Human vs. Machine: Unveiling Randomness with Data Visualization and Stats
Students will learn about the concept of randomness and see how human decision-making contrasts with computer-generated choices.
Jul 15
Is screen time beneficial or harmful? In this lesson, students will learn how to collect data on the hours they spend on their smartphones and represent it visually. They will also explore a correlation analysis between the two quantitative variables of hours of screen time and number of notifications.
Nov 13
This lesson allows students to explore whether intrinsic (self-motivation) or extrinsic (physical) rewards are a better motivator for best results on a creativity assessment. Student-generated data will be created through different classes completing a task of trying to write the most English words they can out of the phrase “Statistics is fun.”
Mar 23
In this lesson, students will practice data collection through simulation, performing estimation, and providing support for or against a claim.
Mar 23
In this lesson, students will draw simple random samples; calculate sample proportions; construct histograms; and compare sampling distributions' shape, mean, and variability.
Mar 23
Beth Chance, Elsa Medina, and Jacquelyn Silverbush share a series of activities used with students in grades 4–6 to introduce statistical inference. The article is structured based on the amount of time to devote to the topic.
Mar 23
This investigation focuses on students conducting a comparative experiment to explore whether there are meaningful differences between the number of times people can write their name with their dominant hand and the number of times people can write their name with their non-dominant hand.
Oct 24
After drawing simple random samples, students will calculate sample proportions; construct dotplots; and identify a population, parameter, sample, and statistic.
Mar 23
In this lesson, students build their own sampling distribution of sample proportions from the data-collection process and use the information to answer the question of whether the manufacturer’s claim is supported or not by the evidence collected.
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