Math 143 Week 2 Desmos 2022 Activity Worksheet Roberto Jones

.pdf

School

Boise State University *

*We aren’t endorsed by this school

Course

143

Subject

Mathematics

Date

Apr 3, 2024

Type

pdf

Pages

2

Uploaded by AgentCrownDove34

Report
M143 Week 2 Worksheet Math 143 Week 2 Activity Worksheet Linear Regressions Directions: These activity questions are written to follow the Desmos activity for the week. Once you have completed the weekly activity you will be able to answer these questions. You can complete the questions on any document and then hand in the document on Canvas. 1. In your own words define a regression. Is a set of statistics that help to determine a model for predicting or estimating using a set of variables. 2. Why would you use a regression? When you want to study the relationship between 2 variables, relate them or even correlate them. 3. What is the domain of a data set? Explain. Is the area of pre-defined values that you will use in a lot of cases. 4. What is the range in a set of linear data? Explain. The difference between the largest and smallest numbers. 5. How many hours per week do you need to spend actively working on Aleks? At least 5 hours per week. 6. Given the data set {(2, 3), (3, 4.2), (4, 7), (5, 9), (11, 10.89)}
M143 Week 2 Worksheet a) Describe the data set. Does it look linear? Does it slope up to the right? Does it slope down to the right? List any characteristics that you see. It looks linear. b) Create a scatterplot on Desmos using the data set above. Sketch the scatterplot below. c) What window did you use for the data set in Desmos? Explain why you chose this window. Make sure to connect the window on Desmos to the domain and range of the data set. I created a table and input the data to plot the graph with the given data set. d) Using Desmos, calculate the linear regression that best fits your data. Write the equation below. I used the equation y1 ~ mx1 + b e) Could you have created a linear regression by hand? Explain. I could possibly create an approximate linear regression by hand but it not be super accurate.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
  • Access to all documents
  • Unlimited textbook solutions
  • 24/7 expert homework help