Colorado Academic Standards

Colorado Department of Education

Colorado Academic Standards Online

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clear Content Area: Mathematics - 2019 // Grade Level: High School // Standard Category: 3. Data, Statistics, and Probability

Mathematics - 2019

High School, Standard 3. Data, Statistics, and Probability

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More information icon Prepared Graduates:

  • MP2. Reason abstractly and quantitatively.
  • MP4. Model with mathematics.
  • MP5. Use appropriate tools strategically.

More information icon Grade Level Expectation:

HS.S-ID.A. Interpreting Categorical & Quantitative Data: Summarize, represent, and interpret data on a single count or measurement variable.

More information icon Evidence Outcomes:

Students Can:

  1. Model data in context with plots on the real number line (dot plots, histograms, and box plots). (CCSS: HS.S-ID.A.1)
  2. 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. (CCSS: HS.S-ID.A.2)
  3. Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers). (CCSS: HS.S-ID.A.3)
  4. Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages and identify data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve. (CCSS: HS.S-ID.A.4)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Understand statistical descriptors of data and interpret and be critical of the use of statistics outside of school. (Professional Skills: Information Literacy)
  2. Create, analyze, and synthesize visual representations of statistical data. (Entrepreneurial Skills: Literacy/Reading)
  3. Reason about the context of the data separate from the numbers involved and about the numbers separate from the context; move fluidly between contextualized reasoning and decontextualized reasoning. (MP2)
  4. Use statistics and statistical reasoning to make sense of, interpret, and generalize about real-world situations. (MP4)
  5. Use technology to reason about, model, and compute statistical problems and to interpret results within the context. Additionally, students sketch a distribution and answer questions about it just from knowledge of these three facts: shape, center, and spread. (MP5)

More information icon Inquiry Questions:

  1. How would you describe the difference between the distributions of two data sets with the same measure of center but different measures of spread?
  2. Why do we have multiple measures of center? Why wouldn’t we always just use the mean?
  3. What questions might a statistician ask about extreme data points? How do they/should they affect the interpretation of the data?

More information icon Coherence Connections:

  1. This expectation is in addition to the major work of high school.
  2. In Grade 6, students study data displays, measures of center, and measures of variability. Standard deviation, introduced in high school, involves much the same principle as the mean absolute deviation (MAD) that students use beginning in Grade 6. Students should see that the standard deviation is the appropriate measure of spread for data distributions that are approximately normal in shape, as the standard deviation then has a clear interpretation related to relative frequency.
  3. At this level, students are not expected to fit normal curves to data. Instead, the aim is to look for broad approximations, with application of the rather rough “empirical rule” (also called the 68%–95% Rule) for distributions that are somewhat bell-shaped. The better the bell, the better the approximation.

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More information icon Prepared Graduates:

  • MP5. Use appropriate tools strategically.
  • MP7. Look for and make use of structure.

More information icon Grade Level Expectation:

HS.S-ID.B. Interpreting Categorical & Quantitative Data: Summarize, represent, and interpret data on two categorical and quantitative variables.

More information icon Evidence Outcomes:

Students Can:

  1. Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data. (CCSS: HS.S-ID.B.5)
  2. Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. (CCSS: HS.S-ID.B.6)
    1. Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models. (CCSS: HS.S-ID.B.6.a)
    2. Informally assess the fit of a function by plotting and analyzing residuals. (CCSS: HS.S-ID.B.6.b)
    3. Fit a linear function for a scatter plot that suggests a linear association. (CCSS: HS.S-ID.B.6.c)
  3. Distinguish between correlation and causation. (CCSS: HS.S-ID.C.9)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Create, interpret and demonstrate statistical understanding using technology. (Professional Skills: Use Information and Communications Technologies)
  2. Analyze, synthesize, and interpret information from scatter plots and residual plots, and construct explanations for these interpretations. (Entrepreneurial Skills: Literacy/Reading and Writing)
  3. Use calculators or computer software to compute with large data sets then interpret and make statistical use of the results. (MP5)
  4. Look for patterns in tables and on scatter plots. (MP7)

More information icon Inquiry Questions:

  1. Does a high correlation (close to \(\pm1\)) in the data of two quantitative variables mean that one causes a response in the other? Why or why not?
  2. In what way(s) does a plot of the residuals help us consider the best model for a data set?

More information icon Coherence Connections:

  1. This expectation supports the major work of high school.
  2. In Grade 8, students explore scatter plots with linear associations and create equations for informal “lines of best fit” in support of their in-depth study of linear equations. In high school, this statistical topic is formalized and includes fitting quadratic or exponential functions (where appropriate) in addition to linear. Additionally, students use graphing calculators or software to analyze the residuals and interpret the meaning of this analysis in terms of the correctness of fit.
  3. It is important that students understand the foundational concept that “correlation does not equal causation” within their study of curve/line-fitting and the associated numerical calculations. This presents a launching point for discussions about the design and analysis of randomized experiments, also included in high school statistics.
  4. The mathematics of summarizing, representing, and interpreting data on two categorical or quantitative variables lays the foundation for more advanced statistical topics, such as inference.

