Hi, what do you want to do?
EngageNY
Understanding Box Plots
Scholars apply the concepts of box plots and dot plots to summarize and describe data distributions. They use the data displays to compare sets of data and determine numerical summaries.
EngageNY
Sampling Variability and the Effect of Sample Size
The 19th installment in a 25-part series builds upon the sampling from the previous unit and takes a larger sample. Pupils compare the dot plots of sample means using two different sample sizes to find which one has the better variability.
EngageNY
Connecting Graphical Representations and Numerical Summaries
Which graph belongs to which summary statistics? Class members build upon their knowledge of data displays and numerical summaries to connect the two. Pupils make connections between different graphical displays of the same data in...
EngageNY
Describing the Center of a Distribution Using the Median
Find the point that splits the data. The lesson presents to scholars the definition of the median through a teacher-led discussion. The pupils use data lists and dot plots to determine the median in sets with even and odd number of data...
EngageNY
The Mean as a Balance Point
It's a balancing act! Pupils balance pennies on a ruler to create a physical representation of a dot plot. The scholars then find the distances of the data points from the balance point, the mean.
EngageNY
Summarizing a Distribution Using a Box Plot
Place the data in a box. Pupils experiment with placing dividers within a data set and discover a need for a systematic method to group the data. The 14th lesson in a series of 22 outlines the procedure for making a box plot based...
EngageNY
Describing Variability Using the Interquartile Range (IQR)
The 13th lesson in a unit of 22 introduces the concept of the interquartile range (IQR). Class members learn to determine the interquartile range, interpret within the context of the data, and finish by finding the IQR using an...
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...
EngageNY
Describing Center, Variability, and Shape of a Data Distribution from a Graphical Representation
What is the typical length of a yellow perch? Pupils analyze a histogram of lengths for a sample of yellow perch from the Great Lakes. They determine which measures of center and variability are best to use based upon the shape of the...
EngageNY
The Mean Absolute Deviation (MAD)
Is there a way to measure variability? The ninth resource in a series of 22 introduces mean absolute deviation, a measure of variability. Pupils learn how to determine the measure based upon its name, then they use the mean...
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
More Practice with Box Plots
Don't just think outside of the box — read outside of it! The 15th lesson in a 22-part unit provides pupils more work with box plots. Learners read the box plots to estimate the five-number summary and interpret it within the context....
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...