For two or more sets of numerical univariate data, calculate and compare the appropriate measures of center and measures of variability, accounting for possible effects of outliers. Interpret any notable features of the shape of the data distribution.
: The measure of center is limited to mean and median. The measure of variation is limited to range, interquartile range, and standard deviation.
| Name |
Description |
| A MEANingful Discussion about Central Tendency | Using relatable scenarios, this lesson explores the mean and median of a data set and how an outlier affects each measure differently. |
| Analyzing Box Plots | This lesson is designed for students to demonstrate their knowledge of box plots.
- Students will need to create four box plots from given data.
- Students will need to analyze the data displayed on the box plots by comparing similarities and differences.
- Students will work with a partner to complete the displays and the follow-up questions.
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| Texting and Standard Deviation | This lesson uses texting to teach statistics. In the lesson, students will calculate the mean, median, and standard deviation. They will create a normal distribution using the mean and standard deviation and estimate population percentages. They will construct and interpret dot plots based on the data they collected. Students will also use similarities and differences in shape, center, and spread to determine who is better at texting, boys, or girls. |
| Comparing Standard Deviation | Students will predict and compare standard deviation from a dot plot. Each data set is very different, with a small variation vs. a larger variation. The students are asked to interpret the standard deviation after calculating the range and mean of the each data set. |
| Close to the Crossbar with Standard Deviation | The lesson will connect student's prior knowledge of measures of central tendency to standard deviation and variance. Students will learn how to calculate and analyze variance and standard deviation. With a partner, students will collect data from kicking a ball into a goal mark. Students will collect data and find the mean, then calculate standard deviation and variance, and compare the data between boys and girls. They will analyze the data distribution in terms of how many students are within certain numbers of standard deviations from the mean. |
| Bowling for Box Plots | Students will learn about the effects of an outlier and interpret differences in shape, center, and spread using a bowling activity to gather data. The students will learn to score their games, report their scores, and collectively measure trends and spread by collaborating to create a box plot. They will analyze and compare box plots, and determine how much of an effect an extreme score (outlier) can have on the overall box plot of the data. |
| What's My Grade? | "What's My Grade" is a lesson that will focus on a sample student's grades to demonstrate how a final grade is calculated as well as explore possible future grades. Students will create the distributions of each grade category using histograms. They will also analyze grades using mean and standard deviation. Students will use statistics to determine data distribution while comparing the center and spread of two or more different data sets. |
| College Freshman Entrance Data | An introduction to classifying data as normally distributed, skewed left, or skewed right, Technology is used to calculate the mean, median, and standard deviation. Data listing ranking, acceptance rates, average GPA, SAT and ACT scores, and tuition rates from 36 Universities are used. |
| How tall is an 8th grader? | Ever wonder about the differences in heights between students in grade 8? In this lesson, students will use data they collect to create and analyze multiple box plots using 5-number summaries. Students will make inferences about how height and another category may or may not be related. |
| Plane Statistics | This lesson starts with an activity to gather data using paper airplanes then progresses to using appropriate statistics to compare the center and spread of the data. Box plots are used in this application lesson of concepts and skills previously acquired. |
| What's Your Tendency? | This resource can be used to teach students how to create and compare box plots. After completing this lesson, students should be able to answer questions in both familiar and unfamiliar situations. |
| The Distance a Coin Will Travel | This lesson is a hands-on activity that will allow students to collect and display data about how far different coins will travel. The data collected is then used to construct double dot plots and double box plots. This activity helps to facilitate the statistical implications of data collection and the application of central tendency and variability in data collection. |
| Which is Better? Using Data to Make Choices | Students use technology to analyze measures of center and variability in data. Data displays such as box plots, line plots, and histograms are used. The effects of outliers are taken into consideration when drawing conclusions. Students will cite evidence from the data to support their conclusions. |
| How many licks does it take to get to the center? | Students will create different displays, line plots, histograms, and box plots from data collected about types of lollipops. The data will be analyzed and compared. Students will determine "Which lollipop takes the fewest number of licks to get to the center: a Tootsie Pop, a Blow Pop, or a Dum Dum?" |
| Birthday Party Decisions | Students will create and compare four different boxplots to determine the best location for a birthday party. |
| Outliers in the Outfield – Dealing With Extreme Data Points | Students will explore the effects outliers have on the mean and median values using the Major League Baseball (MLB) salary statistics. They will create and compare box plots and analyze measures of center and variability. They will also be given a set of three box plots and asked to identify and compare their measures of center and variablity. |
| In terms of soccer: Nike or Adidas? | In this lesson, students calculate and interpret the standard deviation for two data sets. They will measure the air pressure for two types of soccer balls. This lesson can be used as a hands-on activity or completed without measuring using sample data. |
| Marshmallow Madness | This lesson allows students to have a hands-on experience collecting real-world data, creating graphical representations, and analyzing their data. Students will make predictions as to the outcome of the data and compare their predictions to the actual outcome. Students will create and analyze line plots, histograms, and box plots. |
| Comparing Data Using Box Plots | Students will use box plots to compare two or more sets of data. They will analyze data in context by comparing the box plots of two or more data sets. |
| Digging the Plots | Students construct box plots and use the measure(s) of center and variability to make comparisons, interpret results, and draw conclusions about two populations. |
| A Walk Down the Lane | Students will collect data, and create box plots. Students will make predictions about which measurement best describes the spread and center of the data. Students will use this information to make predictions. |
| How do we measure success? | Students will use the normal distribution to estimate population percentages and calculate the values that fall within one, two, and three standard deviations of the mean. Students use statistics and a normal distribution to determine how well a participant performed in a math competition. |
| Centers, Spreads, and Outliers | The students will compare the effects of outliers on measures of center and spread within dot plots and box plots. |
| Baking Soda and Vinegar: A statistical approach to a chemical reaction. | Students experiment with baking soda and vinegar and use statistics to determine which ratio of ingredients creates the most carbon dioxide. This hands-on activity applies the concepts of plot, center, and spread. |
| Should Statistics be Shapely? | Students will Interpret differences in shape, center, and spread of a variety of data displays, accounting for possible effects of extreme data points.
Students will create a Human Box Plot using their data to master the standard and learning objectives, then complete interactive notes with the classroom teacher, a formative assessment, and later a summative assessment to show mastery. |
| Exploring Box plots | This lesson involves real-world data situations. Students will use the data to create, explore, and compare the key components of a box plot. |
| The Debate: Who is a Better Baller? | In this activity the students will use NBA statistics on Lebron James and Tim Duncan who were key players in the 2014 NBA Finals, to calculate, compare, and discuss mean, median, interquartile range, variance, and standard deviation. They will also construct and discuss box plots. |
| Who's Better?--Using Data to Determine | This lesson is intended for use after students are able to construct data plots (histograms, line plots, box plots). Students are tasked with not only constructing data plots, but also matching data plots to data sets. In the summative assessment, students are given two data sets and asked to select which of three data plots (histogram, line plot, or box plot) would best be used to compare the data. After choosing and constructing their plot, students are then tasked with forming a conclusion based on the plots they have constructed. |
| Burgers to Smoothies. | Students will create double box plots to compare nutritional data about popular food choices. |
| A MEANingful Discussion about Central Tendency | Using relatable scenarios, this lesson explores the mean and median of a data set and how an outlier affects each measure differently. |
