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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.


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Q: How do you determine the sample size to estimate the proportion?
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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.


How do you determine an adequate sample size?

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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.


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.


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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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 ecological inquiry method is an ecologist using when he enters an area periodically to count the population number of a certain species?

The ecologist is using the mark and recapture method to estimate the population number of a certain species. This involves capturing, marking, and releasing a sample of individuals, then recapturing a new sample later to estimate the total population size based on the proportion of marked individuals in the second sample.


What are the mean and the standard deviation of a proportion?

The mean of a proportion, p, is X/n; where X is the number of instances & n is the sample size; and its standard deviation is sqrt[p(1-p)]


Why do you compare bands in gel electrophoresis?

Bands in gel electrophoresis are compared to determine the size of DNA fragments or proteins based on their migration distances in the gel. By comparing the position of sample bands to standard marker bands of known sizes, one can estimate the size of the unknown DNA fragments or proteins in the sample.


What effect does sample size have on the estimate of the mean?

the larger you r sample size the better your estimate. imagine take the height of person to estimate the average high of an adult male. would one person's height be a good estimate, or would taking the average height of 100, or 5000 adult males will produce a better estimate?