Day 9 and 10 - March 6 and 8
Presentation of Linear Regression Projects
Day 8 - March 1
Explain why data may need to be transformed and some possible transformations
Video - "Transforming nonlinear data: steps and examples"
Discuss "Residual Plot"
Project ready for presentation: DUE March 6
Project submitted on paper or electronically by March 8
Day 7 - February 27
Explain the meaning of a and b for a line of regression given the context
Extrapolate the line to make predictions for data points beyond the given set of data
Video - "Interpreting Linear Relationships Using Data"
Practice finding and interpreting
-linear regression equation
-coefficient of determination
4 tests for validity of linear model
Regression line equation, correlation coefficient and coefficient of determination for your project. DUE March 1
Day 6 -February 22
Explain the meaning of a specific Coefficient of Determination
Explain the difference between Correlation Coefficient and Coefficient of Determination
Formative Assessment - "Scatterplots and Lines of Best Fit" (a copy can be found under the documents tab)
Linear Regression Project (Copies of this document can be found under the documents tab)
Study.com video - "Coefficient of Determination: definition, formula, example"
Correlation Coefficient and Coefficient of Determination explained:
Practice finding and interpreting Coefficient of Determination AND Correlation Coefficient using death rate data
Scatterplot and data table for project, DUE Monday February 27
Day 5-February 15
Explain the meaning of a given correlation coefficient
Explain the difference between correlation and causation
Video- "How to interpret correlations in research results" Minute 8:17 on
Video "The correlation coefficient: Practice problems"
Work through examples
Day 4 - February 13
Calculate and interpret the correlation coefficient
Reviewed and practiced Least Squares Formula
Video -"The Correlation Coefficient: definition, formula and example"
Complete practice problems from video
Practice more with death rate data
Find correlation coefficient for hydrocarbons, nitrogen and household size from the death rate data
Day 3 - February 8
Find simple regression line using Least Squares Formulas
Analyze residuals to see if they satisfy the 4 conditions for linear regression analysis
Video - "Problem solving using linear regression: steps and examples"
Using Jakes data from the video, calculate slope and y-intercept using Least Squares formula
Video - "Analyzing residuals"
Discuss 4 conditions for Linear Regression Analysis to be valid: Statistical independence, linearity, homoscedasticity and normality
Death Rate data sheet
Day 2 - February 1
Find regression line 2 ways: draw line of best fit and write equation for line AND enter data into calculator and calculate regression line using LinReg function
Watch video "Simple linear regression: definition, formula,examples"
Practice graphing and writing equations and calculating regression equations, use Hannah's data from the video
graph and estimate regression line for Brain vs. Body or Per Capita data. Write equation for line of best fit. Compare your equation to calculator line using LinReg function.
Day 1 - January 30
Describe the correlation between the two variables as strong/weak and positive/negative
Vocabulary - scatterplot, bivariate data, correlation, independent variable, dependent variable
Video - "Creating and interpreting scatterplots"
Create scatter plots for Liam's data, then for brain vs. body size and look for correlations
Bring 5 ideas of variable that you are curious if they might have a correlation to the next class