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More information icon Prepared Graduates:

  • MP2. Reason abstractly and quantitatively.
  • MP5. Use appropriate tools strategically.

More information icon Grade Level Expectation:

HS.S-ID.C. Interpreting Categorical & Quantitative Data: Interpret linear models.

More information icon Evidence Outcomes:

Students Can:

  1. Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data. (CCSS: HS.S-ID.C.7)
  2. Using technology, compute and interpret the correlation coefficient of a linear fit. (CCSS: HS.S-ID.C.8)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Critically interpret the use of statistics in their lives outside of school. (Professional Skills: Information Literacy)
  2. Use technology and interpret results as they relate to life outside of school. (Professional Skills: Use Information and Communications Technologies)
  3. Reason quantitatively about the contextual meaning of slope and intercept of linear models of real-world data, and when the numerical value has no meaning within the context. (MP2)
  4. Use technology to compute, model, and reason about linear representations of bivariate data, and interpret the meaning of the calculated values. (MP5)

More information icon Inquiry Questions:

  1. How is it possible for the intercept of a linear model to not have meaning in the context of the data?
  2. What does the correlation coefficient of a linear model tell us? What actions, recommendations, or interpretations might we have about the correlation coefficient?

More information icon Coherence Connections:

  1. This expectation is in addition to the major work of high school.
  2. The comprehensive study of linear functions in Grade 8 allows the high school focus to shift from computation to interpretation of the components of a linear function. Whereas in Grade 8 the slope/rate of change is described mathematically, the work here focuses on the contextual meaning of the rate of change and its applicability to the linear function as a model to predict unknown values of the real-world scenario.
  3. The statistics concepts in high school lend themselves to application in other content areas, such as science (e.g., the relationship between cricket chirps and temperature), sports (e.g., the relationship between the year and the average number of home runs in major league baseball), and social studies (e.g., the relationship between returns from buying Treasury bills and from buying common stocks).

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More information icon Prepared Graduates:

  • MP3. Construct viable arguments and critique the reasoning of others.
  • MP6. Attend to precision.

More information icon Grade Level Expectation:

HS.S-IC.A. Making Inferences & Justifying Conclusions: Understand and evaluate random processes underlying statistical experiments.

More information icon Evidence Outcomes:

Students Can:

  1. Describe statistics as a process for making inferences about population parameters based on a random sample from that population. (CCSS: HS.S-IC.A.1)
  2. Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation. For example, a model says a spinning coin falls heads up with probability \(0.5\). Would a result of \(5\) tails in a row cause you to question the model? (CCSS: HS.S-IC.A.2)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Students understand how statistics serves to make inferences about a population. (Professional Skills: Information Literacy)
  2. Use a variety of statistical tools to construct and defend logical arguments based on data. (MP3)
  3. Understand and describe the differences between statistics (derived from samples) and parameters (characteristic of the population). (MP6)

More information icon Inquiry Questions:

  1. What is the difference between a statistic and a parameter? Why do we need both?
  2. Why is it important that random sampling be used to make inferences about population parameters?

More information icon Coherence Connections:

  1. This expectation represents major work of high school.
  2. In Grade 7, students approximate the probability of a chance event by collecting data on the chance process that produces it and observing its long-run relative frequency, and predict the approximate relative frequency given the probability.
  3. The concepts of this expectation are foundational for advanced study of statistical inference.

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More information icon Prepared Graduates:

  • MP3. Construct viable arguments and critique the reasoning of others.
  • MP4. Model with mathematics.
  • MP8. Look for and express regularity in repeated reasoning.

More information icon Grade Level Expectation:

HS.S-IC.B. Making Inferences & Justifying Conclusions: Make inferences and justify conclusions from sample surveys, experiments, and observational studies.

More information icon Evidence Outcomes:

Students Can:

  1. Identify the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each. (CCSS: HS.S-IC.B.3)
  2. 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. (CCSS: HS.S-IC.B.4)
  3. Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant. (CCSS: HS.S-IC.B.5)
  4. Evaluate reports based on data. Define and explain the meaning of significance, both statistical (using p-values) and practical (using effect size). (CCSS: HS.S-IC.B.6)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Apply statistical methods to interpret information and draw conclusions in real-world contexts. (Entrepreneurial Skills: Critical Thinking/Problem Solving)
  2. Evaluate reports based on data and explain the practical and statistical significance of the results. (Entrepreneurial Skills: Literacy/Reading and Writing)
  3. Use sampling, design, and results of sample surveys, experiments, and observational studies and justify reasonable responses and misleading or inaccurate results. (MP3)
  4. Use sampling, randomization, and simulations to model, describe, and interpret real-world situations, and use margin of error, p-values and effect size to describe the meaning of the results. (MP4)
  5. Observe regular patterns in distributions of sample statistics and use them to make generalizations about the population parameter. (MP8)

More information icon Inquiry Questions:

  1. How can the results of a statistical investigation be used to support or critique a hypothesis?
  2. What happens to sample-to-sample variability when you increase the sample size?
  3. How does randomization minimize bias?
  4. Can the practical significance of a given study matter more than statistical significance? Why is it important to know the difference?
  5. Why is the margin of error in a study important?

