I can easily guess the answers to these questions, but that's not the point. By writing it out, you clarify things in your own mind.CryptoMath said:Variance/n
Average_Total: as in the average of all the 14 plums.andrewkirk said:You'll find it easier to understand if you write sentences around your formulas, explaining what they represent.
For instance, what is 'Average_Total' and why did you write
I can easily guess the answers to these questions, but that's not the point. By writing it out, you clarify things in your own mind.
Writing explanatory sentences helps it fit together in a logical manner in your mind, rather than just being a jumbled bunch of formulas that you try to commit to memory, hoping to use the right one at the right time.
I got this one resolved it is simply that:andrewkirk said:You'll find it easier to understand if you write sentences around your formulas, explaining what they represent.
For instance, what is 'Average_Total' and why did you write
I can easily guess the answers to these questions, but that's not the point. By writing it out, you clarify things in your own mind.
Writing explanatory sentences helps it fit together in a logical manner in your mind, rather than just being a jumbled bunch of formulas that you try to commit to memory, hoping to use the right one at the right time.
I have an other exercise, may you help me with that one please ?andrewkirk said:That's right, the formula that the variance of a sum of independent random variables is the sum of the variances is true regardless of distribution.
BTW, the problem statement omitted to say that the weight of plums in the pack is independent, which is essential to obtaining the solution. In practice, that may not be the case, depending on how the sample of 14 was selected. For instance if there is a lot of jostling there will be more larger plums near the top, and smaller near the bottom. So 14 plums selected from near one another would be expected to have correlated sizes.
https://www.physicsforums.com/threads/math-probability-need-to-find-the-variance.857348/andrewkirk said:OK. Post it as a new thread though, unless it's very closely related, to avoid confusing readers..
Variance is a measure of how spread out a set of data is. In math probability, it is used to determine the average distance of each data point from the mean, or average, of the data set.
To calculate the variance of a data set, follow these steps:
Variance is important in math probability because it helps us understand the spread of data and how likely it is to deviate from the mean. It is also used to calculate other important measures, such as standard deviation and covariance.
Variance and standard deviation are closely related. Standard deviation is simply the square root of variance. This means that they both measure the spread of data, but standard deviation gives us a more intuitive understanding of this spread as it is in the same units as the original data set.
Variance can be used in many real-world situations, such as finance, sports, and medicine. It can help us understand the risk and potential outcomes of investments, the performance of athletes, and the effectiveness of medical treatments. Basically, any situation where we want to analyze and make predictions based on data can benefit from the use of variance.