Interpret a scatter plot by identifying clusters and outliers
In this lesson you will learn how to interpret a scatter plot by identifying clusters and outliers.
ADDITIONAL MATERIALS
Lesson slides [ Ссылка ]
STANDARDS
VA.PS.8.13.b make observations about data represented in scatterplots; and
VA.DS.PS.4 The student will analyze scatterplots to identify and describe the relationship between two variables, using shape; strength of relationship; clusters; positive, negative, or no association; outliers; and influential points.
VA.PS.8.13.a represent data in scatterplots;
CCSS.8.SP.A.1 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.
FL.MAFS.8.SP.1.1 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.
IN.AI.DS.2 Graph bivariate data on a scatter plot and describe the relationship between the variables.
IN.8.DSP.1 Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantitative variables. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
TEKS.S.7.A analyze scatterplots for patterns, linearity, outliers, and influential points;
TEKS.8.5.D use a trend line that approximates the linear relationship between bivariate sets of data to make predictions;
TEKS.8.11.A construct a scatterplot and describe the observed data to address questions of association such as linear, non-linear, and no association between bivariate data;
TEKS.5.9.B represent discrete paired data on a scatterplot; and
