I will be able to:
 Define terms like placebo effect, control group, experimental group, outliers, extraneous variables, independent, dependent variable, correlation coefficient, coefficient of determination,
line of best fit, and curve of best fit.
 Identify the independent and dependent variable for a set of two variable data.
 Create an appropriately labeled and scaled scatterplot for a set of two variable data.
 Classify a correlation by inspection of a scatterplot (weak, moderate, strong, positive or negative)
 Calculate the correlation coefficient for a data set and use it classify the strength of a correlation.
 Find the equation of the line of best fit for a set of data by hand.
 Use a linear or non-linear model to interpolate/extrapolate data points (non-linear model will be given not calculated)
 Match a scenario to a specific type of relationship – cause and effect, accidental/coincidental, reverse cause and effect, common cause, presumed relationship.
 Give examples of specific type of relationships as stated above.
 Explain how to determine the goodness of fit for a non-linear model with respect to the coefficient of determination and initial/final states.
 Explain how extraneous variables can be controlled and suggest ways to improve the research methods for a given scenario.
I will be able to:
 Define terms like placebo effect, control group, experimental group, outliers, extraneous variables, independent, dependent variable, correlation coefficient, coefficient of determination,
line of best fit, and curve of best fit.
 Identify the independent and dependent variable for a set of two variable data.
 Create an appropriately labeled and scaled scatterplot for a set of two variable data.
 Classify a correlation by inspection of a scatterplot (weak, moderate, strong, positive or negative)
 Calculate the correlation coefficient for a data set and use it classify the strength of a correlation.
 Find the equation of the line of best fit for a set of data by hand.
 Use a linear or non-linear model to interpolate/extrapolate data points (non-linear model will be given not calculated)
 Match a scenario to a specific type of relationship – cause and effect, accidental/coincidental, reverse cause and effect, common cause, presumed relationship.
 Give examples of specific type of relationships as stated above.
 Explain how to determine the goodness of fit for a non-linear model with respect to the coefficient of determination and initial/final states.
 Explain how extraneous variables can be controlled and suggest ways to improve the research methods for a given scenario.