Pendulum Lab. Working with Pendulums. What we are doing. Using the information that you have learned about energy and what you have already done with lab writeups Devise a procedure that looks at the variables that affect each of the following parts of pendulous motion Keep good notes!.By pules
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BADM 750 – Case Writeups Common Errors and Correction Strategies. Not reading the material fully or not reading and directly addressing all assigned material How does he know? (Very obvious and significant points are never discussed, while the paper rambles on obviously groping to fill space.)
Lab: Graphing Lab. Showing patterns & trends. Practice makes perfect !. 12. 10. 0. 4. 8. 2. 6. M. O. A. D. S. P. L. What foods do slugs like to eat?. Bar graph !. amount food eaten (g). Conclusion?. Slugs like apples best & dog food the least. food source. 12. 15. 18. 0.
Lab #2 Maze Lab. Problem. What variables can change the amount of time required to complete a maze?. Materials. Printed Maze. Procedure. Obtain a printed maze. Have your classmate time how long it takes to complete the maze. Record this time in the control section of chart.
Lab #2 Computer Lab. Jason Brown Kevin Keating 04/23/2013. Lab #2- Computer Lab Jason Brown Kevin Keating Date: 04/23/2013 Tools: Philips Screwdriver Parts: Used Computer Tower Procedure:
Lab 9—Last Lab. Statistical Analyses & Threats to Validity. Background. Recall from last lab that there are two major types of designs. If you are interested in the association between continuous variables, you should use a correlational design.
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Lab Accuracy/Precision Lab. Pre-Lab Contrast Accuracy & Precision Give another example of accuracy and another example of precision Contrast Random Errors & Systematic Errors Copy the Formula for % Error. Lab Accuracy/Precision. Lab
Lab. The reaction of copper (II) nitrate and Iron is a single replacement reaction. Fe + Cu(NO 3 ) 2 Fe(NO 3 ) 2 + Cu This equation is already balanced. In this lab we will be putting an iron nail into produce solid copper.
Lab. Neural Networks based control of nonlinear systems. Identification of dynamic systems with Artificial Neural Networks. Dynamic/ feedback network:. Eduard Petlenkov, Automaatikainstituut, 201 3. Identification with Artificial Neural Networks. is theinput of the system and the model.