Representing data on dot plots, histograms, box plots, scatter plots, and two-way tables. Investigating patterns of association in data and lines of best fit.
Mapped to CCSS Section# 6.SP.B.4, 6.SP.B.5a, 6.SP.B.5b, 8.SP.A.1, 8.SP.A.2, 8.SP.A.4
Display numerical data in plots on a number line, including dot plots, histograms, and box plots. Summarize numerical data sets in relation to their context. Reporting the number of observations. Describing the nature of the attribute under investigation, including how it was measured and its units of measurement. Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association. Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line. Understand that patterns of association can also be seen in bivariate categorical data by displaying frequencies and relative frequencies in a two-way table. Construct and interpret a two-way table summarizing data on two categorical variables collected from the same subjects. Use relative frequencies calculated for rows or columns to describe possible association between the two variables. For example, collect data from students in your class on whether or not they have a curfew on school nights and whether or not they have assigned chores at home. Is there evidence that those who have a curfew also tend to have chores?