Hauptinhalt
Nebraska Math
High School Advanced Topics: DATA
Students will solve problems and reason with data/probability using multiple representations, make connections within math and across disciplines, and communicate their ideas.
Explain what constitutes good practice in designing a sample survey, an experiment, and an observational study.
Explain the use of randomization to reduce the influence of confounding or lurking variables.
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Explain issues of bias and confounding variables in a study and their implications for interpretation.
Demonstrate knowledge of the role sampling distributions play in the estimation of an unknown population parameter through the use of appropriate sampling techniques.
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Determine when a data set can be reasonably said to be normally distributed and draw conclusions about the data from the associated normal distribution.
Use technology to develop regression models for linear and non-linear data to predict unobserved outcomes. Apply algebraic transformations to non-linear data to generate a linearized data set and employ linear regression techniques to analyze the non-linear data set.
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Weigh the possible outcomes of a decision by assigning probabilities to payoff values and finding expected values. Interpret the expected value as the mean of a probability distribution.
Communicate what constitutes statistical significance. Interpret statistical significance in the context of a situation and answer investigative questions appropriately.
Use data to compare two groups, describe sample variability, and decide if differences between parameters are significant based on the statistics.
Use probability as a tool for assessing risk and for informed decision making by computing and interpreting P-values.
Use confidence intervals to estimate an unknown population parameter.
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