REGRESSION WORKSHEET:
Prof. Porter Mercer County College
REGRESSION PROJECT GRADE SHEET:
|1. Did the student show the material learned in this course can be useful in a topic that is relevant to the|1 |
|individual students? | |
|2. Is it cited if the source of the data is from the library or internet versus data that is collected in an|2 |
|experiment? | |
|3. Did the student identify the variables. |3 |
|4. Is the data given? |4 |
|5. Is the data plotted in an appropriate window? |5 |
|6. Did the student give at least 2 regressions like linear, quadratic, and exponential? |6 |
|7. Did the student give the equation and work for a first regression? |7 |
|8. Did the student give the equation and work for a second regression? |8 |
|9. On the same graph as the data, did the student graph the different regressions clearly? |9 |
|10. Did the student will decide if the regression is close to the data? R2 |10 |
|11. Did the student conclude anything? |11 |
|12 Was a prediction made? |12 |
|13. Was there a summary? |13 |
|14. Were two reviews written for other students? |14 |
|15. Were two reviews done by other students? (names listed only- not review) |15 |
|16. Was the project handed in on time? |16 |
TOTAL COMPLETED: ___________________________
GRADE(% out of 100): ___________________________
REGRESSION PROJECT WORKSHEET:
The purpose of this project is for the student to connect real data to material learned in this course. To this end, the student is expected to collect data on any topic that interests them and perform some calculus based calculations.
First the student should cited the source of the data. If it is from the library or internet versus give details, and if the data is collected in an experiment the details of the experiment should be explained clearly.
The student should then identify the variables and which would be considered independent (like time or price) and dependant (like absorption or sales).
I. Enter Data: (TI-83: Stat:1 Edit / TI-86 Stat F2:EDIT)
Let L1/x-stat represent your independent x- variable: ________________________,
Let L2/y-stat represent your dependant y-values:___________________________
Data:
L1/
xstat | | | | | | | | | | |L2/
ystat | | | | | | | | | | |
Next, I expect to see the data graphed in an appropriate window.
II. Plot Data: ( TI-83: 2nd y= gives stat plot Turn your plot on.
Again, let L1 be your x-values and L2 be your y-values.
To graph, you will likely have to adjust your window and graph.
zoom:9 zoomstat does it automatically when plots are on)
(TI-86: stat plots On
Again, let xstat be your x-values and ystat be your y-values.
To graph, you will likely have to adjust your window and graph.
Graph ZOOM zdata does it automatically when plots are on)
Once a graph is created, the student should try to imagine a number of possible regressions that would fit the data. More complicated regressions should be tried (like quadratic and exponential or any other that looks promising).
III. Calculate Regression: (stat > calc gives option)
Decide if you want a line, parabola, or higher powered polynomial
After you make the choice, you will have to enter the lists (2nd 1,2nd 2)
83:. LinReg L1,L2 or just LinReg
For a regression on L1 and L2
86: LinR xstat,ystat (use lists names to get xstat)
Copy down result as regression
On the same graph as the data, the student should graph the different regressions. Be sure it is clear which regression is which.
IV. Graph Regression: Enter equation into function part of calculator
(use Y= vars:5 statistics >>EQ:1 RegEq, then - gives more precision)
The regressions should be compared. The student will want to decide two things: 1) if the regression is close to the data (called correlation) and 2) is the regression a good model? (will it make good predictions). The students should then attempt to make a prediction using the regressions and compare the results.
V. Make a prediction: Need to evaluate the function at a particular value of x.
(Use tblset and table for a table of values…or use trace)
(if you use trace, you will have to change functions with an arrow up, and you may have to manually expand the window by changing xmin or xmax)
VI. Find Extrema/Describe the graph: Describe the graph using terms like increasing, decreasing, concave up, concave down, etc. Also identify roots and extrema.
VII. Summary: Assess the value of your prediction.
(note: data points may not agree with predictions with the same x value)
Is the function behaving as you would expect?
Is your prediction meaningful?
How is the conclusion useful?
VIII. REVIEW: You need to get at least two other students to review and comment on your work. You must also review at least two other projects and include the reviews on your project.
................
................
In order to avoid copyright disputes, this page is only a partial summary.
To fulfill the demand for quickly locating and searching documents.
It is intelligent file search solution for home and business.
Related searches
- simple linear regression test statistic
- regression coefficient significance
- linear regression coefficients significance
- regression equation calculator
- regression coefficient formula
- linear regression test statistic calculator
- significant test of regression coefficients
- linear regression without a calculator
- linear regression significance
- regression coefficient calculator
- regression coefficient excel
- regression model significance