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There is no simple answer. There are two main factors need to be taken into account. Consider the simple case of a dichotomous or binary variable.
One consideration is the consequences of getting the proportion wrong. If you are estimating the proportion of males (and females) going to a cinema so as to design the correct number of toilets, a 5% risk of getting it wrong may be acceptable. You may have some disgruntled customers and, in any case, it may be possible to rebuild and re-designate some toilets. If, instead, you are estimating the proportion of people who have a serious adverse reaction to some medication, a 5% error rate is catastrophic! Not just for the patient but for the pharmaceutical company as well.
Such risk assessment will determine the confidence level that you require from the estimate. Suppose now that for the study under consideration, a 5% risk of getting it wrong is acceptable. That is, you want to be 95% confident that the true (but unknown proportion) is within 1.96 standard errors of your estimate.
If the true proportion is around 50%, then a sample size of just under 100 will suffice. However, if you are trying to estimate the proportion of a rare characteristic - whose true incidence in the population is 0.5% - then for the same degree of confidence in the estimate you will need a sample of over 19,000.
What else can I help you with?
What sample size is required from a very large population to estimate a population proportion within?
The answer depends on how rare or common the selected trait is. For something that is very rare, you will need a much larger sample to get a reasonable estimate of proportion.
What is the standard error for the following proportion sample size of 25 and?
To calculate the standard error for a proportion, you can use the formula: [ SE = \sqrt{\frac{p(1 - p)}{n}} ] where (p) is the sample proportion and (n) is the sample size. If the proportion is not given in your question, you'll need to specify a value for (p) to compute the standard error. For a sample size of 25, substitute that value into the formula along with the specific proportion to find the standard error.
Consider a random sample of size 45 from a population with proportion 0.30 find the standard error of the distribution of sample proportions?
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What is sample distribution of the sample proportion?
The sample distribution of the sample proportion refers to the probability distribution of the proportion of successes in a sample drawn from a population. It is typically approximated by a normal distribution when certain conditions are met, specifically when the sample size is large enough (usually np and n(1-p) both greater than 5). The mean of this distribution is equal to the population proportion (p), and the standard deviation is calculated using the formula √[p(1-p)/n]. This distribution is useful for making inferences about the population proportion based on sample data.
When can you estimate a population's size when counting individuals in a sample of the population?
You can estimate a population's size when counting individuals if the density in a sample is greater than the population density.
What sample size is required from a very large population to estimate a population proportion within?
The answer depends on how rare or common the selected trait is. For something that is very rare, you will need a much larger sample to get a reasonable estimate of proportion.
What is the standard error for the following proportion sample size of 25 and?
To calculate the standard error for a proportion, you can use the formula: [ SE = \sqrt{\frac{p(1 - p)}{n}} ] where (p) is the sample proportion and (n) is the sample size. If the proportion is not given in your question, you'll need to specify a value for (p) to compute the standard error. For a sample size of 25, substitute that value into the formula along with the specific proportion to find the standard error.
How do you determine an adequate sample size?
A sample size is needed whenever you conduct an experiment. How you determine an adequate sample size depends on the scope of what you're testing, such as medications.
Factors to consider in determining sample size?
Factors that determine sample size
3 scenarios where slovin's formula is being applied?
A research study wants to estimate the proportion of adults in a city who prefer a certain brand of coffee. The researchers use Slovin's formula to determine the sample size needed for their survey. A market researcher is conducting a survey to estimate the average monthly household income in a specific neighborhood. Slovin's formula is utilized to calculate the sample size required to ensure the results are statistically significant. An environmental scientist is studying the population density of a rare species of bird in a particular habitat. By using Slovin's formula, the scientist can determine the appropriate sample size for monitoring and studying this bird population accurately.
The expected frequency is determined by multiplying the sample size by the hypothesized proportion?
True.
Consider a random sample of size 45 from a population with proportion 0.30 find the standard error of the distribution of sample proportions?
dczczczxczczczxczxczc
What is sample distribution of the sample proportion?
The sample distribution of the sample proportion refers to the probability distribution of the proportion of successes in a sample drawn from a population. It is typically approximated by a normal distribution when certain conditions are met, specifically when the sample size is large enough (usually np and n(1-p) both greater than 5). The mean of this distribution is equal to the population proportion (p), and the standard deviation is calculated using the formula √[p(1-p)/n]. This distribution is useful for making inferences about the population proportion based on sample data.
When can you estimate a population's size when counting individuals in a sample of the population?
You can estimate a population's size when counting individuals if the density in a sample is greater than the population density.
Why do smaller populations need larger sample sizes?
They do not. Population size does not affect the sample size. The variability of the characteristic that you are trying to measure and the required accuracy will determine the appropriate sample size.
What is the sampling distribution of p hat?
The sampling distribution of (\hat{p}) (the sample proportion) describes the distribution of sample proportions obtained from repeated random samples of a given size from a population. It is approximately normal when the sample size is large enough, typically when both (np) and (n(1-p)) are greater than 5, where (p) is the population proportion and (n) is the sample size. The mean of this distribution is equal to the population proportion (p), and the standard deviation (standard error) is given by (\sqrt{\frac{p(1-p)}{n}}).
How do i arrive at a sample size in a project?
To determine an appropriate sample size for a project, start by defining your research objectives and the target population. Use a sample size formula that incorporates the desired confidence level, margin of error, and the estimated proportion of the population that has the characteristic of interest. Additionally, consider practical factors such as resource availability and time constraints. Tools like statistical software or online calculators can help streamline the calculations.
