S-ID. Interpreting Categorical and Quantitative Data

S-ID.A. Summarize, represent, and interpret data on a single count or measurement variable

• Accuracy of Carbon 14 Dating I

S-ID.A.1. Represent data with plots on the real number line (dot plots, histograms, and box plots).

• Haircut Costs
• Speed Trap

S-ID.A.2. 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.

• Haircut Costs
• Measuring Variability in a Data Set
• Speed Trap
• Understanding the Standard Deviation

S-ID.A.3. Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).

• Describing Data Sets with Outliers
• Haircut Costs
• Identifying Outliers
• Measuring Variability in a Data Set
• Speed Trap

S-ID.A.4. Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.

• Do You Fit In This Car?
• SAT Scores
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S-ID.B. Summarize, represent, and interpret data on two categorical and quantitative variables

S-ID.B.5. 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.

• Musical Preferences
• Support for a Longer School Day?

S-ID.B.6. Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

• Coffee and Crime
• Laptop Battery Charge 2
• Used Subaru Foresters I

S-ID.B.6.a. Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.

• Olympic Men's 100-meter dash

S-ID.B.6.b. Informally assess the fit of a function by plotting and analyzing residuals.

• Restaurant Bill and Party Size

S-ID.B.6.c. Fit a linear function for a scatter plot that suggests a linear association.

• No tasks yet illustrate this standard.

S-ID.C. Interpret linear models

S-ID.C.7. Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.

• Coffee and Crime
• Olympic Men's 100-meter dash
• Texting and Grades II
• Used Subaru Foresters II

S-ID.C.8. Compute (using technology) and interpret the correlation coefficient of a linear fit.

• Coffee and Crime

S-ID.C.9. Distinguish between correlation and causation.

• Coffee and Crime
• Golf and Divorce
• High blood pressure
• Math test grades