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Some assumptions that must be made in order to use a sample to describe a population is to ensure that an accurate sample of the population has been taken. Some factors that must be taken in to account include: gender, race, ethnicity, age, and any other factors that may affect the outcome of the total population. Also the number of sample in relation to the population is also a big factor. Usually, census services use population ratios of per 1000 people.

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Some assumptions that must be made in order to use a sample to describe a population include: 1) the sample is representative of the population, meaning that it accurately reflects the characteristics of the population as a whole; 2) the sample is randomly selected, ensuring that every member of the population has an equal chance of being included in the sample; and 3) the sample size is large enough to provide accurate and reliable results.

Q: What are some assumptions that must be made in order to use a sample to describe a population?

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The sample size is the number of elements, out of a population, for which some data are measured in order to make assessments about the population.

sample is a noun. sampling is a verb. Statistically speaking, a sample is where we gather and examine part of a population. A sampling is where we take the means of samples in order to gather info about the whole...

In order to do a systemic random sample, the items or individuals in the population are arranged in a certain way (for example, alphabetically). A random starting point is selected and then every __th (for example: 10th or 15th) individual is selected for the sample.

Population and SamplePopulation is the area in which you are trying to get information from. Sample is a section of your population that you are actually going to survey. It is important to have a sample that will represent your entire population in order to minimize biases. For example: You want in know how American citizens feel about the war in Iraq. Your population: The United States Your sample: 500 citizens selected randomly from each state.Since the answers all over the US would greatly vary, it is important to have everyone in the population represented in your sample. This is usually done through random sampling, which assumes no biases seeing as the subjects were selected at random.

We would need to know what sample you are referring to in order to answer this question.

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The sample size is the number of elements, out of a population, for which some data are measured in order to make assessments about the population.

Inferential statistics is concerned with making predictions or inferences about a population from observations and analyses of a sample. That is, we can take the results of an analysis using a sample and can generalize it to the larger population that the sample represents. In order to do this, however, it is imperative that the sample is representative of the group to which it is being generalized.

In order to answer the question it is necessary to know the population standard error.

Because the whole population might be too large to sample. A good example is the population of the world. At nearly 7 billion people, it would be unrealistic to sample each person to determine some factor that you are looking at. Generally, we sample a subset of the population, taking into account differences (or errors) that might result, in this case, regional and cultural, in order to estimate the behavior of the larger population.

sample is a noun. sampling is a verb. Statistically speaking, a sample is where we gather and examine part of a population. A sampling is where we take the means of samples in order to gather info about the whole...

The FOUR steps to follow in order to design a good sample are: I. Determination of the data to be collected or described II. Determination of the population to be sampled III. Choosing the type of sample IV. Deciding on the sample size

Population and SamplePopulation is the area in which you are trying to get information from. Sample is a section of your population that you are actually going to survey. It is important to have a sample that will represent your entire population in order to minimize biases. For example: You want in know how American citizens feel about the war in Iraq. Your population: The United States Your sample: 500 citizens selected randomly from each state.Since the answers all over the US would greatly vary, it is important to have everyone in the population represented in your sample. This is usually done through random sampling, which assumes no biases seeing as the subjects were selected at random.

the participants are representative of the population they are interested in studying

A sample order and acknowledgement letter can be found on the 'Sample Letter Templates' website. The sample is not a downloadable sample but will suffice the purpose.

Population and SamplePopulation is the area in which you are trying to get information from. Sample is a section of your population that you are actually going to survey. It is important to have a sample that will represent your entire population in order to minimize biases. For example: You want in know how American citizens feel about the war in Iraq. Your population: The United States Your sample: 500 citizens selected randomly from each state.Since the answers all over the US would greatly vary, it is important to have everyone in the population represented in your sample. This is usually done through random sampling, which assumes no biases seeing as the subjects were selected at random.

A subset of cases selected from a larger population is called a sample. Samples are chosen to represent the larger population in order to make inferences or draw conclusions about the population as a whole.

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