This page contains links to projects aligned with Statistics & Probability CCSSs.

  1. Water Problems Grades 6 & 8 (Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape; Know that straight lines are widely used to model relationships between two quantitative variables; Suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line)
  2. Play Ball! Grades 7-12 (Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations; Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table; Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects; Use relative frequencies calculated for rows or columns to describe possible association between the two variables; Use data from a sample survey to estimate a population mean or proportion; develop a margin of error through the use of simulation models for random sampling)
  3. Investing -- Risk vs. Reward Grades 9-12 (Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets)
  4. ESL Statistical Analysts Grade 8 (Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association)
  5. Surreal Estate Grade 6 (Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape)
  6. The Game of Set Grade 6 (Recognize a statistical question as one that anticipates variability in the data related to the question and accounts for it in the answers)
  7. Gas Crunch Grade 6 (Display numerical data in plots on a number line, including dot plots, histograms, and box plots)
  8. My First Car Grade 6 (Solve multi-step real-life and mathematical problems posed with positive and negative rational numbers in any form (whole numbers, fractions, and decimals), using tools strategically; Apply properties of operations to calculate with numbers in any form; convert between forms as appropriate; and assess the reasonableness of answers using mental computation and estimation strategies)
  9. Generic vs. Name Brand Grades 8-12 (Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table; Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects; Use relative frequencies calculated for rows or columns to describe possible association between the two variables; Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points)
  10. Environmental Action Groups Grade 8 (Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table; Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects; Use relative frequencies calculated for rows or columns to describe possible association between the two variables)
  11. Bungee Barbie Grades 6-8 (Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape; Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations; Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities; Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association; Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points)
  12. Gas or Hybrid? Grades 9-12 (Represent data with plots on the real number line)
  13. Do Plants Keep Us Healthy? Grades 9-12 (Represent data on two quantitative variables on a scatter plot, and describe how the variables are related)
  14. Connecting Math to Our Lives Grades 6-12 (Recognize statistical question as one that anticipates variability in the data related to the question and accounts for it in the answers; Understand that statistics can be used to gain information about a population by examining a sample of the population; Understand that random sampling tends to produce representative samples and support valid inferences; Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table; Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects; Use relative frequencies calculated for rows or columns to describe possible association between the two variables; Define a random variable for a quantity of interest by assigning a numerical value to each event in a sample space; Graph the corresponding probability distribution using the same graphical displays as for data distributions)
  15. OF2 -- Our Footprints, Our Future Grades 6-12 (Recognize statistical question as one that anticipates variability in the data related to the question and accounts for it in the answers; Understand that statistics can be used to gain information about a population by examining a sample of the population; Understand that random sampling tends to produce representative samples and support valid inferences; Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table; Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects; Use relative frequencies calculated for rows or columns to describe possible association between the two variables; Define a random variable for a quantity of interest by assigning a numerical value to each event in a sample space; Graph the corresponding probability distribution using the same graphical displays as for data distributions)