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What is the standard deviation of the sample means called?
The standard deviation of the sample means is called the standard error of the mean (SEM). It quantifies the variability of sample means around the population mean and is calculated by dividing the population standard deviation by the square root of the sample size. The SEM decreases as the sample size increases, reflecting improved estimates of the population mean with larger samples.
When a sample is representative of a population is said to be what?
When a sample is representative of a population, it is said to be a "probability sample" or simply a "representative sample." This means that the characteristics of the sample accurately reflect those of the larger population, allowing for valid inferences and generalizations. Such samples are essential in statistical analysis to ensure the findings can be applied to the entire population.
Is mean an unbiased estimator of a population?
Yes, the sample mean is an unbiased estimator of the population mean. This means that, on average, the sample mean will equal the true population mean when taken from a large number of random samples. In other words, as the sample size increases, the expected value of the sample mean converges to the population mean, making it a reliable estimator in statistical analysis.
When testing for differences between two means the sample population are?
You are testing the difference between two means of independent sample and the population variance are not known. from those population you take two samples of two different size n1and n2. what degrees of freedom is appropriate to consider in this case
What does it means if the standard deviation is large?
that you have a large variance in the population and/or your sample size is too small
What is the standard deviation of the sample means called?
The standard deviation of the sample means is called the standard error of the mean (SEM). It quantifies the variability of sample means around the population mean and is calculated by dividing the population standard deviation by the square root of the sample size. The SEM decreases as the sample size increases, reflecting improved estimates of the population mean with larger samples.
Why is the sample mean an unbiased estimator of the population mean?
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.
What does it mean to say that the sample variance provides an unbiased estimate of the population variance?
It means you can take a measure of the variance of the sample and expect that result to be consistent for the entire population, and the sample is a valid representation for/of the population and does not influence that measure of the population.
Why is population sampling most effective when a population has an even dispersion pattern?
If the population is not evenly dispersed then the sample may unfortunately come from a section that is not typical of the population. That means the sample will not be representative of the population and so any estimates for the population, based on sample statistics are biased and therefore unreliable.
What does simple random sample mean in statistics?
It means that every member of the population has the same probability of being included in the sample.
What is the defining characteristic of a representative sample?
A representative sample accurately reflects the characteristics of the population it is drawn from. This means that the sample is chosen in a way that each member of the population has an equal chance of being included in the sample, which helps to ensure that the findings can be generalized back to the population.
Is mean an unbiased estimator of a population?
Yes, the sample mean is an unbiased estimator of the population mean. This means that, on average, the sample mean will equal the true population mean when taken from a large number of random samples. In other words, as the sample size increases, the expected value of the sample mean converges to the population mean, making it a reliable estimator in statistical analysis.
When testing for differences between two means the sample population are?
You are testing the difference between two means of independent sample and the population variance are not known. from those population you take two samples of two different size n1and n2. what degrees of freedom is appropriate to consider in this case
When the population standard deviation is not known the sampling distribution is a?
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.
When a large number of samples are drawn from a negatively skewed population the distribution of the sample means?
.45
What does it means if the standard deviation is large?
that you have a large variance in the population and/or your sample size is too small
What does polled mean?
When your talking about cows, it means a cow that's naturally horns. and its other stuff for other animals
