| Curricular Competency |
Assess the justification for competing historical accounts after investigating points of contention, reliability of sources, and adequacy of evidence (evidence) |
20th Century World History 12 |
No CCG |
| Keyword: Assess the justification for competing historical accounts after investigating points of contention, reliability of sources, and adequacy of evidence |
Elaboration: Key questions:What criteria should be used to assess the reliability of a source?How much evidence is sufficient in order to support a conclusion?How much about various people, places, events, or developments can be known and how much is unknowable?Sample activities:Compare and contrast multiple accounts of the same event and evaluate their usefulness as historical sources.Examine what sources are available and what sources are missing and evaluate how the available evidence shapes our perspective on the people, places, events, or developments studied. |
|
| Curricular Competency |
Assess the significance of people, locations, events, and developments, and compare varying perspectives on their historical significance at particular times and places, and from group to group (significance) |
20th Century World History 12 |
No CCG |
| Keyword: Assess the significance of people, locations, events, and developments, and compare varying perspectives on their historical significance at particular times and places, and from group to group |
Elaboration: Key questions:What factors can cause people, places, events, or developments to become more or less significant?What factors can make people, places, events, or developments significant to different people?What criteria should be used to assess the significance of people, places, events, or developments?Sample activities:Use criteria to rank the most important people, places, events, or developments in their current unit of study.Compare how different groups assess the significance of people, places, events, or developments. |
|
| Curricular Competency |
Use historical inquiry processes and skills to ask questions; gather, interpret, and analyze ideas; and communicate findings and decisions |
20th Century World History 12 |
No CCG |
| Keyword: Use historical inquiry processes and skills to ask questions; gather, interpret, and analyze ideas; and communicate findings and decisions |
Elaboration: Key skills:Draw conclusions about a problem, an issue, or a topic.Assess and defend a variety of positions on a problem, an issue, or a topic.Demonstrate leadership by planning, implementing, and assessing strategies to address a problem or an issue.Identify and clarify a problem or issue.Evaluate and organize collected data (e.g., in outlines, summaries, notes, timelines, charts).Interpret information and data from a variety of maps, graphs, and tables.Interpret and present data in a variety of forms (e.g., oral, written, and graphic).Accurately cite sources.Construct graphs, tables, and maps to communicate ideas and information, demonstrating appropriate use of grids, scales, legends, and contours. |
|
| Big Ideas |
Statistical findings gain value through effective communication. |
Statistics 12 |
No CCG |
| Keyword: effective communication |
Elaboration: Sample questions to support inquiry with students:Why is the communication of statistical findings important?How can we best communicate statistical findings verbally and in writing?What are the roles of context and the target audience in the communication of statistical findings?How can technology assist us in the communication of statistical ideas? |
|
| Big Ideas |
We can develop statistical thinking to help make inferences intuitive. |
Statistics 12 |
No CCG |
| Keyword: statistical thinking |
Elaboration: Sample questions to support inquiry with students:How can we explore the sampling distribution of a statistic?What properties of a sample statistic make it a good estimator of a population parameter?How can technology help us appreciate the properties of a confidence interval?How surprising are the data from a study if the research hypothesis is true? |
|
| Big Ideas |
Statistical analysis allows us to explore, describe, model, and explain variation. |
Statistics 12 |
No CCG |
| Keyword: Statistical analysis |
Elaboration: Sample questions to support inquiry with students:Why is it important to explore and understand variation?How can we describe variation graphically?What is the role of probabilistic models for describing variation?Can we describe the sampling variation of a statistic, such as the sample mean? |
|
| Big Ideas |
The research question and practical and ethical issues determine whether a statistical study should be observational or experimental. |
Statistics 12 |
No CCG |
| Keyword: statistical study |
Elaboration: Sample questions to support inquiry with students:How do studies obtaining data enable us to explore research questions?What features of a study will make it effective, practical, and ethical for exploring a research question?How do we conduct an effective observational study?How do we conduct an effective designed experiment? |
|
| Big Ideas |
Statistics plays an integral role in research, decision making, and policy in society. |
Statistics 12 |
No CCG |
| Keyword: Statistics |
Elaboration: Sample questions to support inquiry with students:Why is statistical thinking important in our lives?How do the statistical sciences help us make decisions?What is the role of statistics in the scientific process? |
|
| Content |
communication of statistical findings |
Statistics 12 |
No CCG |
| Keyword: communication |
Elaboration: communicating statistical findings in context, appropriate to the target audiencewriting a report on a research project involving an observational studywriting a report on a research project involving a designed experimentpresenting to an audience on a research project involving an observational studypresenting to an audience on a research project involving a designed experiment |
|
| Content |
use of software and technology to enhance statistical ideas |
Statistics 12 |
No CCG |
| Keyword: software and technology |
Elaboration: Software can assist us in exploring and summarizing data.Online simulation-based learning tools can help us gain intuition of inferential concepts, such as sampling distribution, interval estimation, and hypothesis tests. |
|
| Content |
intuition and appreciation of inferential concepts, such as confidence intervals and hypothesis tests |
Statistics 12 |
No CCG |
| Keyword: inferential concepts |
Elaboration: making intuitive inferences based on a large number of simulationsintuition on interval, estimation of means and proportions via simulationinference for proportion via simulation (randomization/permutation tests)inference for a mean via simulation (randomization/permutation tests)two-sample questions via simulation (randomization/permutation tests) |
|
| Content |
probability models for variation |
Statistics 12 |
No CCG |
| Keyword: models |
Elaboration: binomial distribution:When is it appropriate?What does it model?What assumptions can be made?Shape of distribution affected by n and p.normal (Gaussian) distribution:when it is usefulroles of the mean and standard deviation, 68-95-99.7 rulecentral limit theorem: describing the variation of a sample meanuse of simulation software to explore sampling distributions |
|
| Content |
association between two variables |
Statistics 12 |
No CCG |
| Keyword: association |
Elaboration: categorical variables: contingency tables — clustered, stacked bar chartsquantitative variables: scatterplotscorrelation and causation |
|
| Content |
use of summary statistics to describe variation |
Statistics 12 |
No CCG |
| Keyword: summary statistics |
Elaboration: measures of centre, spread (range, variance, standard deviation interquartile range), including five-number summaryuse of Chebyshev’s inequalityuse of correlation in measuring association between quantitative variables |
|
| Content |
common graphical representations of variation |
Statistics 12 |
No CCG |
| Keyword: graphical |
Elaboration: Graphical methods should always be used to explore data.Graphical approaches can display data distributions.Focus on interpreting data through bar charts, histograms, dot plots, boxplots, scatterplots, tables.Graphical approaches can be used to explore the association between variables (e.g., clustered bar charts, scatterplots).Software should be used (e.g., Minitab).What are the advantages and disadvantages of different representations? |
|