High School — Statistics and Probability

Other Common Core State Standards Mathematics sets

• Grade K
• Grade 1
• Grade 2
• Grade 3
• Grade 4
• Grade 5
• Grade 6
• Grade 7
• Grade 8
• Grades 9, 10, 11, 12 (All Topics)
• High School — Algebra
• High School — Functions
• High School — Geometry
• High School — Number and Quantity
• Standards for Mathematical Practice

Represent data with plots on the real number line (dot plots, histograms, and box plots).CCSS.Math.Content.HSS-ID.A.1

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.Math.Content.HSS-ID.A.2

Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).CCSS.Math.Content.HSS-ID.A.3

Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.CCSS.Math.Content.HSS-ID.A.4

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.Math.Content.HSS-ID.B.5

Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.CCSS.Math.Content.HSS-ID.B.6

Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.CCSS.Math.Content.HSS-ID.C.7

Compute (using technology) and interpret the correlation coefficient of a linear fit.CCSS.Math.Content.HSS-ID.C.8

Distinguish between correlation and causation.CCSS.Math.Content.HSS-ID.C.9

Understand statistics as a process for making inferences about population parameters based on a random sample from that population.CCSS.Math.Content.HSS-IC.A.1

Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation.CCSS.Math.Content.HSS-IC.A.2

Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.CCSS.Math.Content.HSS-IC.B.3

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.Math.Content.HSS-IC.B.4

Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.CCSS.Math.Content.HSS-IC.B.5

Evaluate reports based on data.CCSS.Math.Content.HSS-IC.B.6

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.Math.Content.HSS-CP.A.1

Understand 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.Math.Content.HSS-CP.A.2

Understand the conditional probability of A given B as P(A and B)/P(B), and interpret 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.Math.Content.HSS-CP.A.3

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.CCSS.Math.Content.HSS-CP.A.4

Recognize and explain the concepts of conditional probability and independence in everyday language and everyday situations.CCSS.Math.Content.HSS-CP.A.5

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.Math.Content.HSS-CP.B.6

Apply the Addition Rule, P(A or B) = P(A) + P(B) - P(A and B), and interpret the answer in terms of the model.CCSS.Math.Content.HSS-CP.B.7

(+) Apply the general Multiplication Rule in a uniform probability model, P(A and B) = P(A)P(B|A) = P(B)P(A|B), and interpret the answer in terms of the model.CCSS.Math.Content.HSS-CP.B.8

(+) Use permutations and combinations to compute probabilities of compound events and solve problems.CCSS.Math.Content.HSS-CP.B.9

(+) 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.Math.Content.HSS-MD.A.1

(+) Calculate the expected value of a random variable; interpret it as the mean of the probability distribution.CCSS.Math.Content.HSS-MD.A.2

(+) Develop a probability distribution for a random variable defined for a sample space in which theoretical probabilities can be calculated; find the expected value.CCSS.Math.Content.HSS-MD.A.3

(+) Develop a probability distribution for a random variable defined for a sample space in which probabilities are assigned empirically; find the expected value.CCSS.Math.Content.HSS-MD.A.4

(+) Weigh the possible outcomes of a decision by assigning probabilities to payoff values and finding expected values.CCSS.Math.Content.HSS-MD.B.5

(+) Use probabilities to make fair decisions (e.g., drawing by lots, using a random number generator).CCSS.Math.Content.HSS-MD.B.6

(+) Analyze decisions and strategies using probability concepts (e.g., product testing, medical testing, pulling a hockey goalie at the end of a game).CCSS.Math.Content.HSS-MD.B.7