High level detailed steps including null hypothesis, alternative hypothesis, significance level, statistics, probability value and statistical significance.
This resources offers a brief, one paragraph description of mutually exclusive events and gives an example for further clarification.
This lesson looks at a hypothesis test for one mean in a problem about Instagram use among teenagers. Includes downloadable study guide with exercises - guide also covers other topics. [5:00]
This lesson looks at a hypothesis test for one proportion in a problem about Snapchat use among teenagers. Includes downloadable study guide with exercises - guide also covers other topics. [11:34]
This lesson demonstrates how to test a hypothesis about whether there is a significant difference in Instagram followers based on gender. Includes downloadable study guide with exercises - guide also covers other topics. [6:00]
This model-eliciting activity (MEA) challenges students to develop a model for predicting the characteristics of a person who has committed a crime. Students work with real data on shoe length, height, and gender to develop the model. Students write a report to the crime victim that identifies a suspect and justifies their decision. The activity sets the stage for students to learn about regression models, and reinforces their understanding of central tendency and variability. It is suggested that this activity be used prior to a formal introduction to linear relationships.
An interactive game for learning theoretical vs experimental probability.
This lesson explains how to interpret the slope and the y-intercept for a scatter plot. Includes downloadable study guide with exercises - guide also covers other topics. [7:39]
By Joan Garfield, Robert delMas and Andrew Zieffler, University of Minnesota What are Model-Eliciting Activities? Model-Eliciting Activities (MEAs) are activities that encourage students to invent and test models. ...
Spreadsheets Across the Curriculum module. Students use the Compound Interest Equation and an annuity equation to calculate the growth of investments over time.
This model-eliciting activity (MEA) challenges students to develop ideas about center and variability when making decisions based on data. Students examine data on departure delays for five airlines flying out of the Chicago O'Hare airport. The task is to develop a model to determine which airline has the best chance of departing on time. Students write a report that identifies the best airline and the reasoning behind their decision.
This model-eliciting activity has students create rules to allow them to judge whether or not the shuffle feature on a particular iPod appears to produce randomly generated playlists. Because people's intuitions about random events and randomly generated data are often incorrect or misleading, this activity initially focuses students' attention on describing characteristics of 25 playlists that were randomly generated. Students then use these characteristics to come up with rules for judging whether a playlist does NOT appear to be randomly generated. Students test and revise their rules (model) using five additional playlsits. Then, they apply their model to three particular playlists that have been submitted to Apple by an unhappy iPod owner who claims the shuffle feature on his iPod is not generating random playlists. In the final part of the activity, students write a letter to the ipod owner, on behalf of Apple, explaining the use of their model and their final conclusion about whether these three suspicious playlists appear to have been randomly generated.This lesson provides an introduction to the fundamental ideas of randomness, random sequences and random samples.
This model-eliciting activity has students determine how to create a fair judging scheme for a paper airplane contest while considering both the most accurate paper airplane and the best floater. Students are given a sample of data that includes multiple flights of paper airplanes by three different pilots. Each team writes a report describing how their judging scheme can be implemented by the judges of the contest. This activity could serve as an introduction to ideas of central tendency and variability. It can also set the stage for understanding the correspondence between data sets and their graphical representations. Alternatively, the activity could be the basis for student introduction to analysis of variance.
This lesson looks at how to use the line of best fit to make predictions about bivariate data. Includes downloadable study guide with exercises - guide also covers other topics. [8:21]
A compilation of resources devoted to teaching probability and statistics. The resources are broken into seventeen different objectives that have a problem, activity, and a game.
Distributions and Variability
Type of Unit: Project
Prior Knowledge
Students should be able to:
Represent and interpret data using a line plot.
Understand other visual representations of data.
Lesson Flow
Students begin the unit by discussing what constitutes a statistical question. In order to answer statistical questions, data must be gathered in a consistent and accurate manner and then analyzed using appropriate tools.
Students learn different tools for analyzing data, including:
Measures of center: mean (average), median, mode
Measures of spread: mean absolute deviation, lower and upper extremes, lower and upper quartile, interquartile range
Visual representations: line plot, box plot, histogram
These tools are compared and contrasted to better understand the benefits and limitations of each. Analyzing different data sets using these tools will develop an understanding for which ones are the most appropriate to interpret the given data.
To demonstrate their understanding of the concepts, students will work on a project for the duration of the unit. The project will involve identifying an appropriate statistical question, collecting data, analyzing data, and presenting the results. It will serve as the final assessment.
Getting Started
Type of Unit: Introduction
Prior Knowledge
Students should be able to:
Solve and write numerical equations for whole number addition, subtraction, multiplication, and division problems.
Use parentheses to evaluate numerical expressions.
Identify and use the properties of operations.
Lesson Flow
In this unit, students are introduced to the rituals and routines that build a successful classroom math community and they are introduced to the basic features of the digital course that they will use throughout the year.
An introductory card sort activity matches students with their partner for the week. Then over the course of the week, students learn about the lesson routines: Opening, Work Time, Ways of Thinking, Apply the Learning, Summary of the Math, and Reflection. Students learn how to present their work to the class, the importance of taking responsibility for their own learning, and how to effectively participate in the classroom math community.
Students then work on Gallery problems to further explore the program’s technology resources and tools and learn how to organize their work.
The mathematical work of the unit focuses on numerical expressions, including card sort activities in which students identify equivalent expressions and match an expression card to a word card that describes its meaning. Students use the properties of operations to identify equivalent expressions and to find unknown values in equations.
Decide which charts and graphs represent the number of goals two football teams scored in fifteen matches. This data handling activity is designed to get children talking meaningfully about mathematics, presenting and justifying arguments, and is aimed at primary school pupils at Key Stage 2.
What events are there in your school sports day, and in the Olympic Games? What are your favourite races and sports? This activity encourages discussion and decisions about how to collect and display data, and is designed to be accessible to primary pupils at Key Stage 2.
This is a great starting point for anyone doing research or a report on asthma. Organized into several sections -- including "Signs and Symptoms," "Screening and Diagnosis," and "Treatment."