Curve-fitting Project - Linear Model ***CHOOSE A TOPIC****SEE
BELOW
Instructions
For this assignment, collect data exhibiting a relatively linear
trend, find the line of best fit, plot the data and the line,
interpret the slope, and use the linear equation to make a
prediction. Also, find r2 (coefficient of determination) and r
(correlation coefficient). Discuss your findings. Your topic may be
that is related to sports, your work, a hobby, or something you
find interesting. If you choose, you may use the suggestions
described below.
A Linear Model Example and Technology Tips are provided in separate
documents.
MY TOPIC IS: The rising Homeless population of the United States
from 2010 to 2018. PLEASE CITE DATA SOURCES as well if
possible
Tasks for Linear Regression Model (LR)
(LR-1) Describe your topic, provide your data, and cite your
source. Collect at least 8 data points. Label appropriately.
(Highly recommended: Post this information in the Linear Model
Project discussion as well as in your completed project. Include a
brief informative description in the title of your posting. Each
student must use different data.)
The idea with the discussion posting is two-fold: (1) To share your
interesting project idea with your classmates, and (2) To give me a
chance to give you a brief thumbs-up or thumbs-down about your
proposed topic and data. Sometimes students get off on the wrong
foot or misunderstand the intent of the project, and your posting
provides an opportunity for some feedback. Remark: Students may
choose similar topics, but must have different data sets. For
example, several students may be interested in a particular Olympic
sport, and that is fine, but they must collect different data,
perhaps from different events or different gender.
(LR-2) Plot the points (x, y) to obtain a scatterplot. Use an
appropriate scale on the horizontal and vertical axes and be sure
to label carefully. Visually judge whether the data points exhibit
a relatively linear trend. (If so, proceed. If not, try a different
topic or data set.)
(LR-3) Find the line of best fit (regression line) and graph it on
the scatterplot. State the equation of the line.
(LR-4) State the slope of the line of best fit. Carefully interpret
the meaning of the slope in a sentence or two.
(LR-5) Find and state the value of r2, the coefficient of
determination, and r, the correlation coefficient. Discuss your
findings in a few sentences. Is r positive or negative? Why? Is a
line a good curve to fit to this data? Why or why not? Is the
linear relationship very strong, moderately strong, weak, or
nonexistent?
(LR-6) Choose a value of interest and use the line of best fit to
make an estimate or prediction. Show calculation work.
(LR-7) Write a brief narrative of a paragraph or two. Summarize
your findings and be sure to mention any aspect of the linear model
project (topic, data, scatterplot, line, r, or estimate, etc.) that
you found particularly important or interesting.
You may submit all of your project in one document or a combination
of documents, which may consist of word processing documents or
spreadsheets or scanned handwritten work, provided it is clearly
labeled where each task can be found. Be sure to include your name.
Projects are graded on the basis of completeness, correctness, ease
in locating all of the checklist items, and strength of the
narrative portions