Create a Scatterplot with 2 Variables

Create a Scatterplot with 3 Variables

Create Comparative Scatterplots

Find a Point on a Scatterplot

Find Coordinating Values Between Scatterplots

Add the Line y=x

Draw an Ellipse Around Our Data

Find the minimum and maximum x & y value

Comparison of Domain and Range with y=x

Compare Scatterplots via Associations

Describing Non-Linear Associations

Describing Direction as a Direct or Inverse Relationship Between x & y

Describing a Scatterplot using FUDS, without r

Interpreting No Association Scatterplots (Round and Flat)

Scatterplots with Sub-Domains of Association

Rectangular vs. Square Data

Guessing the Association From Context

Calculate the Correlation Coefficient

Interpreting the Sign of Correlation (+/-) as Direct or Inverse

Selecting a Scatterplot with a given r Close to 0

Selecting a Scatterplot with a Given r Close to (+/- 1)

Comparing and Selecting Correlation Coefficients (r)

r Can Be Misleading

Correlation Mistakes (r has no units)

Correlation Mistakes (r is not affected by Most Linear Transformations)

Interpreting a Correlation Coefficient of r = 0

Determining Whether Variables are Explanatory or Response

Interpreting Slope (b1) in Context

Interpreting y-Intercept (bo) in Context

Write the LSRL Model from Regression Output

Find the LSRL Model From a Data Set

Given x and a Linear Model, Find Predicted y

Find the Difference of 2 Predicted y's Given 2 x values and a Linear Model

Draw a Linear Model

Draw a Linear Model Using a Broken Axis

Given the Increase in x, Find the Change in Predicted y

Find a Model by Regressing to the Mean

Find Slope or y-Intercept by Regressing to the Mean

Find Mean, Standard Deviation, or r by Regressing to the Mean

Calculate the Correlation Coefficient (r) from r^2

Calculate the Correlation Coefficient (r) from r^2 and Regression Output

Identify the Standard Error of the y-Intercept from Regression Output

Identify the Standard Error of the Slope from Regression Output

Compare Characteristics of 2 LSRL Models

Define Linear as a Model of Constant Change

Calculate Coefficient of Determination (r^2) given r

Calculate Coefficient of Dataset

Finding Corresponding Points Between Scatterplot and Residual Plot

Residuals Expressed as a Vertical Distance, Graphically or in Context

Given Actual y, Predicted y, e, and/or Model, Calculate x-value

Given x, Predicted y, e, and/or Model, Calculate Actual y

Given Actual y and e, Calculate Predicted y (y-hat)

Given x, Actual y, Predicted y, and/or Model, Calculate the Residual (e)

Calculate and/or Interpret Standard Deviation of Residuals (Se)

Calculate Residual Sums (SE, SSE)

LSRL and Rules of Residual Sums

Under- vs. Over-Predictions (+/- e)

Interpreting Association as a Difference Between Actual and Predicted y

Compare Residuals, Residual Sums, or Residual Plots

Interpreting Residuals, in Context, for Appropriateness of a Linear Model

Interpreting Resid Plots for Appropriateness of a Linear Model

Interpreting Resid Plots for Non-Appropriateness of Linear Model

Calculate the Coefficient of Determination (r^2) with Interpretation

Identify a Leverage Point from a Scatterplot

Defining Leverage Points and Affects on the LSRL

Identify an Influential Point from a Scatterplot

Defining Influential Points and Affects on LSRL

Identify an Outlier from a Scatterplot

Defining Outliers and Affects on LSRL

Scatterplots with Sub-Domains of Association

FUDS of a Subset on a Scatterplot

Compare Medians of Subsets

Simpson's Paradox: Subsets and Direction

Breaking into Subsets for Varying Purposes

Models Don't Work Under Extrapolation

Lurking Variables Beware

Non-Meaningful y-intercept (bo) in Context