Full Answer
However, because the population is approximately normal, the sampling distribution of the sample means will be normal as well, even with fewer than 3 0 30 3 0 samples.
The sampling distribution of the sample proportion is approximately Normal with Mean μ = 0.43, Standard deviation p ( 1 − p) n = 0.43 ( 1 − 0.43) 75 ≈ 0.05717 . Therefore, there is a 11.1% chance to get a sample proportion of 50% or higher in a sample size of 75.
The standard deviation of the sampling distribution, also called the sample standard deviation or the standard error or standard error of the mean, is therefore given by where σ sigma σ is population standard deviation and n n n is sample size.
Sample proportion: The proportion of observations in a sample with a certain characteristic. Often denoted p̂, It is calculated as follows: p̂ = x / n
We use the sample proportion to estimate a population proportion. For example, we might be interested in understanding what proportion of residents in a certain city support a new law.
Nutrition: A nutritionist may survey 100 people at a hospital to estimate the average number of calories that residents eat per day. Depending on the question of interest, it might make more sense to use the sample proportion or the sample mean to answer the question.