Normally distributed plastic beads

This term I decided to recenter on tile seven to force a peak at a tile row value. This would also then match a Schoology homework assignment. At 8:00 I wound up with a left skew. I also eliminated all round beads due to concern for the impact of rolling. In the past the round beads have rolled upon landing, leading to extreme values.
The stool centered on tile row seven

In the past I have used centimeter measures. At one point I measured to the class upper limit, the south side of the tile row. But that ensured a skewed result. Then I used tile midpoints, which worked better. I shifted to throwing on a line, but this term I switched back to throwing from and on row center. The center row is tile row seven, fourteen total rows seem to work well enough.

I also further developed the session by pre-writing the material on the upper left onto the board, and pre-guessing the shape I hoped to generate. I expect a normal curve, that is what I normally expect to get. Predicting the future.

This term I also redeveloped spreadsheet tools to provide numeric support to the visual answers I derive on the board, introducing also - if only very lightly - the idea of the mean as being a first moment and the variance as a second moment. I used modified formulas that differ from my chapter six but make more sense to me intuitively and share a certain symmetry.

At 8:00 I had significant skew in the distribution. A few bad tosses, forgot the importance of throwing also with my left hand.

At 8:00 there were only 122 plastic beads down, none round.

At 9:00 I tossed 265 beads, including round beads, used both hands, and was more careful in centering my toss direction and follow-through. I obtained a nicely symmetric normal distribution, perhaps a tad leptokurtic. Round beads are important, outliers happen but they also help increase the spread.

This then leads into a lecture on the mean under the peak, the inflection points being one standard deviation away from the mean, and the location of plus or minus two standard deviations.


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