Small samples and large population variances imply that the estimate for the mean will be relatively poor. Whether or not it will result in an underestimate or overestimate depends on the distribution: with a symmetric distribution the two outcomes are equally likely.
A 'random' sample - covers all age groups, genders, and other criteria. A 'targeted' sample might only cover a small part of the population.
AnswerA sample is a subset of a population. Usually it is impossible to test an entire population so tests are done on a sample of that population. These samples can be selected so that they are representative of the population in which cases the sample will have weights, strata, and clusters. But usually people use random samples. So it's not that the line is different, it's that the line comes from different data. In stats we have formulas that allow a sample to represent a population, if you have the entire population (again unlikely), you wouldn't need to use this sample formulas, only the population formulas.
The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.
They are not usually the same.
They are usually rounded off. It's messy to have a percentage of a person.
A 'random' sample - covers all age groups, genders, and other criteria. A 'targeted' sample might only cover a small part of the population.
Price and quantity variances are computed respectively because different managers are usually responsible for buying and for using inputs.
AnswerA sample is a subset of a population. Usually it is impossible to test an entire population so tests are done on a sample of that population. These samples can be selected so that they are representative of the population in which cases the sample will have weights, strata, and clusters. But usually people use random samples. So it's not that the line is different, it's that the line comes from different data. In stats we have formulas that allow a sample to represent a population, if you have the entire population (again unlikely), you wouldn't need to use this sample formulas, only the population formulas.
The cardic CT angio result samples refer to the samples that are usually taken to diagnose the heart problems.
Marketing researchers study small components of the total consumer population, known as samples, to draw conclusions about the larger group. These samples are representative of the larger population and allow researchers to make inferences about consumers as a whole based on their findings. By studying these samples and analyzing the data collected, researchers can gain insights into consumer behavior, preferences, and trends.
situational factors.
The term preserved usually refers to samples, such as those taken for analysis. Preservation keeps the samples, usually some kind of body tissue, from spoiling or degenerating.
The only way to get rid of sampling error is to use the entire population under study. This is usually impossible, so the next best thing is to use large samples and good sampling methods.
Population distribution is usually greatly affected by what?
You don't. Blood samples are usually taken from a blood vessel.
While insurance liability quotes can vary greatly, they do not reflect on the company. The variances are usually based on the size of the company and its profitability.
Usually 2 or more samples are taken for testing, this is to ensure a clean sample free of contamination during transportation or other unforeseen circumstances.