More information icon Coherence Connections:

  1. This expectation represents major work of high school.
  2. In Grades 6–8, students engage with statistics to: (a) draw informal comparative inferences about two populations; (b) informally assess degree of visual overlap of two numerical data distributions; (c) use measures of center and measure of variability for numerical data from random samples to draw comparative inferences; and (d) generate or simulate multiple samples to gauge variation in estimates and predictions. These concepts are extended and formalized in high school.
  3. Students’ understanding of random sampling is the key that allows the computation of margins of error in estimating a population parameter and can be extended to the random assignment of treatments in an experiment.

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More information icon Prepared Graduates:

  • MP3. Construct viable arguments and critique the reasoning of others.
  • MP4. Model with mathematics.
  • MP6. Attend to precision.

More information icon Grade Level Expectation:

HS.S-CP.A. Conditional Probability & the Rules of Probability: Understand independence and conditional probability and use them to interpret data.

More information icon Evidence Outcomes:

Students Can:

  1. Describe events as subsets of a sample space (the set of outcomes) using characteristics (or categories) of the outcomes, or as unions, intersections, or complements of other events (“or,” “and,” “not”). (CCSS: HS.S-CP.A.1)
  2. Explain that two events \(A\) and \(B\) are independent if the probability of \(A\) and \(B\) occurring together is the product of their probabilities, and use this characterization to determine if they are independent. (CCSS: HS.S-CP.A.2)
  3. Using the conditional probability of \(A\) given \(B\) as \(P(A \mbox{and} B)/P(B)\), interpret the independence of \(A\) and \(B\) as saying that the conditional probability of \(A\) given \(B\) is the same as the probability of \(A\), and the conditional probability of \(B\) given \(A\) is the same as the probability of \(B\). (CCSS: HS.S-CP.A.3)
  4. Construct and interpret two-way frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. For example, collect data from a random sample of students in your school on their favorite subject among math, science, and English. Estimate the probability that a randomly selected student from your school will favor science given that the student is in 10th grade. Do the same for other subjects and compare the results. (CCSS: HS.S-CP.A.4)
  5. Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations. For example, compare the chance of having lung cancer if you are a smoker with the chance of being a smoker if you have lung cancer. (CCSS: HS.S-CP.A.5)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Apply probability concepts and interpret their real-world meaning. (Entrepreneurial Skills: Critical Thinking/Problem Solving)
  2. Use probability values to describe how multiple random events are related, including the ideas of independence and conditional probability as they have meaning in the real world. (MP3)
  3. Use probability to support the independence of two random events, or to make sense to conditional probabilities. (MP4)
  4. Use clear definitions and accurate notation to express probability concepts. (MP6)

More information icon Inquiry Questions:

  1. How can you describe the formula for determining independence in everyday language? Why does this make sense?
  2. How can you describe the formula for conditional probability in everyday language? Why does this make sense?
  3. How can a careful and clear display of categorical data in a table help in interpreting relationships between the values expressed?

More information icon Coherence Connections:

  1. This expectation is in addition to the major work of high school.
  2. In Grade 7, students encounter the development of basic probability, including chance processes, probability models, and sample spaces.
  3. In high school, the relative frequency approach to probability is extended to conditional probability and independence, rules of probability and their use in finding probabilities of compound events, and the use of probability distributions to solve problems involving expected value. As seen in the expectations for Making Inferences & Justifying Conclusions, there is a strong connection between statistics and probability.

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More information icon Prepared Graduates:

  • MP1. Make sense of problems and persevere in solving them.
  • MP2. Reason abstractly and quantitatively.
  • MP4. Model with mathematics.

More information icon Grade Level Expectation:

HS.S-CP.B. Conditional Probability & the Rules of Probability: Use the rules of probability to compute probabilities of compound events in a uniform probability model.

