EngageNY
Graphing the Tangent Function
Help learners discover the unique characteristics of the tangent function. Working in teams, pupils create tables of values for different intervals of the tangent function. Through teamwork, they discover the periodicity, frequency, and...
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What Is a Trigonometric Identity?
Protect yourself from identity theft! Establishing a strong understanding of the Pythagorean identity allows learners to prove that sine^2x + cos^2x = 1. They then use the identity to find sine or cosine ratios given the other.
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Proving Trigonometric Identities
Young mathematicians first learn the basics of proving trigonometric identities. They then practice this skill on several examples.
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Trigonometric Identity Proofs
Proving a trig identity might just be easier than proving your own identity at the airport. Learners first investigate a table of values to determine and prove the addition formulas for sine and cosine. They then use this result to...
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Chance Experiments, Sample Spaces, and Events
Want a leg up on the competition? Show classes how to use mathematics to their advantage when playing games. Learners calculate probabilities to determine a reasonable scoring strategy for a game.
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Calculating Probabilities of Events Using Two-Way Tables
Tables are useful for more than just eating. Learners use tables to organize data and calculate probabilities and conditional probabilities.
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Calculating Conditional Probabilities and Evaluating Independence Using Two-Way Tables (part 1)
Being a statistician means never having to say you're certain! Learners develop two-way frequency tables and calculate conditional and independent probabilities. They understand probability as a method of making a prediction.
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Calculating Conditional Probabilities and Evaluating Independence Using Two-Way Tables (part 2)
Without data, all you are is another person with an opinion. Show learners the power of statistics and probability in making conclusions and predictions. Using two-way frequency tables, learners determine independence by analyzing...
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Probability Rules (part 2)
Ensure your pupils are rule followers! Learners add the addition rule to the set of probability rules examined in the previous lesson. Problems require both the multiplication and addition rule.
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Events and Venn Diagrams
Time for statistics and learning to overlap! Learners examine Venn Diagrams as a means to organize data. They then use the diagrams to calculate simple and compound probabilities.
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Probability Rules (part 1)
In statistics, probability rules—literally! Learners use their previous knowledge and explore a set of rules for conditional probability, independent probability, and complements. Given different scenarios, they must determine what type...
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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.
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Types of Statistical Studies
All data is not created equal. Scholars examine the different types of studies and learn about the importance of randomization. They explore the meaning of causation and when it can be applied to data.
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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.
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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...
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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...
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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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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...
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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.
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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...
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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...
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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...
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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.
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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...
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