Learning to read, construct, interpret and evaluate tables, graphs and charts.
We will introduce the students to the use of matlab/octave and other tools to show them how to create and interpret information rich visual representations of real-life data sets.
Developing quantitative measures of physical, behavioral or social phenomena.
We will look closely and several large studies and discuss their choice of quantitative measures. We will also engage in some experimental design creating our own quantitative measures.
Using mathematical models to express causal relationships and to explore the implications of changed assumptions or proposed solutions to problems in the physical or social world.
We will use curve fitting and other data analysis tools to make predictions based on historical data. We will also look into creating predictive models based on longitudinal survey data (e.g. NLSY97)
Collecting and organizing numerical data from archives, surveys, lab experiments or other sources.
We will engage in some construction and analysis of surveys.
Testing hypotheses using experimental or statistical controls.
We will design some simple educational experiments using appropriate controls.
Assessing the limitations of research, such as the reliability and validity of measures, adequacy of experimental design, sample size and quality and alternative hypotheses and interpretations.
We will begin to explore the qualitative measures of a reliable experimental protocol.