Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Represent data with plots on the real number line (dot plots, histograms, and box plots).*
Degree of Alignment:
Not Rated
(0 users)
Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.*
Degree of Alignment:
Not Rated
(0 users)
Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).*
Degree of Alignment:
Not Rated
(0 users)
Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.*
Degree of Alignment:
Not Rated
(0 users)
Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.*
Degree of Alignment:
Not Rated
(0 users)
Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.*
Degree of Alignment:
Not Rated
(0 users)
Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Compute (using technology) and interpret the correlation coefficient of a linear fit.*
Degree of Alignment:
Not Rated
(0 users)
Learning Domain: Statistics and Probability: Interpreting Categorical and Quantitative Data
Standard: Distinguish between correlation and causation.*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Summarize, represent, and interpret data on a single count or measurement variable
Standard: Represent data with plots on the real number line (dot plots, histograms, and box plots).*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Summarize, represent, and interpret data on a single count or measurement variable
Standard: Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Summarize, represent, and interpret data on a single count or measurement variable
Standard: Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Summarize, represent, and interpret data on two categorical and quantitative variables
Standard: Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Summarize, represent, and interpret data on two categorical and quantitative variables
Standard: Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Interpret linear models
Standard: Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Interpret linear models
Standard: Compute (using technology) and interpret the correlation coefficient of a linear fit.*
Degree of Alignment:
Not Rated
(0 users)
Cluster: Interpret linear models
Standard: Distinguish between correlation and causation.*
Degree of Alignment:
Not Rated
(0 users)
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