EngageNY
Normal Distributions (part 2)
From z-scores to probability. Learners put together the concepts from the previous lessons to determine the probability of a given range of outcomes. They make predictions and interpret them in the context of the problem.
EngageNY
Sampling Variability in the Sample Proportion (part 1)
Increase your sample and increase your accuracy! Scholars complete an activity that compares sample size to variability in results. Learners realize that the greater the sample size, the smaller the range in the distribution of sample...
EngageNY
Sampling Variability in the Sample Proportion (part 2)
Increase your sample and increase your accuracy! Scholars complete an activity that compares sample size to variability in results. Learners realize that the greater the sample size, the smaller the range in the distribution of sample...
EngageNY
Margin of Error When Estimating a Population Proportion (part 1)
Use the power of mathematics to find the number of red chips in a bag — it's a little like magic! The activity asks learners to collect data to determine the percentage of red chips in a bag. They calculate the margin of error and...
EngageNY
Margin of Error When Estimating a Population Proportion (part 2)
Error does not mean something went wrong! Learners complete a problem from beginning to end using concepts developed throughout the last five lessons. They begin with a set of data, determine a population proportion, analyze their result...
EngageNY
Margin of Error When Estimating a Population Mean (part 2)
Don't leave your classes vulnerable in their calculations! Help them understand the importance of calculating a margin of error to represent the variability in their sample mean.
EngageNY
Evaluating Reports Based on Data from a Sample
Statistics can be manipulated to say what you want them to say. Teach your classes to be wise consumers and sort through the bias in those reports. Young statisticians study different statistical reports and analyze them for...
EngageNY
Experiments and the Role of Random Assignment
Time to experiment with mathematics! Learners study experimental design and how randomization applies. They emphasize the difference between random selection and random assignment and how both are important to the validation of the...
EngageNY
Sampling Variability in the Sample Mean (part 2)
Reduce variability for more accurate statistics. Through simulation, learners examine sample data and calculate a sample mean. They understand that increasing the number of samples creates results that are more representative of the...
EngageNY
Margin of Error When Estimating a Population Mean (part 1)
We know that sample data varies — it's time to quantify that variability! After calculating a sample mean, pupils calculate the margin of error. They repeat the process with a greater number of sample means and compare the results.
EngageNY
Differences Due to Random Assignment Alone
It takes a lot of planning to achieve a random result! Learners compare results of random assignment, and conclude that random assignment allows results to be attributed to chance. They also realize the set of random means...
EngageNY
Ruling Out Chance (part 1)
What are the chances? Teach your classes to answer this question using mathematics. The first part of a three-day lesson on determining significance differences in experimental data prompts learners to analyze the data by...
EngageNY
Ruling Out Chance (part 2)
Help your classes find the significance in this instructional activity! Learners analyze the probability of Diff values. They then determine if the difference is significant based on their probability of occurrence.
EngageNY
Ruling Out Chance (part 3)
Pupils analyze group data to identify significant differences. They use simulation to create their own random assignment data for comparison.
EngageNY
Drawing a Conclusion from an Experiment (part 1)
Challenge your classes to complete an experiment from beginning to end. Learners make their own hypotheses, collect and analyze their own data, and make their own conclusions. They are on their way to becoming statisticians!
EngageNY
Drawing a Conclusion from an Experiment (part 2)
Communicating results is just as important as getting results! Learners create a poster to highlight their findings in the experiment conducted in the previous lesson in a 30-part series. The resource provides specific criteria and...
EngageNY
Solve for Unknown Angles—Angles and Lines at a Point
How do you solve for an unknown angle? In this sixth installment of a 36-part series, young mathematicians use concepts learned in middle school geometry to set up and solve linear equations to find angle measures.
EngageNY
Rational Exponents—What are 2^1/2 and 2^1/3?
Are you rooting for your high schoolers to learn about rational exponents? In the third installment of a 35-part module, pupils first learn the meaning of 2^(1/n) by estimating values on the graph of y = 2^x and by using algebraic...
EngageNY
Properties of Exponents and Radicals
(vegetable)^(1/2) = root vegetable? The fourth installment of a 35-part module has scholars extend properties of exponents to rational exponents to solve problems. Individuals use these properties to rewrite radical expressions in...
EngageNY
Euler’s Number, e
Scholars model the height of water in a container with an exponential function and apply average rates of change to this function. The main attraction of the lesson plan is the discovery of Euler's number.
EngageNY
Bacteria and Exponential Growth
It's scary how fast bacteria can grow — exponentially. Class members solve exponential equations, including those modeling bacteria and population growth. Lesson emphasizes numerical approaches rather than graphical or algebraic.
EngageNY
The “WhatPower” Function
The Function That Shall Not Be Named? The eighth installment of a 35-part module uses a WhatPower function to introduce scholars to the concept of a logarithmic function without actually naming the function. Once pupils are...
EngageNY
Logarithms—How Many Digits Do You Need?
Forget your ID number? Your pupils learn to use logarithms to determine the number of digits or characters necessary to create individual ID numbers for all members of a group.
EngageNY
Piecewise Functions
Show your class members that if they can graph a linear function, they can graph an absolute value function. Groups create an absolute value graph using a table, then entertain the idea of an absolute value function defined as two...
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