More information icon Evidence Outcomes:

Students Can:

  1. Find the conditional probability of \(A\) given \(B\) as the fraction of \(B\)’s outcomes that also belong to \(A\), and interpret the answer in terms of the model. (CCSS: HS.S-CP.B.6)
  2. Apply the Addition Rule, \(P\left( A \mbox{ or } B \right) = P \left(A \right) + P \left( B \right) – P \left( A \text{ and } B \right)\), and interpret the answer in terms of the model. (CCSS: HS.S-CP.B.7)
  3. (+) Apply the general Multiplication Rule in a uniform probability model, \(P \left( A \text{ and } B \right) = P \left( A \right) P \left( B \mid A \right) = P \left( B \right) P \left( A \mid B \right)\), and interpret the answer in terms of the model. (CCSS: HS.S-CP.B.8)
  4. (+) Use permutations and combinations to compute probabilities of compound events and solve problems. (CCSS: HS.S-CP.B.9)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Understand and apply probability to the real world. (Entrepreneurial Skills: Critical Thinking/Problem Solving)
  2. Consider multiple approaches and representations for representing and understanding probabilities of random events. (MP1)
  3. Consider probability concepts in context and mathematically and make connections between both types of reasoning. (MP2)
  4. Use probability models to represent and make sense of real-world phenomena. (MP4)

More information icon Inquiry Questions:

  1. What is an everyday situation that helps explain the Addition Rule? How does the context help you understand the subtraction of \(P \left( A \text{ and } B \right)\) from \(P \left(A \right) + P \left( B \right)\)?

More information icon Coherence Connections:

  1. This expectation is in addition to the major work of high school and includes advanced (+) outcomes.
  2. Studying and understanding probability, which is always in a context, provides high school students with a mathematical structure for dealing with the many changes they will experience as part of life.

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More information icon Prepared Graduates:

  • MP2. Reason abstractly and quantitatively.
  • MP4. Model with mathematics.

More information icon Grade Level Expectation:

HS.S-MD.A. Using Probability to Make Decisions: Calculate expected values and use them to solve problems.

More information icon Evidence Outcomes:

Students Can:

  1. (+) 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. (CCSS: HS.S-MD.A.1)
  2. (+) Calculate the expected value of a random variable; interpret it as the mean of the probability distribution. (CCSS: HS.S-MD.A.2)
  3. (+) Develop a probability distribution for a random variable defined for a sample space in which theoretical probabilities can be calculated; find the expected value. For example, find the theoretical probability distribution for the number of correct answers obtained by guessing on all five questions of multiple-choice test where each question has four choices, and find the expected grade under various grading schemes. (CCSS: HS.S-MD.A.3)
  4. (+) Develop a probability distribution for a random variable defined for a sample space in which probabilities are assigned empirically; find the expected value. For example, find a current data distribution on the number of TV sets per household in the United States, and calculate the expected number of sets per household. How many TV sets would you expect to find in \(100\) randomly selected households? (CCSS: HS.S-MD.A.4)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Understand and apply probability to the real world. (Entrepreneurial Skills: Critical Thinking/Problem Solving)
  2. Consider probability concepts in context and mathematically, and make connections between both types of reasoning. (MP2)
  3. Apply probability models to real-world situations, calculate appropriately, and interpret the results. (MP4)

More information icon Inquiry Questions:

  1. What is a random variable?
  2. Create a context which can be used to describe a random variable.

More information icon Coherence Connections:

  1. This expectation represents advanced (+) work of high school.

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More information icon Prepared Graduates:

  • MP4. Model with mathematics.

More information icon Grade Level Expectation:

HS.S-MD.B. Using Probability to Make Decisions: Use probability to evaluate outcomes of decisions.

More information icon Evidence Outcomes:

Students Can:

  1. (+) Weigh the possible outcomes of a decision by assigning probabilities to payoff values and finding expected values. (CCSS: HS.S-MD.B.5)
    1. Find the expected payoff for a game of chance. For example, find the expected winnings from a state lottery ticket or game at a fast-food restaurant. (CCSS: HS.S-MD.B.5.a)
    2. Evaluate and compare strategies on the basis of expected values. For example, compare a high-deductible versus a low-deductible automobile insurance policy using various, but reasonable, chances of having a minor or major accident. (CCSS: HS.S-MD.B.5.b)
  2. (+) Use probabilities to make fair decisions (e.g., drawing by lots, using a random number generator). (CCSS: HS.S-MD.B.6)
  3. (+) Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game). (CCSS: HS.S-MD.B.7)

More information icon Academic Contexts and Connections:

More information icon Colorado Essential Skills and Mathematical Practices:

  1. Students understand and apply probability to the real world. (Entrepreneurial Skills: Critical Thinking/Problem Solving)
  2. Apply probability models to real-world situations, calculate appropriately, and interpret the results. (MP4)

More information icon Inquiry Questions:

  1. How does probability help in the decision-making process?
  2. Why does expected value require the weighted average of all possible values?

More information icon Coherence Connections:

  1. The expectation represents advanced (+) work of high school.

Need Help? Submit questions or requests for assistance to bruno_j@cde.state.co.us