Physics and Astronomy Labs/Uniform acceleration on tapped basketball



In the Tapping Basketballs and Spitwad Lab we started by marking every 5 tiles in the hallway. We designated people to different jobs. One person tapped the back of a basketball at a constant rhythm with a meter stick so the basketball would accelerate at a constant pace. Other people made spitwads. One person was a timer we used the spitwads to mark where the ball was at a certain time. we used seconds, so, every second the timer yelled and the throwers threw spitwads to mark where the ball was. After everyone threw we marked the distances of the best spitwads from the origin we then used the data to make a scatterplot and then found the line of best fit.

In the lab, we had someone hit a basketball with a meter stick which caused it to accelerate, while this was happening, we had two people on each side of the hall assigned with a number throw spit wads in front of the ball as their number was called.

When everybody's number was called and the spits wads were thrown, we measured the distance between each second using the spit wads on the ground, this helped us figure out the uniform acceleration of the ball.

Trig Physics
To be modified pending input from Calc Physics

GW
We took data from an experiment, which consisted of using a ruler to hit a ball--marking where the ball has travelled with spit wads thrown every second, and attempting to increase velocity at a steady rate. The distance between each spit wad is the distance the ball has travelled in one second. The data included time and distance. We then put that data into an excel spreadsheet, solved for the approximate velocity of the ball, then made a velocity-time graph to map out the experiment. Finally, we solved for two different rates of change to better capture the entire span of the graph, then solved for our percent error.

TJ
Data were collected from an experiment conducted by using a yard stick to hit a basketball down the hall while spit wads were used to measure the distance in feet. Data from the lab was inserted into excel and the velocity was calculated in ft/s. Once a graph was constructed two lines of best fit were drawn and the slope of both were found using the change in velocity divided by the change in time. using this information we guesstimated the uncertainty.

TR
Acceleration of Basketball
 * 1) Copied data from this table into Microsoft Excel
 * 2) Inserted formula into velocity column to calculate velocity; =(ft+in/12)/(1)
 * Divided by 1 because the time interval between measurements was 1 sec. 3.

Calculus physics

 * 1) Suggest an edit on the lab as described above.
 * 2) Measure the slope with an uncertainty in the figure by hand. Keep in mind that "uncertainty" usually means one standard deviation, suggesting that typically 68% of the data points fall within your range.     Repeat using Excel and/or Matlab
 * 3) Explain the formulas governing this. Use pencil and paper on equations and sketches.  Put words into sandbox, referencing the equations and sketches.

finding the uncertainty in slope

 * Method 1; entire class measures slope by hand and we take the mean and standard deviation

Result: $$3.0\pm0.2$$
 * Metho 2; Draw a "high" and "low" estimate.

How Things Work Lake Campus Fall 17
Is this good data? Look at the 1 and 2 are the first (or among the first) HR diagrams to be published. This is a modern one.

This was graphed in two courses and the acceleration was "eyeball fit" to about 2.0&plusmn;0.5 ft/sec2. We had to "cheat" by including a zero velocity data point at t = 0 and also neglected the last data point. Note: This is not "cheating" if you report what you did, and also, no scholarly paper would use the word "cheat" to explain what was done here.--user:Guy vandegrift

At many small strikes equivalent to a gentle push (or force)?
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