Videos uploaded by user “Jeremy Jones”

Follow these five steps to calculate standard deviation. Also includes the standard deviation formula.
Here's the video transcript:
"How to Calculate Standard Deviation
How many vegetables do you have in your fridge? Is that a common amount or are you an outlier? We can use standard deviation to know whether someone’s behavior is normal or extraordinary.
Standard deviation, often calculated along with the mean of a data set, tells us how spread out the data is. It is used for data that is normally distributed and can be easily calculated using a graphing calculator or spreadsheet software, but it can also be calculated with a few math operations.
We’re going to use an example involving the number of vegetables five of our friends have in their fridges. They have 2, 3, 4, 7, and 9 vegetables.
To calculate the standard deviation, the first step is to calculate the mean of the data set, denoted by x with a line over it, also called x-bar.
In this case, the mean would be (2 + 3 + 4 + 7 + 9) / 5 = 5. Our average friend has 5 vegetables in their fridge.
The second step is to subtract the mean from each data point to find the differences. It’s helpful to use a table like this. 2 - 5 = -3, 3 - 5 = -2, 4 - 5 = -1, 7 - 5 = 2, and 9 - 5 = 4.
The third step is to square each difference. (This makes all the differences positive so they don’t cancel each other out and it also magnifies larger differences and minimizes smaller differences.)
-32 = 9, -22 = 4, -12 = 1, 22 = 4, and 42 = 16.
The fourth step is to calculate the mean of the squared differences.
(9 + 4 + 1 + 4 + 16) / 5 = 6.8.
The final step is to take the square root. (This counteracts the squaring we did earlier and allows the standard deviation to be expressed in the original units.)
The square root of 6.8 is about 2.6 and that’s the standard deviation.
We're done! The mean number of vegetables is 5 with a standard deviation of 2.6 veggies. Knowing that about ⅔ of the data fall within one standard deviation of the mean (assuming the data is normally distributed), we can say that about ⅔ of our friends have between 2.4 and 7.6 vegetables in their fridges.
To recap, these are the five steps for calculating standard deviation:
1. Calculate the mean.
2. Subtract the mean from each data point.
3. Square each difference.
4. Calculate the mean of the squared differences.
5. Take the square root.
Using symbols, the equation for calculating standard deviation looks like this [see video]...
Lower case sigma stands for standard deviation of a population.
Upper case sigma tells us to calculate the sum for each instance.
X is each data point.
X bar is the mean of the data points.
And n is the number of data points.
Keep in mind that there is a similar formula that divides by n-1. That formula is used when you only have data for a sample of the population.
Hope this was helpful. See you next time!"

Views: 220448
Jeremy Jones

Video transcript:
How does an insurance company decide how much to charge for car insurance?
How do casinos set up payout structures to make sure that they make a profit?
How does a poker player decide whether or not to fold?
How do we efficiently measure the appeal of a political candidate?
The answers to these questions are informed by the law of large numbers.
The law of large numbers states that as the number of trials or observations increases, the actual or observed probability approaches the theoretical or expected probability.
This is important to understand because it allows us to predict and have confidence in how events will play out in the long run.
Let’s take a common example—flipping a coin. Assuming the coin is fair, we know that the theoretical probability of flipping heads is .5 or 50%. However, that doesn’t guarantee that if we flip a coin 10 times we’ll get 5 heads. But we can be confident that as we continue flipping a coin indefinitely the cumulative proportion of heads flipped should get closer and closer to 50%.
Looking at this graphically helps to illustrate the concept. I just flipped a coin 20 times and these are the results. After each flip, we’ll calculate the cumulative proportion of heads so far. So the first flip is tails, so our current proportion is 0 heads out of 1 flip—0%. The second flip is also tails, so now it’s 0 heads out of 2 flips— still 0% heads. Next flip is tails again— 0%. Then heads, now we have 1 heads out of 4 flips— 25% heads. Flip again and it’s heads—40%. Heads again and we finally hit our theoretical probability of 50% for the first time. Let’s keep going…(video plays out the rest of the 20 flips). This graph shows the observed probability approaching the theoretical probability.
One common misconception, referred to as the gambler’s fallacy, is that if the first four flips were tails, you’re more likely to get heads on the next flip because the proportion is supposed to even out to 50% heads. This is not the case because each flip of a coin is an independent event, its outcome is unaffected by all previous events. So if you start out with four tails in a row, it’s not that you are more likely to get heads, it’s just that in the grand scheme of things, four tails flips will get averaged with a huge number of flips that are expected to yield an even number of heads and tails, causing the proportion to approach 50% as the number of trials increases.
Another version of the law of large numbers explains that the more people from a population that you sample, so the larger your sample size, assuming your sample is free from bias, the closer your sample average will be to the population average.
Let’s say you have a group of 100 people. Each has some number of dollars in their wallet. If we ask one person how much money she has in her wallet, we’ll get our first observation ($49), which might be pretty far from the average of the group. After asking the second person ($29) and averaging that value with the first ($30), we are likely to have a better estimate of the group average. As we continue this process of adding observations and thereby increasing our sample size, we’ll generally get better and better estimates of the group’s average.
SUMMARY
So the law of large numbers gives us a compass with which to navigate the randomness around us. Even though we can never predict the outcome of a single coin flip, we can know that over time about half of the flips will be heads. This knowledge underpins insurance, gambling, and investing. And in general, the principle supports the idea that a well-founded strategy that is followed consistently should win out over time, even though it might result in a few negative events along the way.

