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What are some assumptions that must be made in order to use a sample to describe a population?
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.
How is stratified sampling applied?
Stratified sampling is used where the population to be sampled can be divided into subsets, called strata, according to some criterion. Each of these strata are then treated as population and random samples representing the same sampling proportion are taken from each stratum. This ensures that in the overall sample, the number from each stratum is proportional to the size of the stratum in the population. So, for example, if the population consists of 100 boys and 150 girls and you want a sample of 25. The overall sampling proportion is 25/(100+150) = 25/250 = 1/10. So the sampling procedure is to take a simple random sample of 10 boys out of 100 and a simple random sample of 15 girls out of 150. If the whole sample were selected randomly, there is only a 17% probability that it would have been 10 boys and 15 girls. Stratification ensures both genders are represented proportionally in the sample.
What is the difference between Population and 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.
Why is a census preferred to a sample?
Sampling can be more accurate than a census as there is greater control of interviewers and less chances of mistakes being made as the data is collated
In a random sample of 200 people 140 are successful historically 75 of the population has been classified as successful what is the mean of the sampling distribution of the proportion?
1. In a random sample of 200 persons of a town, 120 are found to be tea drinkers. In a random sample of 500 persons of another town, 240 are found to be tea drinkers. Is the proportion of tea drinkers in the two towns equal? Use 0.01 level of significance.
What is a example sentence of subgroup?
Subgroups of the population have been shown to be poor.
What are some assumptions that must be made in order to use a sample to describe a population?
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.
What is a sample of a population that has been selected using a pattern?
A sample of a population that has been selected using a pattern is when a researcher selects every 10th person from a list or sampling frame. For example, if a researcher wants to study the attitudes of employees in a large company, they may select every 10th employee from the company directory. This method ensures a systematic pattern in selecting the sample.
How can you determine if the values of the summary statistics for a valiable differ for subgroups of cases?
hi members, i have been faced with the same question. but this was my idea. to answer this question, we should ask ourselves the following quetions. * what are the subgroups of cases? * what can you learn from calculating summary statistics seperately for subgroups of cases? * how can you graph summary statistics for subgroups? with these questions answered then you have answered the whole question. H. IKOBA
How is stratified sampling applied?
Stratified sampling is used where the population to be sampled can be divided into subsets, called strata, according to some criterion. Each of these strata are then treated as population and random samples representing the same sampling proportion are taken from each stratum. This ensures that in the overall sample, the number from each stratum is proportional to the size of the stratum in the population. So, for example, if the population consists of 100 boys and 150 girls and you want a sample of 25. The overall sampling proportion is 25/(100+150) = 25/250 = 1/10. So the sampling procedure is to take a simple random sample of 10 boys out of 100 and a simple random sample of 15 girls out of 150. If the whole sample were selected randomly, there is only a 17% probability that it would have been 10 boys and 15 girls. Stratification ensures both genders are represented proportionally in the sample.
Why is a census preferred to?
1) when the fixed cost of selecting a sample is high. 2) when there is high variability in the characteristic been measured. 3) when the population is small.
What is the difference between Population and 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.
Why do you think some areas are shown as having neither a majority nor an evenly divided population?
these areas may not have been inhabited
What are the advantages and disadvantages of random sampling?
The main advantage is that the sample is representative of the population and the mean of the sample is an unbiased estimate of the population mean. Also, characteristics of other statistics based on the sample are well understood. However, sometimes it may not be possible to gather valid information from a sampling unit and then the sample is no longer random. This can be either because the sampling unit cannot be located or has been compromised by external factors. This can be particularly serious if the "missing" units share a common characteristic. Also, simple random samples may not include any units representing characteristics that are rare in the population - but important in the context of the experiment.
What do national government struggle in Afghanistan?
The population is divided among four major ethnic groups. Ethnic and tribal conflict has been central to Afghan history.
Why do national governments struggles in Afghanistan?
Ethnic and tribal conflict has been central to Afghan history. The population is divided among four major ethnic groups.
Why is a census preferred to a sample?
Sampling can be more accurate than a census as there is greater control of interviewers and less chances of mistakes being made as the data is collated
