A polynomial is identically equal to zero if and only if all of its coefficients are equal to zero. eg. The power series on the left is identically equal to zero, consequently all of its coefficients are equal to 0:
Zero is equal to zero
The sampling error is the error one gets from observing a sample instead of the whole population. The bigger it is, the less faith you should have that your sample represents the true value in the population. If it is zero, your sample is VERY representative of the population and you can trust that your result is true of the population.
always zero
Any number to the power zero is equal to 1 - except zero to the power zero, which is undefined. So, if x is not equal to zero, the answer is 1.Any number to the power zero is equal to 1 - except zero to the power zero, which is undefined. So, if x is not equal to zero, the answer is 1.Any number to the power zero is equal to 1 - except zero to the power zero, which is undefined. So, if x is not equal to zero, the answer is 1.Any number to the power zero is equal to 1 - except zero to the power zero, which is undefined. So, if x is not equal to zero, the answer is 1.
Zero
It means that there are is no variation from the mean. In other words, all values in your sample are identical.
It is equal to zero in ALL distributions.
A polynomial is identically equal to zero if and only if all of its coefficients are equal to zero. eg. The power series on the left is identically equal to zero, consequently all of its coefficients are equal to 0:
The sample mean is an unbiased estimator of the population mean because the average of all the possible sample means of size n is equal to the population mean.
The sample consisted of the entire population.
Zero.
That refers to the fact that any number multiplied by zero is equal to zero.
True.
Zero is equal to zero
If you mean zero to the power zero, it isn't equal to 1. Every other value to the power zero is.
Yes, it is possible for the sample mean to be exactly equal to 135 minutes. This is because the sample mean is calculated by dividing the sum of all the observations by the number of observations. Therefore, if the sum of all the observations is exactly equal to 2700 minutes (135 times 20), the sample mean would be 135 minutes. However, this is highly unlikely to happen.