Views: 57734
Jeremy Jones

Video transcript:
"Have we discovered a new particle in physics?
Is a manufacturing process out of control?
What percentage of men are taller than Lebron James? How about taller than Yao Ming?
All of these questions can be answered using the concept of standard deviation.
For any set of data, the mean and standard deviation can be calculated. For example, five people may have the following amounts of money in their wallets: 21, 50, 62, 85, and 90. The mean is $61.60 and the standard deviation is $28.01.
How much does the data vary from the average? Standard deviation is a measure of spread, that is, how spread out a set of data is.
A low standard deviation tells us that the data is closely clustered around the mean (or average), while a high standard deviation indicates that the data is dispersed over a wider range of values.
It is used when the distribution of data is approximately normal, resembling a bell curve.
Standard deviation is commonly used to understand whether a specific data point is “standard” and expected or unusual and unexpected. Standard deviation is represented by the lowercase greek letter sigma. A data point’s distance from the mean can be measured by the number of standard deviations that it is above or below the mean. A data point that is beyond a certain number of standard deviations from the mean represents an outcome that is significantly above or below the average. This can be used to determine whether a result is statistically significant or part of expected variation, such as whether a bottle with an extra ounce of soda is to be expected or warrants further investigation into the production line.
The 68-95-99.7 rule tells us that about 68% of the data fall within one standard deviation of the mean. About 95% of data fall within two standard deviations of the mean. And about 99.7% of data fall within 3 standard deviations of the mean.
The average height of an American adult male is 5’10, with a standard deviation of 3 inches. Using the 68-95-99.7 rule, this means that 68% of American men are 5’10 plus or minus 3 inches, 95% of American men are 5’10 plus or minus 6 inches, and 99.7% of American men are 5’10 plus or minus 9 inches. So, this means only about .3% of American men deviate more than 9 inches from the average, with .15% taller than 6’7 and .15% shorter than 5’1. This reasoning suggests that Lebron James is 1 in 2500 and Yao Ming is 1 in 450 million.
In particle physics, scientists have what are called 5-sigma results, results that are five standard deviations above or below the mean. A result that varies this much can signify a discovery as it has only a 1 in 3.5 million chance that it is due to random fluctuation.
In summary, standard deviation is a measure of spread. Along with the mean, the standard deviation allows us to determine whether a value is statistically significant or part of expected variation."

Views: 830598
Jeremy Jones

Explanation of the Monty Hall Problem with four solutions.
Play the game at http://www.stayorswitch.com

Views: 25233
Jeremy Jones

Animated explanation of how to calculate permutations with repetition, permutations without repetition, and combinations without repetition. Useful when trying to calculate probabilities.
How much more secure is a 6-digit passcode than a 4-digit passcode?
How many different two-card hands could you get in Texas Hold ‘em?
How many different outcomes are there for the 100m final?
All of these questions can be answered using permutations and combinations, which are part of the field of mathematics awesomely called combinatorics and less awesome called counting.
When working with permutations and combinations, we need to ask two questions to begin solving the problem: “Does order matter?” and “Is repetition possible?”

Views: 6070
Jeremy Jones

Views: 10706
Jeremy Jones

This tutorial shows how to use the boolean modifier and add a wood grain texture.

Views: 18700
Jeremy Jones

Tutorial video: https://www.youtube.com/watch?v=V_iNNrvonxo
Music: Don't Stop by Audionautix is licensed under a Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/)
Artist: http://audionautix.com/

Views: 1380
Jeremy Jones

How to model an airfoil fin to be 3D printed for a model rocket.

Views: 1613
Jeremy Jones

This is a tutorial showing how to model a low poly rose.

Views: 3962
Jeremy Jones

This tutorial demonstrates how to show off a completed 3D model using camera tracking.

Views: 1176
Jeremy Jones

Views: 2576
Jeremy Jones

This Blender 3D modeling tutorial goes over how to create the St. Louis Gateway Arch.

Views: 1237
Jeremy Jones

A miller uses a 40 lb rock to measure grain with a two-sided scale. He lends the rock to his friend the butcher. The butcher comes to return the rock and says, “I’m sorry but I dropped the rock and it broke into 4 pieces.” Upon seeing the pieces, the miller says, “Actually, this is great. With these 4 pieces I can measure any amount of grain from 1 to 40 lbs!” What are the weights of the 4 pieces?

Views: 496
Jeremy Jones

10 mg of celexa during pregnancy

Pro derma 100mg trazodone

Voltaren 100mg slow release

Glibenese gits 10 mg prednisone

© 2019 Exchange outlook 2018 certificate error

Current Dividend Preference. Participating Preferred Stock. Convertible Preferred Stock. Cumulative preferred stock includes a provision that requires the company to pay preferred shareholders all dividends, including those that were omitted in the past, before the common shareholders are able to receive their dividend payments. Non-cumulative preferred stock does not issue any omitted or unpaid dividends. If the company chooses not to pay dividends in any given year, the shareholders of the non-cumulative preferred stock have no right or power to claim such forgone dividends at any time in the future. Participating preferred stock provides its shareholders with the right to be paid dividends in an amount equal to the generally specified rate of preferred dividends, plus an additional dividend based on a predetermined condition. This additional dividend is typically designed to be paid out only if the amount of dividends received by common shareholders is greater than a predetermined per-share amount. If the company is liquidated, participating preferred shareholders may also have the right to be paid back the purchasing price of the stock as well as a pro-rata share of remaining proceeds received by common shareholders. Significance to Investors. Shareholder. Preferred Stock.