Desmos Regression Techniques

This video tutorial introduces the use of regressions in Desmos, starting with importing data from Excel or Google Sheets. It demonstrates fitting a linear regression model and explores a parabolic model for better data fitting. The tutorial concludes with adding residuals to the data table and provides additional resources for further learning.

What is the first step before creating a regression in Desmos?

• Choosing a regression model

• Adjusting the window size

• Adding residuals

• Importing data

Which of the following is a source from which you can import data into Desmos?

• Word Document

• PowerPoint

• Excel

• PDF

What does Desmos do automatically after importing data?

• Deletes the previous data

• Adjusts the window to fit the data

• Changes the data format

• Saves the data

What is the purpose of adjusting the window in Desmos?

• To delete the data

• To change the data

• To save the data

• To fit the data

In a linear regression model in Desmos, what does the tilde symbol (~) represent?

• Regressed against

• Equals

• Repressed against

• Approximately

What is the formula used for a linear regression in Desmos?

• y1 = a x1² + b x1 + c

• y1 ~ a x1² + b x1 + c

• y1 = m x1 + b

• y1 ~ m x1 + b

What is the significance of the subscript in the regression formula?

• It indicates a constant

• It is used for decoration

• It represents a variable

• It denotes a specific data column

What is the purpose of using a parabolic regression model in Desmos?

• To find a better fit for the data

• To make calculations easier

• To reduce data size

• To simplify the data

Which of the following represents a parabolic regression model in Desmos?

• y1 ~ m x1 + b

• y1 = m x1 + b

• y1 ~ a x1² + b x1 + c

• y1 = a x1² + b x1 + c

What does the tutorial suggest if the linear model is not a good fit?

• Try a different data set

• Change the data format

• Adjust the window size

• Use a parabolic model