EngageNY
Distributions—Center, Shape, and Spread
Data starts to tell a story when it takes shape. Learners describe skewed and symmetric data. They then use the graphs to estimate mean and standard deviation.
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
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...
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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
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
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
Solving Inequalities
Do properties of equations hold true for inequalities? Teach solving inequalities through the theme of properties. Your class discovers that the multiplication property of equality doesn't hold true for inequalities when multiplying by a...
EngageNY
Solving Logarithmic Equations
Of course you're going to be solving an equation—it's algebra class after all. The 14th installment of a 35-part module first has pupils converting logarithmic equations into equivalent exponential equations. The conversion allows for...
EngageNY
Rational and Irrational Numbers
Back to the basics: learning how to add numbers. The 17th installment of a 35-part module first reviews addition techniques for rational numbers, such as graphical methods (number line) and numerical methods (standard algorithm). It goes...
EngageNY
Geometric Sequences and Exponential Growth and Decay
Connect geometric sequences to exponential functions. The 26th installment of a 35-part module has scholars model situations using geometric sequences. Writing recursive and explicit formulas allow scholars to solve problems in context.
EngageNY
Trigonometry and Complex Numbers
Complex numbers were first represented on the complex plane, now they are being represented using sine and cosine. Introduce the class to the polar form of a complex number with the 13th part of a 32-part series that defines the...
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Exploiting the Connection to Trigonometry 2
The class checks to see if the formula for finding powers of a complex number works to find the roots too. Pupils review the previous day's work and graph on the polar grid. The discussion leads the class to think about...
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Counting Rules—The Fundamental Counting Principle and Permutations
Count the benefits of using the resource. The second installment of a 21-part module focuses on the fundamental counting principle to determine the number of outcomes in a sample space. It formalizes concepts of permutations and...
EngageNY
Using Permutations and Combinations to Compute Probabilities
Now that we know about permutations and combinations, we can finally solve probability problems. The fourth installment of a 21-part module has future mathematicians analyzing word problems to determine whether permutations or...
EngageNY
Using Matrix Operations for Encryption
Data encryption is an important security measure for sensitive data stored on computers. Pupils learn how to utilize matrices for creating code. They also get a great review of matrix multiplication, inverse matrices, and the identity...
EngageNY
The Graph of a Function
Mathematics set notation can be represented through a computer program loop. Making the connection to a computer program loop helps pupils see the process that set notation describes. The activity allows for different types domain and...
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The General Multiplication Rule
In the first installment of a 21-part module, scholars build on previous understandings of probability to develop the multiplication rule for independent and dependent events. They use the rule to solve contextual problems.
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Discrete Random Variables
You don't need to be discreet about using the resource on discrete variables. In the fifth installment of a 21-part module, scholars explore random variables and learn to distinguish between discrete and continuous random variables. They...
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Probability Distribution of a Discrete Random Variable
Learn how to analyze probability distributions. The sixth installment of a 21-part module teaches pupils to use probability distributions to determine the long-run behavior of a discrete random variable. They create graphs of probability...
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Expected Value of a Discrete Random Variable
Discover how to calculate the expected value of a random variable. In the seventh installment of a 21-part module, young mathematicians develop the formula for expected value. They connect this concept the dot product of vectors.
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Interpreting Expected Value
Investigate expected value as a long-run average. The eighth installment of a 21-part module has scholars rolling pairs of dice to determine the average sum. They find aggregate data by working in groups and interpret expected value as...
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Determining Discrete Probability Distributions 1
Learn how to determine a probability distribution. In the ninth installment of a 21-part module, future mathematicians use theoretical probabilities to develop probability distributions for a random variable. They then use these...
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Estimating Probability Distributions Empirically 1
What if you don't have theoretical probabilities with which to create probability distributions? The 11th installment of a 21-part module has scholars collecting data through a survey. The results of the survey provide empirical data to...