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Compute the variance and standard deviation of the following sample data:5 9 10 2 7 9 14?
mean =(5+9+10+2+7+9+14)/7=8
s^2 = Variance = (1/7){(5-8)^2+(9-8)^2+(10-8)^2+(2-6)^2+(7-8)^2+(9-8)^2+(14-8)^2}=14.6666
Standard deviation =s= sqrt(14.6666)=3.8297
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How to compute residual variance of RIL and Sensex?
Variance is variability and diversity of security from average mean and expected value Variance = standard deviation fo security * co relation (r) devided by standanrd deviation of sensex
Why standard deviation is more often used than variance?
Both variance and standard deviation are measures of dispersion or variability in a set of data. They both measure how far the observations are scattered away from the mean (or average). While computing the variance, you compute the deviation of each observation from the mean, square it and sum all of the squared deviations. This somewhat exaggerates the true picure because the numbers become large when you square them. So, we take the square root of the variance (to compensate for the excess) and this is known as the standard deviation. This is why the standard deviation is more often used than variance but the standard deviation is just the square root of the variance.
Is the range used to compute the median or standard deviation?
Neither.
What is a better measure of variability range or standard deviation?
The standard deviation is better since it takes account of all the information in the data set. However, the range is quick and easy to compute.
How do you compute the standard error in refractive index from your graph?
To compute the standard error in refractive index from a graph, calculate the standard deviation of the data points and divide it by the square root of the sample size. This will give you the standard error in your refractive index measurement.
Is a standard deviation dependent on the mean?
To find the standard deviation, you must first compute the mean for the data set. So the answer is yes. Just have a look at the 5 steps needed to compute a standard deviation and you will see why the answer is yes. In reality, people most often use calculators or computers to do this. However, it is good to understand what they are doing. 1. Compute the deviation by subtracting the mean from each value. 2. Square each individual deviation. 3. Add up the squared deviations. 4. Divide by one less than the sample size. 5. Take the square root
Data A 77 64 71 55 72 73 71 47 52 Data 40 25 26 12 2 46 22 23 28 34 which one what data sets shows more variatiion around the mean?
Compute the variance (or its square root , standard deviation) of each of the data set. Set 1: standard deviation = 10.121 Set 2: standard deviation = 12.09 Set 2 shows more variation around the mean. Check the link below
What does a negative profit variance mean?
From a statistical sense, variance is basically a measure of how spread out the data is from the mean (center) observation. For example, if a company has a mean profit of $100 from all their sales, then we might compute the variance which say for sake of argument is $16. Then what we would do is use the variance number and take the square root to find what is called the standard deviation. In this case the standard deviation would be $4. (The square root of $16). Then we could say that we are 68% sure that the true profit is within the range of the mean plus or minus the standard deviation. In our example, we would have the range as being 100-4=96 to 100+4=104. So we can say that we are 68% sure that the true profit is within ($96, $104) This could be extended further for more confidence... This is just an example of how we use variance. Just think of it as spread. As for negative profit variance..I think that would simply mean that we are looking at loses. It would be similar to above example, example that our average would be -$100 instead.
How do you compute discrete variables?
You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.You do not compute discrete variables. Some variables are discrete others are not. Simple as that. You do not compute people - you can compute their average height, or mass, or shoe size, etc. But that is computing those characteristics, you are not computing people. In the same way, you can compute the mean, variance, standard error, skewness, kurtosis of discrete variables, or the probability of outcomes, but none of that is computing the discrete variable.
What is the mean and standard deviation of 60 percent of 300?
There is insufficient information in the question to answer it. In order to compute a mean and a standard deviation, you need at least two data points, but the question only gave one. Please restate the question.
What does is mean when the standard deviation is 0?
Intuitively, a standard deviation is a change from the expected value.For the question you asked, this means that the change in the "results" doesn't exist, which doesn't really happen. If the standard deviation is 0, then it's impossible to perform the test! This shows that it's impossible to compute the probability with the "null" standard deviation from this form:z = (x - µ)/σIf σ = 0, then the probability doesn't exist.
Why do we have to compute for the mean median mode and standard deviation?
To obtain a much better, simpler, and more practical understanding of the data distribution.
