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Teaching
Core Teaching Commitments
Courses
STA215
Linear Regression
LR-A1: Intro to Linear Regression
LR-A2:Predicted Equation
LR-A3: Least Squared Errors
LR-A4: Interpreting Coefficients
LR-A5: Interpreting Significance (and insignificance)
LR-A6: Interpreting the Intercept
LR-A8: Interpreting Coefficients for Quantitative IVs
LR-A9: Interpreting Coefficients for Qualitative IVs
LR-A10: Interpreting R2
LR-A11: Residual Plots
LR-A12: Linear Relationship
LR-B1-Residual vs Error
LR-B2-Calculating Predicted Values and Residuals
LR-B3-Interpreting predictions + residuals
LR-B4-Covariance
LR-B5-Interpret Units
LR-B6-Qualitative IV with more than two categories
LR-B7-calculating difference categories not reference
LR-B8-Substantive intercepts
LR-B9-Significance using confidence intervals
LR-B10-Standardized Quantitative Independent Variables
LR-B11-Standardizing with Qualitative IV
LR-B12-Assumptions and Conditions
LR-B13-Relationship as Modeled, Not Observed
LR-C1-calculating coefficients
LR-C2-Effect of Outliers
LR-C3-Root Mean Square Error
LR-C4-Squared Error Regression Line
LR-C5-Inferences in Regression
LR-C6-Calculating T-Statistic
LR-C7-Calculating Confidence Intervals of the Slops
LR-C8-Fitting non-linear Relationships
LR-C9-Interpreting non-linear regressions
LR-C10-Polynomials
LR-C11-Log-linear Model
LR-C12-Using Residual Plots to Assess Assumptions
Research
Major Projects
Peer-Reviewed Publications
C.V.
Home
Teaching
Core Teaching Commitments
Courses
STA215
Linear Regression
LR-A1: Intro to Linear Regression
LR-A2:Predicted Equation
LR-A3: Least Squared Errors
LR-A4: Interpreting Coefficients
LR-A5: Interpreting Significance (and insignificance)
LR-A6: Interpreting the Intercept
LR-A8: Interpreting Coefficients for Quantitative IVs
LR-A9: Interpreting Coefficients for Qualitative IVs
LR-A10: Interpreting R2
LR-A11: Residual Plots
LR-A12: Linear Relationship
LR-B1-Residual vs Error
LR-B2-Calculating Predicted Values and Residuals
LR-B3-Interpreting predictions + residuals
LR-B4-Covariance
LR-B5-Interpret Units
LR-B6-Qualitative IV with more than two categories
LR-B7-calculating difference categories not reference
LR-B8-Substantive intercepts
LR-B9-Significance using confidence intervals
LR-B10-Standardized Quantitative Independent Variables
LR-B11-Standardizing with Qualitative IV
LR-B12-Assumptions and Conditions
LR-B13-Relationship as Modeled, Not Observed
LR-C1-calculating coefficients
LR-C2-Effect of Outliers
LR-C3-Root Mean Square Error
LR-C4-Squared Error Regression Line
LR-C5-Inferences in Regression
LR-C6-Calculating T-Statistic
LR-C7-Calculating Confidence Intervals of the Slops
LR-C8-Fitting non-linear Relationships
LR-C9-Interpreting non-linear regressions
LR-C10-Polynomials
LR-C11-Log-linear Model
LR-C12-Using Residual Plots to Assess Assumptions
Research
Major Projects
Peer-Reviewed Publications
C.V.
More
Home
Teaching
Core Teaching Commitments
Courses
STA215
Linear Regression
LR-A1: Intro to Linear Regression
LR-A2:Predicted Equation
LR-A3: Least Squared Errors
LR-A4: Interpreting Coefficients
LR-A5: Interpreting Significance (and insignificance)
LR-A6: Interpreting the Intercept
LR-A8: Interpreting Coefficients for Quantitative IVs
LR-A9: Interpreting Coefficients for Qualitative IVs
LR-A10: Interpreting R2
LR-A11: Residual Plots
LR-A12: Linear Relationship
LR-B1-Residual vs Error
LR-B2-Calculating Predicted Values and Residuals
LR-B3-Interpreting predictions + residuals
LR-B4-Covariance
LR-B5-Interpret Units
LR-B6-Qualitative IV with more than two categories
LR-B7-calculating difference categories not reference
LR-B8-Substantive intercepts
LR-B9-Significance using confidence intervals
LR-B10-Standardized Quantitative Independent Variables
LR-B11-Standardizing with Qualitative IV
LR-B12-Assumptions and Conditions
LR-B13-Relationship as Modeled, Not Observed
LR-C1-calculating coefficients
LR-C2-Effect of Outliers
LR-C3-Root Mean Square Error
LR-C4-Squared Error Regression Line
LR-C5-Inferences in Regression
LR-C6-Calculating T-Statistic
LR-C7-Calculating Confidence Intervals of the Slops
LR-C8-Fitting non-linear Relationships
LR-C9-Interpreting non-linear regressions
LR-C10-Polynomials
LR-C11-Log-linear Model
LR-C12-Using Residual Plots to Assess Assumptions
Research
Major Projects
Peer-Reviewed Publications
C.V.
C.V.
Kline(2022_9_19)CV_website.pdf
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Kline(2022_9_19)CV_website.pdfKline(2022_9_19)CV_website.pdfKline(2022_9_19)CV_website.pdf