It can be.
If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.
The standard deviation associated with a statistic and its sampling distribution.
Yes.
You use the t-test when the population standard deviation is not known and estimated by the sample standard deviation. (1) To test hypothesis about the population mean (2) To test whether the means of two independent samples are different. (3) To test whether the means of two dependent samples are different. (4) To construct a confidence interval for the population mean.
If the sample size is large (>30) or the population standard deviation is known, we use the z-distribution.If the sample sie is small and the population standard deviation is unknown, we use the t-distribution
You probably mean the confidence interval. When you construct a confidence interval it has a percentage coverage that is based on assumptions about the population distribution. If the population distribution is skewed there is reason to believe that (a) the statistics upon which the interval are based (namely the mean and standard deviation) might well be biased, and (b) the confidence interval will not accurately cover the population value as accurately or symmetrically as expected.
If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.
It goes up.
normal distribution
The standard deviation associated with a statistic and its sampling distribution.
Yes.
normal distribution
The standard deviation is used in the numerator of the margin of error calculation. As the standard deviation increases, the margin of error increases; therefore the confidence interval width increases. So, the confidence interval gets wider.
z- statistics is applied under two conditions: 1. when the population standard deviation is known. 2. when the sample size is large. In the absence of the parameter sigma when we use its estimate s, the distribution of z remains no longer normal but changes to t distribution. this modification depends on the degrees of freedom available for the estimation of sigma or standard deviation. hope this will help u.... mona upreti.. :)
You use the t-test when the population standard deviation is not known and estimated by the sample standard deviation. (1) To test hypothesis about the population mean (2) To test whether the means of two independent samples are different. (3) To test whether the means of two dependent samples are different. (4) To construct a confidence interval for the population mean.
If the sample size is large (>30) or the population standard deviation is known, we use the z-distribution.If the sample sie is small and the population standard deviation is unknown, we use the t-distribution
The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.