Solve Cubic Regression Equation for US Limousine Production

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In summary, the graphing utility found a cubic regression equation for the data. However, the user forgot how to make the equation appear in the y equals screen so they could see the graph.
  • #1
undrcvrbro
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Cubic Regression

Homework Statement


(I was given a graph to enter into my calculator):

Let x represent time(in years) since 1980, and let y represent the corresponding U.S production of limousines. Enter the data in a graphing utility and find a cubic regression equation for the data.

Homework Equations


Calculator steps
Stat ---> Calc --->CubicReg... now what

The Attempt at a Solution


I have found the Cubic Regression equation but have forgotten how to make the equation itself appear in the y equals screen so that I can see the graph. I need that to answer the next part of the question.

I believe it should look something like this, but I'm not sure exactly how:

CubicReg L1,Y1,L2

Any help is greatly appreciated!
 
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  • #2
What kind of calculator do you have?
 
  • #3
calculator

im using a TI-83 Plus
 
  • #4
I have a TI-89, but this .pdf file may help you out.

http://academic.pg.cc.md.us/psc/TI83_booklet.pdf

Page 5 tells you how to enter data in list form. In your case, list 1 would be x = years since 1980 = 0, 1, 2, 3, ...
List 2 would be y variables and the entries would be the number of limousines that correspond to the year in the x column. Ex. In year 1980 (x=0), y = 100000 limousines
were produced.

Page 6-7 tell you how to select cubic regression from the STAT menu and enter the lists (L1, L2) that you want to analyze.

I wish I knew more about the TI-83, but hopefully you can find enough info in the pdf to do the problem.
 
  • #5
thank you

thank you very much, I'm sure that will help. I'll go go check it out right now.
 
  • #6
Thank You

THANK YOU! You area lifesaver, thank you for taking a little bit of time out of your day to save my whole night!
 

FAQ: Solve Cubic Regression Equation for US Limousine Production

What is a cubic regression equation?

A cubic regression equation is a mathematical formula used to model the relationship between a dependent variable and one or more independent variables. It is a type of polynomial regression that involves fitting a curve to a set of data points in order to make predictions or understand the underlying trend of the data.

How is a cubic regression equation used to solve for US limousine production?

A cubic regression equation can be used to analyze the relationship between the independent variable (e.g. time) and the dependent variable (e.g. US limousine production). By fitting a cubic regression curve to historical data, we can make predictions about future production levels and identify any underlying trends or patterns.

What factors are included in a cubic regression equation for US limousine production?

A cubic regression equation for US limousine production would typically include time as the independent variable and production levels as the dependent variable. Other factors that may be included could be economic indicators, such as inflation or consumer spending, that may impact the demand for limousines.

How accurate are predictions made using a cubic regression equation for US limousine production?

The accuracy of predictions made using a cubic regression equation for US limousine production will depend on the quality and size of the data set, as well as the stability of the underlying trend. It is important to regularly update the model with new data and reassess its accuracy.

Can a cubic regression equation be used to analyze other industries or products?

Yes, a cubic regression equation can be used to analyze the relationship between variables in any industry or product. However, it is important to consider the unique factors and variables that may be relevant to each specific case and adjust the model accordingly.

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