The Mugenda and Mugenda sampling formula is used to determine the appropriate sample size for a study based on a specific population size and the desired margin of error. The formula accounts for the confidence level, population size, and the variability of the responses. It is particularly useful in Social Sciences for research involving large populations, ensuring that the sample accurately represents the larger group. The formula helps researchers make informed decisions about how many participants to include in their studies.
According to research made at multiple websites; Mugenda and Mugenda, which is a company that focuses on research methods for various areas, define sample size by using statistics data and probability.
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
Sampling and Non sampling errors
Random Sampling
simple random, stratified sampling, cluster sampling
According to research made at multiple websites; Mugenda and Mugenda, which is a company that focuses on research methods for various areas, define sample size by using statistics data and probability.
Well, let's not worry about complex formulas right now. Remember, determining sample size is just a way to ensure your research results are reliable. It's like adding a touch of color to your painting to make it truly shine. Just focus on the beauty of your research journey, and the right sample size will naturally come to you.
it's a random sampling technique formula to estimate sampling sizen=N/1+N(e)2n- sampling sizeN-total populatione-level of confidence
it's a random sampling technique formula to estimate sampling size n=N/1+N(e)2 n- sampling size N-total population e-level of confidence
sampling theorem is defined as , the sampling frequency should be greater than or equal to 2*maximum frequency, and the frequency should be bounded.. i,e fs=2*fmax where fs= sampling frequency
https://onlinecourses.science.psu.edu/stat506/node/44
state and prove sampling theory as applied to low pass signal
The formula for simple random sampling is: n = N * (X / M) Where: n = number of samples N = population size X = sample size chosen M = total number of units in the population
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
Answer is Quota sampling. Its one of the method of non-probability sampling.
Sampling techniques in researching involves to types of sampling. The probability sampling and the non-probability sampling. Simple random is an example of probability sampling.
You are correct; convenience sampling is not random sampling.