MA19.GDA.7

Mathematics (2019) Grade(s): 09-12 - Geometry with Data Analysis

MA19.GDA.7
Use mathematical and statistical reasoning with quantitative data, both univariate data (set of values) and bivariate data (set of pairs of values) that suggest a linear association, in order to draw conclusions and assess risk.

Unpacked Content

Knowledge

Students know:

Patterns found on scatter plots of bivariate data.
Strategies for determining slope and intercepts of a linear model.
Strategies for informally fitting straight lines to bivariate data with a linear relationship.
Methods for finding the distance between two points on a coordinate plane and between a point and a line.

Skills

Students are able to:

Construct a scatter plot to represent a set of bivariate data.
Use mathematical vocabulary to describe and interpret patterns in bivariate data.
Use logical reasoning and appropriate strategies to draw a straight line to fit data that suggest a linear association.
Use mathematical vocabulary, logical reasoning, and closeness of data points to a line to judge the fit of the line to the data.
Find a central value using mean, median and mode.
Find how spread out the univariate data is using range, quartiles and standard deviation.
Make plots like Bar Graphs, Pie Charts and Histograms.

Understanding

Students understand that:

Using different representations and descriptors of a data set can be useful in seeing important features of the situation being investigated,
When visual examination of a scatter plot suggests a linear association in the data, fitting a straight line to the data can aid in interpretation and prediction.
Modeling bivariate data with scatter plots and fitting a straight line to the data can aid in interpretation of the data and predictions about unobserved data.
A set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape.
Using different representations and descriptors of a data set can be useful in seeing important features of the situation being investigated.
Statistical measures of center and variability that describe data sets can be used to compare data sets and answer questions.

Vocabulary

Mathematical reasoning
Statistical reasoning
Univariate data
bivariate data
quantitative data
linear association
Scatter plots
linear model
Slope
bar graphs, Pie graphs, Histograms
Mean, median, mode
Standard deviation

COS Examples

Example: Estimate the typical age at which a lung cancer patient is diagnosed, and estimate how the typical age differs depending on the number of cigarettes smoked per day.

Aligned Learning Resources

Modeling & Simulation: Nodes and Graphs

MA19.GDA.7 Use mathematical and statistical reasoning with quantitative data, both univariate data (set of values) and bivariate data (set of pairs of values) that suggest a linear association, in order to draw conclusions and assess risk.