Curated OER
US Population 1982-1988
Your algebra learners make predictions using the concepts of a linear model from real-life data given in table form. Learners analyze and discuss solutions without having to write a linear equation.
Illustrative Mathematics
Complex number patterns
Start off with the definition of the imaginary number i, then have your class practice simplifying expressions involving powers of i and look for patterns. See how the cyclic nature of powers of i translate to sums of powers of i.
Curated OER
Triangles Inscribed in a Circle
Are you tired of answers without understanding? Learners can give a correct response, but do they really understand the concept? Have young mathematicians think deeper about linear functions, angles, and formulas in algebra. Learners are...
Illustrative Mathematics
Zeroes and Factorization of a General Polynomial
These four problems will guide your class through the idea behind the Fundamental Theorem of Algebra, which states that a polynomial of degree n has exactly n roots. Use the division algorithm and the definition of a zero/root of a...
Illustrative Mathematics
Delivering the Mail
A mail truck travels the same amount of miles per day. It will be up to your algebra learners to find an equation for this mailman’s truck. One needs a good understanding of rate of change and the initial value for this model. The...
Illustrative Mathematics
Comparing Rational and Irrational Number
Algebra learners must know how to use rational numbers to approximate irrationals. This resource asks participants to decide which number is larger without using a calculator. It makes a great exercise to use as a five-minute transition...
Illustrative Mathematics
Equations of Lines
The intent of this resource is to show algebra learners that there is a proportional relationship between two lines that have an intersecting point. As the coordinate x increases by a constant, the y coordinate also increases. It will...
EngageNY
Interpreting Residuals from a Line
What does an animal's gestation period have to do with its longevity? Use residuals to determine the prediction errors based upon a least-square regression line. This second lesson on residuals shows how to use residuals to create a...
EngageNY
Modeling from a Sequence
Building upon previous knowledge of sequences, collaborative pairs analyze sequences to determine the type and to make predictions of future terms. The exercises build through arithmetic and geometric sequences before introducing...
EngageNY
Analyzing a Graph
Collaborative groups utilize their knowledge of parent functions and transformations to determine the equations associated with graphs. The graph is then related to the scenario it represents.
EngageNY
Summarizing Deviations from the Mean
Through a series of problems, learners determine the variability of a data set by looking at the deviations from the mean. Estimating means of larger data sets presented in histograms and providing a way to calculate an estimate round...
EngageNY
Analyzing a Data Set
Through discussions and journaling, classmates determine methods to associate types of functions with data presented in a table. Small groups then work with examples and exercises to refine their methods and find functions that work to...
EngageNY
Distributions and Their Shapes
What can we find out about the data from the way it is shaped? Looking at displays that are familiar from previous grades, the class forms meaningful conjectures based upon the context of the data. The introductory lesson to descriptive...
EngageNY
Describing the Center of a Distribution
So the mean is not always the best center? By working through this exploratory activity, the class comes to realize that depending upon the shape of a distribution, different centers should be chosen. Learners continue to explore the...
EngageNY
Estimating Centers and Interpreting the Mean as a Balance Point
How do you balance a set of data? Using a ruler and some coins, learners determine whether the balance point is always in the middle. Through class and small group discussions, they find that the mean is the the best estimate of the...
EngageNY
Measuring Variability for Skewed Distributions (Interquartile Range)
Should the standard deviation be used for all distributions? Pupils know that the median is a better description of the center for skewed distributions; therefore, they will need a variability measure about the median for those...
EngageNY
Interpreting the Standard Deviation
Does standard deviation work for non-symmetrical distributions, and what does it mean? Through the use of examples, high schoolers determine the standard deviation of a variety of distributions and interpret its meaning. Problems require...
EngageNY
Measuring Variability for Symmetrical Distributions
How do we measure the deviation of data points from the mean? An enriching activity walks your class through the steps to calculate the standard deviation. Guiding questions connect the steps to the context, so the process is not about...
EngageNY
Analyzing Residuals (Part 1)
Just how far off is the least squares line? Using a graphing calculator, individuals or pairs create residual plots in order to determine how well a best fit line models data. Three examples walk through the calculator procedure of...
EngageNY
More on Modeling Relationships with a Line
How do you create a residual plot? Work as a class and in small groups through the activity in order to learn how to build a residual plot. The activity builds upon previous learning on calculating residuals and serves as a precursor to...
EngageNY
Relationships Between Two Numerical Variables
Is there another way to view whether the data is linear or not? Class members work alone and in pairs to create scatter plots in order to determine whether there is a linear pattern or not. The exit ticket provides a quick way to...
EngageNY
Modeling Relationships with a Line
What linear equation will fit this data, and how close is it? Through discussion and partner work, young mathematicians learn the procedure to determine a regression line in order to make predictions from the data.
EngageNY
Summarizing Bivariate Categorical Data with Relative Frequencies
It is hard to determine whether there is a relationship with the categorical data, because the numbers are so different. Working with a familiar two-way table on super powers, the class determines relative frequencies for each cell and...
EngageNY
Summarizing Bivariate Categorical Data
How do you summarize data that cannot be averaged? Using an exploratory method, learners complete a two-way frequency table on super powers. The subject matter builds upon 8th grade knowledge of two-way tables.
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