Arkansas Mathematics Standards (adopted in 2023): Statistics
Skills available for Arkansas Statistics standards
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MI
Making Inferences & Justifying Conclusion
Surveys, Experiments, & Observational Data: Students make inferences and justify conclusions from sample surveys, experiments, and observational studies.
S.MI.1 Estimate a population mean or proportion from a sample survey; develop a margin of error through the use of simulation models for random sampling.
S.MI.1 Estimate a population mean or proportion from a sample survey; develop a margin of error through the use of simulation models for random sampling.
S.MI.2 Calculate the standardized test statistic and p-value for a test about a population proportion and a population mean; determine if the sample data provides convincing evidence against a parameter claim.
S.MI.2 Calculate the standardized test statistic and p-value for a test about a population proportion and a population mean; determine if the sample data provides convincing evidence against a parameter claim.
S.MI.3 Compare two treatment groups in an experiment and determine if the difference in parameters is significant by calculating the standardized test statistics and p-value.
S.MI.3 Compare two treatment groups in an experiment and determine if the difference in parameters is significant by calculating the standardized test statistics and p-value.
RP
Conditional Probability & Rules of Probability
Compute Probability of Compound Events: Students use the rules of probability to compute probabilities of compound events.
S.RP.1 Determine unions or intersections of events in a sample space; determine complements of events.
S.RP.1 Determine unions or intersections of events in a sample space; determine complements of events.
S.RP.2 Identify the two components that make up a legitimate probability model/distribution.
S.RP.2 Identify the two components that make up a legitimate probability model/distribution.
Independence & Conditional Probability: Students understand and use independence and conditional probability to interpret data.
S.RP.3 Determine if two events, A and B, are independent when given the probabilities of A and B.
S.RP.3 Determine if two events, A and B, are independent when given the probabilities of A and B.
S.RP.4 Calculate and use conditional probabilities to determine if events are independent.
S.RP.4 Calculate and use conditional probabilities to determine if events are independent.
S.RP.5 Create and analyze two-way frequency tables of data to calculate marginal, joint, and conditional probabilities.
S.RP.5 Create and analyze two-way frequency tables of data to calculate marginal, joint, and conditional probabilities.
S.RP.6 Using a two-way table, determine if two events are independent.
S.RP.6 Using a two-way table, determine if two events are independent.
S.RP.7 Explain conditional probability and independence using everyday language in a variety of real-world contexts.
S.RP.7 Explain conditional probability and independence using everyday language in a variety of real-world contexts.
S.RP.8 Find the conditional probability of A given B, P(A|B), and interpret the answer in terms of the model, including two-way frequency tables and Venn diagrams.
S.RP.8 Find the conditional probability of A given B, P(A|B), and interpret the answer in terms of the model, including two-way frequency tables and Venn diagrams.
S.RP.9 Apply the Addition Rule, P(A or B) = P(A) + P(B) – P(A and B) and interpret the answer.
S.RP.9 Apply the Addition Rule, P(A or B) = P(A) + P(B) – P(A and B) and interpret the answer.
S.RP.10 Identify whether or not two events are mutually exclusive / disjoint.
S.RP.10 Identify whether or not two events are mutually exclusive / disjoint.
S.RP.11 Apply the general Multiplication Rule, P(A and B) = P(A)P(B|A) = P(B)P(A|B) and interpret the answer.
S.RP.11 Apply the general Multiplication Rule, P(A and B) = P(A)P(B|A) = P(B)P(A|B) and interpret the answer.
S.RP.12 Compute the probability of compound events and solve problems using combinations, permutations, Venn Diagrams, and Tree Diagrams.
S.RP.12 Compute the probability of compound events and solve problems using combinations, permutations, Venn Diagrams, and Tree Diagrams.
PMD
Use Probability to Make Decisions
Expected Values: Students calculate and use expected values of random variables to solve problems.
S.PMD.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.
S.PMD.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.
S.PMD.2 Calculate the expected value for a discrete random variable; describe the expected value as the mean or typical value of the probability distribution in context.
S.PMD.2 Calculate the expected value for a discrete random variable; describe the expected value as the mean or typical value of the probability distribution in context.
S.PMD.3 Create a probability distribution of a discrete random variable using theoretical probabilities and use the probability distribution to calculate the probability of an event.
S.PMD.3 Create a probability distribution of a discrete random variable using theoretical probabilities and use the probability distribution to calculate the probability of an event.
S.PMD.4 Create a probability distribution for a discrete random variable using experimental or observational data; calculate the expected value.
S.PMD.4 Create a probability distribution for a discrete random variable using experimental or observational data; calculate the expected value.
S.PMD.5 Use probability density models such as the normal curve and uniform density curve to model real-world data; calculate probabilities of continuous random variables using these models.
S.PMD.5 Use probability density models such as the normal curve and uniform density curve to model real-world data; calculate probabilities of continuous random variables using these models.
Outcomes of Decisions: Students evaluate outcomes of decisions using probability.
S.PMD.6 Analyze the costs and benefits of possible outcomes of making a decision by assigning probabilities to particular payoff values of a discrete random variable and calculate expected values.
S.PMD.6 Analyze the costs and benefits of possible outcomes of making a decision by assigning probabilities to particular payoff values of a discrete random variable and calculate expected values.
CD
Collecting Data & Data Bias
Data Collection: Students explore best practices of collecting data while identifying possible sources of bias in data collection methods.
S.CD.1 Describe how to take a simple random sample using technology or a random number table.
S.CD.1 Describe how to take a simple random sample using technology or a random number table.
S.CD.2 Use randomization strategies to ensure random selection processes are fair.
S.CD.2 Use randomization strategies to ensure random selection processes are fair.
S.CD.3 Understand that certain types of sampling methods may lead to bias, such as convenience and voluntary samples.
S.CD.3 Understand that certain types of sampling methods may lead to bias, such as convenience and voluntary samples.
DD
Displaying & Describing Distributions of Data
Data Representation: Students represent raw data in tabular and graphical form to describe features of the data and summarize trends.
S.DD.1 Distinguish between categorical and quantitative data.
S.DD.1 Distinguish between categorical and quantitative data.
S.DD.2 Determine if there is an association between two quantitative variables using the correlation coefficient and scatter plots.
S.DD.2 Determine if there is an association between two quantitative variables using the correlation coefficient and scatter plots.
S.DD.3 Model real-world data using least squares regression techniques.
S.DD.3 Model real-world data using least squares regression techniques.