UP:MA19.GDA.7
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
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.