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When finding standard deviation you are typically looking at what kind of distribution?
Wiki User
∙ 13y ago
Usually a normal distribution.
Wiki User
∙ 13y ago
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What is the essence of finding the standard deviation of your data?
I am not entirely sure I understand correctly what you mean by "essence". However, the idea of finding the standard deviation is to determine, as a general tendency, whether most data points are close to the average, or whether there is a large spread in the data. The standard deviation means, more or less, "How far is the typical data point from the average?"
What is a z score and what its used for?
The Normal probability distribution is defined by two parameters: its mean and standard deviation (sd) and, between them, these two can define infinitely many different Normal distributions. The Normal distribution is very common but there is no simple way to use it to calculate probabilities. However, the probabilities for the Standard Normal distribution (mean = 0, sd = 1) have been calculated numerically and are tabulated for quick reference. The z-score is a linear transformation of a Normal variable and it allows any Normal distribution to be converted to the Standard Normal. Finding the relevant probabilities is then a simple task.
What is the formula for finding probabilities?
The formula for finding probability depends on the distribution function.
What is a standard deviation?
Standard deviation is a statistical tool used to determine how tight or spread out your data is. In effect, this is quantitatively calculating your precision, the reproducibility of your data points. Here's how you find it: 1). Take the average of all the data points in your set. 2). Find the deviation of each point by finding the difference between each data point and the mean. 3). Add the squares of each deviation together. 4). Divide by one less than the number of data points. If there are 20 data points, divide by 19. 5). Take the square root of this value. 6). Done.
What is the formula in finding the frequency distribution?
The frequency distribution usually refers to empirical measurement and there is no formula for finding it. You simply count the number of times an observation falls within a given range.
What are the steps involved in management directing?
1. establishment of standard 2. fixation of the standard 3. compairing actual performance with standard performance 4. finding out the deviation 5. correcting the deviation
What is the essence of finding the standard deviation of your data?
I am not entirely sure I understand correctly what you mean by "essence". However, the idea of finding the standard deviation is to determine, as a general tendency, whether most data points are close to the average, or whether there is a large spread in the data. The standard deviation means, more or less, "How far is the typical data point from the average?"
What is a z score and what its used for?
The Normal probability distribution is defined by two parameters: its mean and standard deviation (sd) and, between them, these two can define infinitely many different Normal distributions. The Normal distribution is very common but there is no simple way to use it to calculate probabilities. However, the probabilities for the Standard Normal distribution (mean = 0, sd = 1) have been calculated numerically and are tabulated for quick reference. The z-score is a linear transformation of a Normal variable and it allows any Normal distribution to be converted to the Standard Normal. Finding the relevant probabilities is then a simple task.
What is the purpose of finding the standard deviation of a data set?
The purpose of obtaining the standard deviation is to measure the dispersion data has from the mean. Data sets can be widely dispersed, or narrowly dispersed. The standard deviation measures the degree of dispersion. Each standard deviation has a percentage probability that a single datum will fall within that distance from the mean. One standard deviation of a normal distribution contains 66.67% of all data in a particular data set. Therefore, any single datum in the data has a 66.67% chance of falling within one standard deviation from the mean. 95% of all data in the data set will fall within two standard deviations of the mean. So, how does this help us in the real world? Well, I will use the world of finance/investments to illustrate real world application. In finance, we use the standard deviation and variance to measure risk of a particular investment. Assume the mean is 15%. That would indicate that we expect to earn a 15% return on an investment. However, we never earn what we expect, so we use the standard deviation to measure the likelihood the expected return will fall away from that expected return (or mean). If the standard deviation is 2%, we have a 66.67% chance the return will actually be between 13% and 17%. We expect a 95% chance that the return on the investment will yield an 11% to 19% return. The larger the standard deviation, the greater the risk involved with a particular investment. That is a real world example of how we use the standard deviation to measure risk, and expected return on an investment.
What is the purpose of finding standard deviation?
The standard deviation of a set of data is a measure of the random variability present in the data. Given any two sets of data it is extremely unlikely that their means will be exactly the same. The standard deviation is used to determine whether the difference between the means of the two data sets is something that could happen purely by chance (ie is reasonable) or not.Also, if you wish to take samples of a population, then the inherent variability - as measured by the standard deviation - is a useful measure to help determine the optimum sample size.
What is the formula for finding the standard deviation of two independent random variables multiplied together?
The question is excellent. If two independent random variable with different pdf's are multiplied together, the mathematics of calculating the resultant distribution can be complex. So, I would prefer to use Monte-Carlo simulation to calculate the resultant distribution. Generally, I use the Matlab program. If this is not a satisfactory answer, it would be good to repost your question.
What is the formula for finding probabilities?
The formula for finding probability depends on the distribution function.
What is a standard deviation?
Standard deviation is a statistical tool used to determine how tight or spread out your data is. In effect, this is quantitatively calculating your precision, the reproducibility of your data points. Here's how you find it: 1). Take the average of all the data points in your set. 2). Find the deviation of each point by finding the difference between each data point and the mean. 3). Add the squares of each deviation together. 4). Divide by one less than the number of data points. If there are 20 data points, divide by 19. 5). Take the square root of this value. 6). Done.
What is the formula in finding the frequency distribution?
The frequency distribution usually refers to empirical measurement and there is no formula for finding it. You simply count the number of times an observation falls within a given range.
How do you calculate the third quartile for a mean of 110 and a standard deviation of 15?
If this is the only information you have, the answer would be somewhere around 125. Usually, you would find the third quartile by first finding the median. Then find the median of all of the numbers between the median and the largest number, which is the third quartile.
What is the purpose of finding the average of your data?
The basic function of an average is so that you have just one value to represent your entire data with. You don't have to say that your data range lies within this boundaries - you just have to quote the average and standard deviation and that more or less, gives significant information about your data.
What is the T-Test formula?
t= absolute value of ( sample 1 - sample two) THEN DIVIDED by the (standard error of sample one - standard error of sample 2) standard error = the standard deviation divided by (square root of the pop. sample number) You have to work in steps to get all info 1. mean ( REPRESENTED BY 'Xbar') 2. sum of squares ('SS') 3. Sample variance ('s^2') 4. standard deviation ('s') 5. standard error ('s subscript x') 6. pooled measure ('s^2p') 7. Standard error between means (s subscript mean one-mean two) 8. t test In other word finding the mean and having ht esample info leads you to each formula with the end formular being the t-test have fun, its easy but dumb
