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Q: What is the difference between the sample mean and the population mean known as?

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A population survey, better known as a census, entails the collection of each unit in the population. In sample survey information is collected from a subset of the population. The subset, or sample, needs to be selected carefully so that it is representative of the whole population and, if that requirement is met, statistics based on the sample are good estimators for the corresponding population parameters.

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

The difference in between an individual, a population, a community, and an ecosystem is and individual (also known as an organism) is only one thing. The difference in between an an organism and a population is a population is multiple organisms. The difference between a population and a community is a group of populations make a community which of course makes a whole ecosystem.

There are Goodness-of-Fit tests that can be used. The choice of test will depend on what is known about the population and sample data.

The answer is Statistics

In Statistics, the measure of spread tells us how much adata sample is spread out or scattered. We can use the range and the interquartile range (IQR) to measure the spread of a sample. Measures of spread together with measures of location (or central tendency) are important for identifying key features of a sample to better understand the population from which the sample comes from. The range is the difference between a high number and the low number in the samples presented. It represents how spread out or scattered a set of data. It is also known as measures of dispersion or measures of spread.

That is known as a simple random sample, or SRS.

In (Simple) random sampling, all of the units in the sample have the same chance of being included in the sample. Units are selected randomly from a population by some random method that gives equal probability to each element. In stratified random sampling, the entire population is divided into heterogeneous sub-popuation known as strata (sub-population with unequal variances) and a random sample is chosen from each of these stratum. The reason when to use which depends on the situation and need of the experimenter.

No, more information is needed to determine the margin of error. For example, one may need to know the sample's mean, the sample size, and the standard deviations of the population and sample. Depending on the type of test one is performing, certain parameters need not be known. For example, the population standard deviation does not need to be known in a one sample T-test.

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.

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

It is known as deductions.

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