In this unit, students will apply statistics, graphical interpretation and representation to the areas of economics, environment, and population. The topics of economics, environment, and population will each be researched and analyzed on a macroscopic scale (global, continental, or national) and a more local scale (back yard, neighborhood, city, county, state, New England). Students will achieve understanding of the statistical skills and concepts through the exploration of these topics. By the end of this unit, students should be able to demonstrate familiarity with the following concepts, and mastery of the following skills:
Statistical and Graphical Topics
Descriptive Statistics
Students will classify data as nominal, ordinal, interval, or ratio (including units of measurement), classify data sets (from tables or graphics) as univariate or bivariate. Students will summarize univariate data sets with measures of center, variation, and position, including median, mean, mode, range, interquartile range, standard deviation, variance, and quartiles. Also, students will describe the effect of an outlier on the measures of center, and interpret graphical displays of data using center, spread, clusters, gaps, outliers, and other unusual features and shapes.
Graphics
Students will construct graphical displays of univariate and bivariate data, including dotplots, histograms, cumulative frequency plots, stem and leaf plots, box plots, scatter plots, bar charts, pie charts, frequency tables and distributions, and ogive (continuous cumulative frequency graph or curve). Students will use scatter plots to estimate a least-squares regression line. Also, students will choose an appropriate form of data display given a data set. Students will compare clusters, gaps, outliers, unusual features, shapes of distributions, and compare distributions using various data representations. Finally, students will describe, analyze, and interpret frequency distributions, and describe properties of a normal distribution.
Analysis of Bivariate Data
Students will choose and acquire linear or nonlinear bivariate data to represent graphically in both time series and scatter plots. They will explore correlation and regression graphically and algebraically. Finally, students will interpolate from and extrapolate on (linearized) bivariate data sets using regression equations.
