Exploring Linear Regression with Calculators

This video tutorial by Kirk Weiler covers linear regression using a calculator. It begins with an introduction to the lesson and available resources. The tutorial then guides viewers through setting up a calculator to enter data and create a scatterplot. It explains how to find the line of best fit and interpret the model's y-intercept and slope. An exercise on car weight and mileage is used to apply these concepts. The lesson concludes with a summary of key points.

What is the main topic of this lesson?

• Probability and Statistics

• Linear Regression on the Calculator

• Quadratic Equations

• Geometry

Tags

CCSS.HSS.ID.B.6A

Where can you find the worksheet and homework assignment for this lesson?

• In the video description or on the website

• In the textbook

• In the library

• In the classroom

What should you do if there is data in L1 or L2 before entering new data?

• Delete the data

• Ignore the data

• Clear the data

• Save the data

Which button do you press to access the stat plot feature on the calculator?

• Mode

• 2nd and Y=

• Graph

• Y=

What is the purpose of setting the window size appropriately when creating a scatterplot?

• To make the data look smaller

• To ensure the data takes up the majority of the screen

• To hide some data points

• To change the data values

Tags

CCSS.HSN.Q.A.1

What does the slope of the line of best fit represent in the context of low and high temperatures?

• The rate at which high temperature increases with low temperature

• The sum of all temperatures

• The average temperature

• The difference between the highest and lowest temperatures

Tags

CCSS.8.EE.B.5

What does a negative correlation between car weight and mileage indicate?

• As car weight increases, mileage increases

• Car weight and mileage are unrelated

• Car weight and mileage both decrease

• As car weight increases, mileage decreases

Tags

CCSS.HSS.ID.B.5

Which parameter of the linear model indicates whether the correlation is positive or negative?

• X-intercept

• Correlation coefficient

• Slope

• Y-intercept

Tags

CCSS.HSF-LE.A.1B

If a car weighs 4.3 thousand pounds, what is its predicted fuel efficiency according to the model?

• 33 miles per gallon

• 40 miles per gallon

• 26 miles per gallon

• 24 miles per gallon

Tags

CCSS.HSF.LE.B.5

If a car gets 40 miles per gallon, what is its approximate weight according to the model?

• 3,000 pounds

• 3,500 pounds

• 4,000 pounds

• 4,500 pounds