Interpret data distributions represented in various ways. State whether the data is numerical or categorical, whether it is univariate or bivariate and interpret the different components and quantities in the display.
: Within the Probability and Statistics course, instruction includes the use of spreadsheets and technology.
| Name |
Description |
| Data Speaks Part 3 | Students will analyze a data set and create a data display that best represents the data, in this integrated lesson plan. |
| Data Speaks: Part 2 | Students will analyze and interpret data displays to explain the advantages and disadvantages of each data display, in this integrated lesson plan. |
| Choosing The Proper Chart For Your Data Set | Students will use previously gathered data to create a spreadsheet, choose and create a graph/chart that best diplays the data, and explain their reasoning for choosing the graph/chart, in this lesson plan. |
| Data Speaks: Part 1 | Students will classify variables as numerical/categorical and univariate/bivariate. Graphs representing various data related to citizenship will be used in this integrated lesson plan. |
| Got Bull? | This MEA is a genetics based lesson for upper level biology students. Students will review the data on several bulls and help a client choose the best bulls to begin a new cattle operation.
Model Eliciting Activities, MEAs, are open-ended, interdisciplinary problem-solving activities that are meant to reveal students’ thinking about the concepts embedded in realistic situations. Click here to learn more about MEAs and how they can transform your classroom. |
| How Hot Is It? | This lesson allows the students to connect the science of cricket chirps to mathematics. In this lesson, students will collect real data using the CD "Myths and Science of Cricket Chirps" (or use supplied data), display the data in a graph, and then find and use the mathematical model that fits their data. |
| 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.
|
| 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. |
| Heart Rate and Exercise: Is there a correlation? | Students will use supplied heart rate data to determine if heart rate and the amount of time spent exercising each week are correlated. Students will use GeoGebra to create scatter plots and lines of fit for the data and examine the correlation. Students will gather evidence to support or refute statistical statements made about correlation. The lesson provides easy to follow steps for using GeoGebra, a free online application, to generate a correlation coefficient for two given variables. |
| Can You Walk in My Shoes? | Students use real-life data to create dot-plots and two-way tables. Students will collect data at the beginning of the lesson and use that data to create double dot plots and frequency tables, finding and interpreting relative frequencies.
The assignment allows students to work collaboratively and cooperatively in groups. They will communicate within groups to compare shoes sizes and ages to acquire their data. From the collection of data they should be able to predict, analyze and organize the data into categories (two-way tables) or place on a number line (dot-plot).
As the class assignment concludes, a discussion of the final class display should take place about the purchasing of shoes versus ages and the relationship that either exists or doesn't exist. |
| Span the Distance Glider - Correlation Coefficient | This lesson will provide students with an opportunity to collect and analyze bivariate data and use technology to create scatter plots, lines of best fit, and determine the correlation strength of the data being compared. Students will have a hands on inquire based lesson that allows them to create gliders to analyze data. This lesson is an application of skills acquired in a bivariate unit of study. |
| Exercise Your Brain, Analyze Your Heart Rate | Students will compile the data gathered from measuring their resting heart rates and heart rates after exercising into box plots. Using these displays, they will analyze the data's center, shape, and spread. |
| 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. |
| 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. |
| Which One: Box plot, Dot Plot, or Histogram? | Students will be asked to obtain data and create a human box plot, which will be analyzed and explained using statistical terms. Students will then understand the differences and advantages to using the box plot, histogram, and dot plot. Students will also practice selecting the most appropriate graphical representation for a set of data. |
| 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. |
| 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. |
| 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. |
| 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. |
| How Old are the Players? | For this lesson, students will research the ages of players on two basketball teams. They will find the five-number summary, the mean, and determine if there are outliers in the data set. Two box plots will be created and the measures of center and variation analyzed. |
| Centers, Spreads, and Outliers | The students will compare the effects of outliers on measures of center and spread within dot plots and box plots. |
| Why do I have to have a bedtime? | This predict, observe, explain lesson that allows students to make predictions based on prior knowledge, observations, discussions, and calculations. Students will receive the opportunity to express themselves and their ideas while explaining what they learned. Students will make a prediction, collect data, and construct a scatter plot. Next, students will calculate the correlation coefficient and use it to describe the strength and magnitude of a relationship. |
| 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. |
| Using Two-Way Frequency Tables to Analyze Data | The television program, 60 Minutes reports that parents are intentionally holding their children back in kindergarten to give them a competitive advantage in sports later on in life. The students will use data collected to decide if this is truly a trend in the United States. |
| Quantitative or Qualitative? | This lesson examines the differences between quantitative and qualitative data and guides students through displaying quantitative data on a scatter plot and then separating the data into qualitative categories to be displayed and interpreted in a two-way frequency table. |
| ENSO: Friend or Foe? | In this activity students will compare El Nino / La Nina Anomaly data and compare the data to hurricane frequency in the Atlantic Basin. The ENSO Anomaly Data has been provided. Students will then research hurricane frequency and compare both data sets. To close the activity, students will need to apply the knowledge learned in the lesson to synthesize and make a prediction in a writing prompt. |
