Well, if your sample does not represent the larger sample, you'll certainly not get a valid result ... For example, if you're studying pregnancy and your sample includes men - The whole idea of "representative' sample is fuzzy and often gives interesting errors.
this is brief, but a census gathers data from the whole group/poulation, wheras a sample investigation on takes a small part of the group/poulation, a sample
With random sampling, you are hoping to get a representative sample of a whole, however statistically you could get a sample that is very different from the whole it was selected from. The larger the sample proportion of the whole, the better your sample will be. For example, a sample of 10 out of 100 is not as good as 20 out of 100. The bigger the sample the closer to the actual whole average you will get.
You have 4 parts and 3 of them taken from that 4 represents 3/4 or 75% of the whole.
It is not a sample. A sample must be a proper subset of the whole population.
The term is "representative sample." It is a subset of a population that accurately reflects the characteristics of the whole population it is meant to represent.
You are studying the sample because you want to find out information about the whole population. If the sample you have drawn from the population does not represent the population, you will find out about the sample but will not find out about the population.
yes because the quota sample include the random sample and when we have over estimation we will use the quota sample
In statistics it is a random sample
Culture
Well, if your sample does not represent the larger sample, you'll certainly not get a valid result ... For example, if you're studying pregnancy and your sample includes men - The whole idea of "representative' sample is fuzzy and often gives interesting errors.
this is brief, but a census gathers data from the whole group/poulation, wheras a sample investigation on takes a small part of the group/poulation, a sample
The advantage of sampling in results is that it greatly simplifies results. If the sample is appropriately random, the results of the sampling will accurately represent the whole.
The colors of the American flag were taken from the flag of the United Kingdom, and represent noting in themselves. The flag as a whole represents the United States of America, the stars represent the states in the union and the stripes represent the original 13 colonies turned states.
With random sampling, you are hoping to get a representative sample of a whole, however statistically you could get a sample that is very different from the whole it was selected from. The larger the sample proportion of the whole, the better your sample will be. For example, a sample of 10 out of 100 is not as good as 20 out of 100. The bigger the sample the closer to the actual whole average you will get.
You have 4 parts and 3 of them taken from that 4 represents 3/4 or 75% of the whole.
A sample is a randomly-selected group chosen to represent a larger population for research or analysis. Sampling aims to provide insight into the characteristics and behaviors of the entire population based on the traits observed in the sample. It is an essential method in statistics and research to draw conclusions about a larger group based on a subset of its members.