March 13 and Beyond

Check in on Lauren Stout's website for information. :-)

Day 9 and 10 - March 6 and 8

Presentation of Linear Regression Projects

Day 8 - March 1

Learning Target

Explain why data may need to be transformed and some possible transformations

Class Agenda

Video - "Transforming nonlinear data: steps and examples"

Discuss "Residual Plot"

Video -


 Project ready for presentation: DUE March 6

Project submitted on paper or electronically by March 8

Day 7 - February 27

Learning Target

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

Class Agenda

Video - "Interpreting Linear Relationships Using Data"

Practice finding and interpreting

-linear regression equation



-extrapolating points

-coefficient of determination

correlation coefficient

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

Learning Target

Explain the meaning of a specific Coefficient of Determination

Explain the difference between Correlation Coefficient and Coefficient of Determination

Class Agenda

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) 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

Learning Target

Explain the meaning of a given correlation coefficient

Explain the difference between correlation and causation

Class Agenda

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

Learning Target

Calculate and interpret the correlation coefficient

Class Agenda

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

Learning Target

Find simple regression line using Least Squares Formulas

Analyze residuals to see if they satisfy the 4 conditions for linear regression analysis

Class Agenda

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

Learning Target

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

Class Agenda

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

Learning Target

Describe the correlation between the two variables as strong/weak and positive/negative

Class Agenda

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