This learning video continues the theme of an early BLOSSOMS lesson, Flaws …
This learning video continues the theme of an early BLOSSOMS lesson, Flaws of Averages, using new example- including how all the children from Lake Wobegon can be above average, as well as the Friendship Paradox. The objective of this module, is to simply point out a few pitfalls that could arise if one is not attentive to details when calculating and interpreting averages. [22:41]
This website from the BBC is a great introduction to averages (mean, …
This website from the BBC is a great introduction to averages (mean, median, and mode) and will take you through some interactive learning activities. A practice test and worksheet are also provided.
Students drop water from different heights to demonstrate the conversion of water's …
Students drop water from different heights to demonstrate the conversion of water's potential energy to kinetic energy. They see how varying the height from which water is dropped affects the splash size. They follow good experiment protocol, take measurements, calculate averages and graph results. In seeing how falling water can be used to do work, they also learn how this energy transformation figures into the engineering design and construction of hydroelectric power plants, dams and reservoirs.
Students, teachers, and parents alike will enjoy this challenging math site. It …
Students, teachers, and parents alike will enjoy this challenging math site. It contains a clever brain teaser section plus creative problems related to algebra, geometry, measurement, numbers, statistics, and probability. A Spanish version is available.
Distributions and Variability Type of Unit: Project Prior Knowledge Students should be …
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.
In this interactive website students practice various skills including adding fractions with …
In this interactive website students practice various skills including adding fractions with common denominators, adding fractions with different denominators, adding decimals, finding equivalent fractions, and calculating averages.
In this episode of Math Club, we explain the concept of the …
In this episode of Math Club, we explain the concept of the "mean" to help take the drama out of dating. What is mean? It's nothing more than an average, or the sum of a list of numbers divided by the size of the list. Mean: or as we call it, "life's highs and lows AVERAGED out."
The results of researches are heavily affected by the process of data …
The results of researches are heavily affected by the process of data collection. However, the process is prone to errors. For example, biased and misleading survey questions, and leading survey questions can all affect the results greatly. In this video, you will learn how to identify and fix these errors. [2:31]
The process of data collection for research can be prone to errors. …
The process of data collection for research can be prone to errors. For example, biased and misleading survey questions, and leading survey questions can all affect the results greatly. In this lesson, you will learn how to identify and fix these errors. [2:31]
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