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How do you calculate the probability of observing a sample proportion of .32 or more?
Wiki User
∙ 12y ago
You need a null hypothesis first. You then calculate the probability of the observation under the conditions specified by the null hypothesis.
Wiki User
∙ 12y ago
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A sample of 66 observations will be taken an infinite population The population proportion equals 0.12 The probability that the sample proportion will be less than 0.1768 is?
.9222
In a sample of 500 students 50 percent attend college within 50km of their homes The probability that the population proportion will be between 0.45 and 0.55 is?
According to the theory behind a sampling distribution of a proportion, when you take a sample proportion with mean p from a sample of n people, the actual population proportion will follow a normal distribution of mean p with a standard deviation of √(p*(1-p)/n). Using the information given, our sample had a mean, p, of .5 and a sample size, n, of 500. Therefore, the mean of the population is .5 and the standard deviation is √(.5*(1-.5)/500)=.022361. Next, in order to find our probability, we need to calculate the z-scores of our 2 bounds using the formula z=(x-mean)/standard deviation. For .45 this gives (.45-.5)/.022361=-2.236 and for .55 we get (.55-.5)/.022361=2.236. In order to convert this into a probability, we will need to look these values up in a z-table and find the area between them. Doing that we find that the area must be .974653. This tells us that the probability that the population proportion is between 0.45 and 0.55 is 97.4653%.
What are the differences between probability sampling and non probability sampling?
In a probability sample, each unit has the same probability of being included in the sample. Equivalently, given a sample size, each sample of that size from the population has the same probability of being selected. This is not true for non-probability sampling.
What is the definition for probability sample?
A probability sample is one in which each member of the population has the same probability of being included. An alternative and equivalent definition is that it is a sample such that the probability of selecting that particular sample is the same for all samples of that size which could be drawn from the population.
What is the probability of observing a sample mean of 18 or more from a sample size of 35?
Without knowing the data which is being sampled, it is impossible to answer this other than by saying that the probability is between 0 and 1 inclusive. Consider a company. If you sample the annual pay of the employees, any mean will be greater than 18 as everyone will be taking home more than £18 per year, so the probability is 1. Consider a school. If you sample the lengths of feet of the pupils, any mean will be less than 18 as all the feet are less than 18 inches long, so the probability is 0.
What is difference between proportion and probability?
Proportion is the probability of a selected sample. probability is the true probability of all cases. If this is not what you are looking for then please specify.
A sample of 66 observations will be taken an infinite population The population proportion equals 0.12 The probability that the sample proportion will be less than 0.1768 is?
.9222
How do you calculate the mean of the sampling distribution of the sample proportion?
i dont no the answer
What is the probability for choosing a red marble?
More information is required. Probability by definition is the proportion of a part, called a sample, to the whole, called a population. Thus in this question, we are given the sample only and without the population, it is impossible to calculate the probability. We need to know the size of the population. As a guide, supposing there are 8 red marbles in a jar containing 40 marbles, then the probability of choosing red is 8/40 or 1: 0.2. There is 20 per cent probability of choosing red.
In a sample of 500 students 50 percent attend college within 50km of their homes The probability that the population proportion will be between 0.45 and 0.55 is?
According to the theory behind a sampling distribution of a proportion, when you take a sample proportion with mean p from a sample of n people, the actual population proportion will follow a normal distribution of mean p with a standard deviation of √(p*(1-p)/n). Using the information given, our sample had a mean, p, of .5 and a sample size, n, of 500. Therefore, the mean of the population is .5 and the standard deviation is √(.5*(1-.5)/500)=.022361. Next, in order to find our probability, we need to calculate the z-scores of our 2 bounds using the formula z=(x-mean)/standard deviation. For .45 this gives (.45-.5)/.022361=-2.236 and for .55 we get (.55-.5)/.022361=2.236. In order to convert this into a probability, we will need to look these values up in a z-table and find the area between them. Doing that we find that the area must be .974653. This tells us that the probability that the population proportion is between 0.45 and 0.55 is 97.4653%.
What are the differences between probability sampling and non probability sampling?
In a probability sample, each unit has the same probability of being included in the sample. Equivalently, given a sample size, each sample of that size from the population has the same probability of being selected. This is not true for non-probability sampling.
What is the definition for probability sample?
A probability sample is one in which each member of the population has the same probability of being included. An alternative and equivalent definition is that it is a sample such that the probability of selecting that particular sample is the same for all samples of that size which could be drawn from the population.
What proportion of sample proportions have a value greater than the population in any normal sample proportion distribution?
A half.
What is the probability of observing a sample mean of 18 or more from a sample size of 35?
Without knowing the data which is being sampled, it is impossible to answer this other than by saying that the probability is between 0 and 1 inclusive. Consider a company. If you sample the annual pay of the employees, any mean will be greater than 18 as everyone will be taking home more than £18 per year, so the probability is 1. Consider a school. If you sample the lengths of feet of the pupils, any mean will be less than 18 as all the feet are less than 18 inches long, so the probability is 0.
What is the primary characteristic of a probability sample?
In the context of a sample of size n out of a population of N, any sample of size n has the same probability of being selected. This is equivalent to the statement that any member of the population has the same probability of being included in the sample.
What is the key feature of probability sampling?
The key feature is that each sample of the given size has the same probability of being selected as the sample. Equivalently, each unit in the population has the same probability of being included in the sample.
What do geologists look for when observing a rock sample?
its structure
