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In Algebra 1, students demonstrate fluency by creating, comparing, analyzing, solving, providing multiple representations, and identifying the structures of exponential & quadratic functions building on the understanding of linear functions from grade 8 to apply linear, quadratic and exponential models to data and unfamiliar problems.
Essential Standards
S-ID.B Claim 4 - Summarize, represent, and interpret data on two categorical and quantitative variables.
S-ID.B Claim 4 - Summarize, represent, and interpret data on two categorical and quantitative variables.
S-ID.B.6 Represent data on two quantitative variables on a scatter plot, and describe how the variables are related. Modeling Standard
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.
b. Informally assess the fit of a function by plotting and analyzing residuals.
c. Fit a linear function for a scatter plot that suggests a linear association.
Embed with S-ID.B.6, 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.
There are no substandards for this standard.
Embed with S-ID.B.6, S-ID.C.8 Compute (using technology) and interpret the correlation coefficient of a linear fit.
There are no substandards for this standard.
Embed with S-ID.B.6, S-ID.C.9 Distinguish between correlation and causation.
There are no substandards for this standard.
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. Modeling Standard
There are no substandards for this standard.
Achievement Level Descriptors & Evidence
Achievement Level Descriptors
Achievement Level Descriptors
Evidence
Evidence
Supporting Standards
Embed with S-ID.B.6, 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.
There are no substandards for this standard.
Embed with S-ID.B.6, S-ID.C.8 Compute (using technology) and interpret the correlation coefficient of a linear fit.
There are no substandards for this standard.
Embed with S-ID.B.6, S-ID.C.9 Distinguish between correlation and causation.
There are no substandards for this standard.
Related standard from Geometry (time permitting), S-CP.4 Construct and interpret two-way frequency tables of data when two categories are associated with each object being classified. Use the two-way table as a sample space to decide if events are independent and to approximate conditional probabilities. Modeling Standard
For example, collect data from a random sample of students in your school on their favorite subject among math, science, and English. Estimate the probability that a randomly selected student from your school will favor science given that the student is in tenth grade. Do the same for other subjects and compare the results.
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