Yes. You could have a biased sample. Its distribution would not necessarily match the distribution of the parent population.
The population consists of every possible unit where a sample is a subset of the population. Note that population and sample need not refer to persons. For example, if studying biodiversity, the population could consist of plots of land.
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.
Population Parameter
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.
You are studying the sample because you want to find out information about the whole population. If the sample you have drawn from the population does not represent the population, you will find out about the sample but will not find out about the population.
The population consists of every possible unit where a sample is a subset of the population. Note that population and sample need not refer to persons. For example, if studying biodiversity, the population could consist of plots of land.
When the population standard deviation is known, the sample distribution is a normal distribution if the sample size is sufficiently large, typically due to the Central Limit Theorem. If the sample size is small and the population from which the sample is drawn is normally distributed, the sample distribution will also be normal. In such cases, statistical inference can be performed using z-scores.
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.
A half.
Population Parameter
A Sample
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.
A sample is a subset of the population.
No, the sample mean and sample proportion are not called population parameters; they are referred to as sample statistics. Population parameters are fixed values that describe a characteristic of the entire population, such as the population mean or population proportion. Sample statistics are estimates derived from a sample and are used to infer about the corresponding population parameters.
A sample is a subset of the population.
The sample is a subset of the population.
You are studying the sample because you want to find out information about the whole population. If the sample you have drawn from the population does not represent the population, you will find out about the sample but will not find out about the population.