Graphing Lines of Best Fit Linear regression

1. Graphing(Lines of Best Fit � Linear regression) To ensure that scientific results are communicated effectively, many scientists and mathematicians rely on data tables and graphing.

2. This experience�. We are going to practice graphing and create our own protocols on how to communicate our results mathematically. We will calculate the lines of best fit then use this to make predictions based upon the data collected and observed.

3. We will use data collected from a science experiment for our example. We will be reviewing an experiment on plant growth and the effects of fertilizer. Remember that a good experiment has some important features:

4. 1.) What question(s) are we trying to answer? Do plants actually grow better using �Grow Good� fertilizer?

5. 2.) What background information is available? The manufacturers of �Grow Good� fertilizer claim that plants will grow better, taller, and healthier using the treatment.

6. 3.) What is the hypothesis? If tomato plants are treated with �Grow Good� fertilizer, then they will grow taller than those that will that are not fertilized.

7. 4.) What are the steps (procedure) used? The investigator planted 12 tomato plants in each of two seedling trays. One tray was watered using only well water with no additives. This serves as our control. The control is used for purpose of comparison.

8. The second tray was watered using well water with the recommended solution of �Grow Good� fertilizer. This is the experimental set up as it contains the factor (fertilizer) that we wish to test. The height of the seedlings in each tray was measured each week in centimeters, averaged and recorded in the data tables.

9. The data table is below:

10. To analyze the data we will present it as a graph. We will be making a graph with two lines, one for the control and the other line for the experimental set up. The graph will be drawn in the first quadrant since all the numbers represented are positive. Let�s review the steps you will use to make your graph.

11. Label the x and y axis including units used.

12. Remember: The x-axis should always represent the independent variable of your experiment. The dependent variable (the y-axis) is the result of the experiment. (It depends on the independent.)

13. Questions: Which of the two variables in the previous experiment is your independent? Which is your dependent?

14. Assigning values: Remember you should always use most of the space provided to make an easily read graph. The spacing of the intervals within each axis should be the same.

15. Determine appropriate intervals and label accordingly.

16. Insert a dot for each point given for the control tomato plants. Connect the points using the color blue.

17. Insert a dot for each point given for the experimental tomato plants. Connect using the color green.

18. Now focus on your control line (blue)�.�eyeing� the points, draw (in black) the line that would �best� represent the data. How could you generate an equation for this line WITHOUT a graphing calculator?

19. Now do the same with the green line (experimental). Using the lines you have created, what are your predictions for heights for week seven for each?

20. Finally�.. Use the worksheet provided to create your graph (please color code each) and what you have learned with your graphing calculator to generate a linear regression for each. Answer all questions and summarize. (Be specific and complete.)