Changing Effects

Changing Effects

CRA Description : 
Students work in small groups to create a scenario in which the standard (or metric) units must be converted to a newly invented system of measurement that students create. Students then collect data from an online source (e.g., weatherchannel.com) that applies to the scenario, and convert the data to their new system of measurement. Students conduct a statistical analysis on the converted data, and then conduct the same statistical analysis on the original data set. Finally, students interpret and compare statistical results based on data using different units of measure, and consider the implications for science conducted globally.
Subjects: 
Mathematics
Algebra II
Mathematical Models with Applications
Key Concepts and Terms: 
Boxplot
Confounding Variables (or Lurking Variables)
Correlation
Correlation Coefficient
Dotplot
Experimental Studies
Histogram
Inter-quartile Range
Least-Squares Regression Equation
Location Statistics
Mean
Metric Units
Min/Max (Lower and Upper Quartiles, Median)
Observational Studies
Scatterplot
Slope
Standard Deviation
Standard Units
Statistical Conclusion
Unit Conversions
Univariate and Bivariate Quantitiative Data
Variation Statistics
Z-score
Prior Knowledge: 
Fathom, Excel, or a similar program that will allow them to manage and analyze data, and present it in graphic form. The difference between the metric and standard systems of measurement, the origins of each and where they are used, and conversion between and within measurements systems. Computing the mean, median, lower and upper quartiles, range, standard deviation, inter-quartile range (IQR), and z-scores for a given data set. Creating a scatterplot for paired data and determining the least-squares regression line and correlation coefficient. Selecting the appropriate measure of central tendency or range to describe a set of data and justify the choice for a situation. Drawing conclusions and making predictions by analyzing trends in scatterplots. Selecting and using an appropriate representation for presenting and displaying relationships among collected data, including line plots, line graphs, stem and leaf plots, circle graphs, bar graphs, box and whisker plots, histograms, and Venn diagrams, with and without the use of technology. Evaluating methods of sampling to determine validity of an inference made from a set of data. Recognizing misuses of graphical or numerical information, and evaluating predictions and conclusions based on data analysis.