fortunes)

(Grades 9-12+) Originally published in May 2014, students will have the opportunity to collect and explore real data using two brands of fortune cookies.

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Double Stuffed?

The question of whether Double Stuf Oreos actually have double the filling is an intriguing one. In this article, I describe an activity that uses that question as a hook to engage students in finding means, comparing distributions, and performing t-tests.

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Lesson Plan: What Fits?

(Grades 6-12+) Originally published in February 2013, this activity has students explore what a line of best fit is and where a line of best fit should be placed on a scatterplot of data with a linear association.

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Lesson Plan: Bubble Trouble!

(Grades 6-12+) Originally published in May 2014, this lesson has two goals: have students generate data and calculate descriptive statistics to describe the distribution of a sample drawn from a random process and compare trials from different experiments and use them to make some judgment about the underlying processes.

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Helping Community College Math Instructors Teach Statistics Effectively

We are reaching a crisis at community colleges across the country. The number of STEM majors (science, technology, engineering, and mathematics) has dramatically decreased, while the number of non-STEM majors continues to rise. At my college alone, only about 30% of our students are STEM majors.

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Lesson Plan: Confidence in Salaries in Petroleum Engineering

(Grades 9-12+) Originally published in October 2016, this lesson introduces students to bootstrapping methods for making inferences about a population parameter using a randomly selected sample from the population.

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