A researcher testing a hypothesis that the population mean is 25 takes a sample of size 36 and obtains a sample mean of 23 with an estimated standard error of 4. What is the observed value of the test statistic

Answer:

The test statistic is 23

Step-by-step explanation:

Best way to understand this is to think of a sample and it's purpose;

You take a sample to get information that can be extrapolated to apply to the whole population;

So, for example, you have a factory making light bulbs, and you want to find out how long they last;

You would take a number of light bulbs from the production line, i.e. a sample, and test these;

It would be impossible to test every light bulb as this would take too long and there would be none left unused to sell, i.e. it would not be feasible or viable to do;

You would then find a mean of these times from the sample, and then extrapolate and assume it to be the duration of any light bulb coming off the production line;

The sample is the handful of light bulbs chosen to test;

The test statistic refers to the quantity or value, calculated from the sample data, this would be the mean light bulb duration in the light bulbs example;

Similar and yet different to a test statistic, a population parameter refers to a quantity or value calculated from population data;

A population refers to all members of a particular group of objects/items, so in the example, it would be all the light bulbs produced;

The population parameter would refer to the mean calculated based on data from the population (i.e. all the light bulbs produced);

Realistically, it is impossible to determine a population since it would be unviable in the practically all cases, as we can see in the example;

This value is almost always theoretical and would be assumed from a test statistic in any real scenario.

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