View All Pages

Modeling Practices

Physics is all about creating the most accurate models of our complex world. Incorporate these features to clearly measure and explain phenomenon you measure. Use this template Links to an external site. made by Fenbert for your lab reports. 

DATA COLLECTION

  • Repeat runs if time allows.
  • Consistently apply your testing method.
  • Usually, keep all variables the same besides your manipulated/independent variable.
  • Collect at least 10 data points. 
  • Make sure your independent variable range is at least a factor of 10 (if your lowest mass is 1kg, measure up to 10 kg). 

GRAPHING

  • Label your graph, typically using the format Dependent variable vs independent variable. EG. Pasta Bridge Strength vs Bridge Design.
  • Place your measured/dependent variable on the vertical axis. Independent/controlled variable on the horizontal axis. 
  • Label your axis using the format variable (units). E.g. Force (Newtons). 
  • Include a line of best fit and an equation. 
  • Start your graph at (0,0). 

MATH MODELS (EQUATIONS)

Using a linear y = mx + b model as an example:

  • Replace y and x with the variable names (for our pasta experiment, y was pasta strength and x was bridge design).
  • Include units for the slope and vertical intercept. 

Pasta Bridge Strength = 20 (pennies/noodle) * bridge design + (2 pennies) 

Describe your relationship with a slope sentence and vertical intercept.

For every 1 unit increase in manipulated variable, the dependent variable increased/decreased by slope coefficient (dependent variable units)

For every 1 noodle increase in bridge design, the pasta bridge strength increased by 20 pennies. 

When the bridge had no noodles, the pasta could hold 2 pennies. Since a bridge that doesn't exist cannon hold any pennies, and since the vertical intercept is less than 5% the maximum penny value we measured, we believe the vertical intercept can be ignored. 

Percent error calculation: If the theoretical strength of a pasta noodle was 21 pennies, then our percent error would be calculated as follows:

% error = (experimental value - theoretical value)/theoretical value *100

experimental (20) - theoretical (21) / theoretical (21) *100 ---? (20-21)/21 *100 = -4.7%, meaning our slope coefficient underestimated the expected pasta strength by about 5% its true strength.