| Are you a CrimiNole or Gatorbait? Two rivalries in one table! | This is an introduction to two-way frequency tables. The lesson will be delivered using a PowerPoint presentation. The teacher will introduce and define joint and marginal frequency, demonstrate how two-way frequency tables are constructed from a given set of data, calculate relative frequencies, and draw conclusions based on the information in the table. Students will practice these skills through guided practice with the teacher, independent practice, and complete a summative assessment to measure student learning. All resources, including the PowerPoint, have been provided. |
| Homework or Play? | Students will be given data and then plot the data using a graphical method of choice (dot plot, bar graph, box plot, etc.) The students will work in groups and then analyze and summarize the data. |
| Sweet Statistics - A Candy Journey | Students will sort pieces of candy by color and then calculate statistical information such as mean, median, mode, interquartile range, and standard deviation. They will also create an Excel spreadsheet with the candy data to generate pie charts and column charts. Finally, they will compare experimental data to theoretical data and explain the differences between the two. This is intended to be an exercise for an Algebra 1 class. Students will need at least 2 class periods to sort their candy, make the statistical calculations, and create the charts in Excel. |
| Interpreting Box Plots | Students will analyze various real world scenario data sets and create, analyze, and interpret the components of the box plots. Students will use data from morning routines, track times, ages, etc. Lesson includes a PowerPoint, homework, and assessments. |
| If the line fits, where's it? | In this lesson students learn how to informally determine a "best fit" line for a scatter plot by considering the idea of closeness. |
| 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. |
| Correlation or Causation: That is the question | Students will learn how to analyze whether two events/properties demonstrate a correlation or causation or both. They will learn what factors are involved when evaluating whether correlated events demonstrate causation. If two events are claimed to be causal when they are not, they will be able to determine why, and which (if any) causal fallacies are present. At the close of the lesson students will be given situational data and develop a newscast that assumes causation when in fact there is no causal link. Students who are observing will analyze each presentation and determine which (if any) causal fallacy was used (or explain why the newscast is correct in their assumption of causality). |
| A Bunch of Hot Air....Balloon Rides That Is! | This is a 9th grade MEA about weather prediction and limitations thereof. This MEA will ask students to work as a team to design a plan to select the source for weather forecasts for a private hot-air balloon tour company. Students will evaluate information from various weather predictions sources to determine which one is best for a hot-air balloon ride company.
Model Eliciting Activities, MEAs, are open-ended, interdisciplinary problem-solving activities that are meant to reveal students’ thinking about the concepts embedded in realistic situations. Click here to learn more about MEAs and how they can transform your classroom. |
| Smarter than a Statistician: Correlations and Causation in the Real World! | Students will learn to distinguish between correlation and causation. They will build their skills by playing two interactive digital games that are included in the lesson. The lesson culminates with a research project that requires students to find and explain the correlation between two real world events. |
| Advantages and Disadvantages of Dot Plots, Histograms, and Box Plots | Students will compare the advantages and disadvantages of dot plots, histograms, and box plots. During this lesson, students will review the statistical process and learn the characteristics of a statistical question; whether it be numerical or categorical. Students will apply the information learned in a project that involves real-world issues and make an analysis based on the data collected. |
| The Perfect Steak Oven | The lesson integrates language arts and physical science standards through the use of a Model Eliciting Activity. Students collaborate to create a procedure to solve a particular problem (the best steak oven).
Model Eliciting Activities, MEAs, are open-ended, interdisciplinary problem-solving activities that are meant to reveal students’ thinking about the concepts embedded in realistic situations. Click here to learn more about MEAs and how they can transform your classroom. |
| A New View: Space Exploration | This MEA is about space exploration. Students will review data on six extrasolar planets and determine which one would be most feasible to explore first.
Model Eliciting Activities, MEAs, are open-ended, interdisciplinary problem-solving activities that are meant to reveal students’ thinking about the concepts embedded in realistic situations. Click here to learn more about MEAs and how they can transform your classroom. |
| Interpreting Statistics: A Case of Muddying the Waters | This lesson is intended to help you assess how well students are able to:
- Interpret data and evaluate statistical summaries.
- Critique someone else's interpretations of data and evaluations of statistical summaries.
The lesson also introduces students to the dangers of misapplying simple statistics in real-world contexts, and illustrates some of the common abuses of statistics and charts found in the media. |
| The Election Resource | In this Model Eliciting Activity, MEA, students will analyze sets of data and draw conclusions to justify the top candidates for positions of President, Treasurer, and Secretary of the school's Student Government Association.
Model Eliciting Activities, MEAs, are open-ended, interdisciplinary problem-solving activities that are meant to reveal students’ thinking about the concepts embedded in realistic situations. MEAs resemble engineering problems and encourage students to create solutions in the form of mathematical and scientific models. Students work in teams to apply their knowledge of science and mathematics to solve an open-ended problem while considering constraints and tradeoffs. Students integrate their ELA skills into MEAs as they are asked to clearly document their thought processes. MEAs follow a problem-based, student-centered approach to learning, where students are encouraged to grapple with the problem while the teacher acts as a facilitator. To learn more about MEAs visit: https://www.cpalms.org/cpalms/mea.aspx |
| Scatter plots, spaghetti, and predicting the future | Students will construct a scatter plot from given data. They will identify the correlation, sketch an approximate line of fit, and determine an equation for the line of fit. They will explain the meaning of the slope and y-intercept in the context of the data and use the line of fit to interpolate and extrapolate values. |
