Основно съдържание
Math
Common Core Math
High School: Statistics & Probability: Making Inferences and Justifying Conclusions
Understand statistics as a process for making inferences about population parameters based on a random sample from that population.
Decide if a specified model is consistent with results from a given data-generating process, e.g., using simulation.?
Recognize the purposes of and differences among sample surveys, experiments, and observational studies; explain how randomization relates to each.
- Can causality be established from this study?
- Conclusions in observational studies versus experiments
- Experiment design considerations
- Experiment designs
- Finding errors in study conclusions
- Introduction to experiment design
- Invalid conclusions from studies example
- Matched pairs experiment design
- Principles of experiment design
- Random sampling vs. random assignment (scope of inference)
- Sampling method considerations
- Sampling methods
- Simple random samples
- Simulation and randomness: Random digit tables
- Systematic random sampling
- Techniques for generating a simple random sample
- Techniques for random sampling and avoiding bias
- The language of experiments
- Types of statistical studies
- Types of studies
- Types of studies
- Worked example identifying observational study
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.
Use data from a randomized experiment to compare two treatments; use simulations to decide if differences between parameters are significant.
Evaluate reports based on data.