N/A Misconceptions: Adopting strategies that model outcome chances inaccurately Creating poor sampling designs and allowing preventable bias to affect our results Misunderstanding how confounding variables affect data Concepts/Content: Competencies/Skills: Description of Activities: Random Recognize random outcomes in Direct teacher-led instruction Simulation a real-world situation group Q & A discussion Component Perform, describe, and interpret Independent student work a simulation based on Small group collaboration Response variable randomness Online remedial/enrichment videos Survey Draw conclusions about Bias questions being investigated Census Know the basic concepts and Representative terminology of sampling Simple random sample Recognize population Sampling frame parameters Sampling variability Understand the value of Stratified sample randomization as a defense Cluster sample against bias Systematic Draw a random sample from a Multistage sample master list of a population Observational study Report possible sources of bias Experiment in sampling methods Factor Know the basic principles of Level experimental design Treatment Design a completely randomized Experimental units experiment or observational Statistically significant study Control group Use blocking and/or blinding to Blinding reduce variation and bias Placebo Use graphical displays to Blocking compare responses for different Matching treatment groups Confounding
N/A Misconceptions: Adopting strategies that model outcome chances inaccurately Creating poor sampling designs and allowing preventable bias to affect our results Misunderstanding how confounding variables affect data Concepts/Content: Random Simulation Component Response variable Survey Bias Census Representative Simple random sample Sampling frame Sampling variability Stratified sample Cluster sample Systematic Multistage sample Observational study Experiment Factor Level Treatment Experimental units Statistically significant Control group Blinding Placebo Blocking Matching Confounding Competencies/Skills: Recognize random outcomes in a real-world situation Perform, describe, and interpret a simulation based on randomness Draw conclusions about questions being investigated Know the basic concepts and terminology of sampling Recognize population parameters Understand the value of randomization as a defense against bias Draw a random sample from a master list of a population Report possible sources of bias in sampling methods Know the basic principles of experimental design Design a completely randomized experiment or observational study Use blocking and/or blinding to reduce variation and bias Use graphical displays to compare responses for different treatment groups Description of Activities: Direct teacher-led instruction group Q & A discussion Independent student work Small group collaboration Online remedial/enrichment videos
2017-AP-Statistics-BHASD-Math-Curriculum.docx