More work is required to pull a stratified sample than a random sample. Planning Tank - An associate of Out of Scale India Pvt. Survey – Methods, Templates & Questionnaire, Copyright infringement take down notification template, Regional Planning - Need, Importance & Implementation, Population elements = homogeneous on important parameters, Time consuming and tedious, need complete data -set (may not be updated), Easier than previous one & evenly distributed sample. The sampling method is the process used to pull samples from the population. But did you notice here we are out in the field for taking sampling and suddenly realized wait! Before getting this term lets look at what else need to be understood. Here we will select the sample on the basis of their percent constituent i.e 25%, 20%, 35%, 20% respectively as mentioned above. The difference between these types of samples has to do with the other part of the definition of a simple random sample. Example. Stratified random samples group the population elements into strata based on certain criteria, then randomly choose elements from each stratum in proportion to the stratum’s size versus the population. 8 right. Stratified: Population = heterogeneous: Highly representative, unbiased & can be inferred statistically. This often requires a smaller sample size, which can save resources and time. This population would frame the initial path for sampling as we have to know our population its characteristic before getting our hands into the sea. The researchers must take care to ensure the strata do not overlap. Population is nothing but a whole group which we are focusing on for taking the survey for obtaining a certain kind of information. Simple random samples involve the random selection of data from the entire population so each possible sample is equally likely to occur. Example. and then we sample out the population proportionally, confused right, wait let’s see through an example. What is the difference between a simple random sample and a stratified random sample? A systematic random sample relies on some sort of ordering to choose sample members. This would be our strategy in order to conduct a stratified sampling. This is different from judgmental sampling, where the units to be sampled are handpicked by the researcher. Simple random samples involve the random selection of data from the entire population so each possible sample is equally likely to occur. A simple random sample is a random sample pulled from the entire population with no constraints placed on how the sample is pulled. Example. Hope now it’s clear for all of you. One thing to keep in mind here is the cluster sampling would be more effective if we have homogeneity with other clusters i.e the cluster have similar features to each other. Now we get to know, that we need sampling for various purposes and reasons. (For related reading, see: What Are Some Examples of Stratified Random Sampling? Ok. One thing to keep in mind here is the cluster sampling would be more effective if we have homogeneity with other clusters i.e the cluster have similar features to each other. (For related reading, see: What are the criteria for a simple random sampling? Copyright ©2014 - 2020 Some Rights Reserved. Similar is the condition with systematic sampling. As the name suggests it has something to do with ‘strata’ which means layer, here, we can call it as classes/categories. Basically there are four methods of choosing members of the population while doing sampling : Random sampling, Systematic sampling, Stratified sampling, Cluster sampling. Time consuming and tedious & data need to be available for strata. ** Note – This article focuses on understanding part of probability sampling techniques through story telling method rather than going conventionally. Let’s have a look on this issue. I hope you know that arithmetic progression (AP) or a geometric procession (GP) follows a certain pattern or we can say a certain system to acquire their next element in their respective series like what would come next 2, 4, 6, ___ ??? A sample is a set of observations from the population. Similarly sampling here acts as a salt in this case to the government/ conducting agency. We want to know how many houses out of 100 are having garages but you don’t have that much ample amount of time to go to conduct survey of each and every house so you decided to select every 3rd house in a 100 house locality. In this type of sampling, we divide the populations into certain classes or categories on the basis of their characteristics / features such as gender, age etc. You were asked to conduct a survey in your city you divided the locality into zones or let’s say you followed the way of wards i.e you decide to conduct sampling in the currently divided zones by the municipality i.e through the way of wards. We must remember that data/survey of an entire population can’t be gathered/facilitated. I would be hereby presenting you the most simplistic way to get to know the term ‘sampling’ rather than conservative approach to knowing it. A stratified sample can provide a more accurate representation of the population based on the characteristic used to divide the population into strata. A random sample is taken from each stratum in direct proportion to the size of the stratum compared to the population. Simple random samples and stratified random samples differ in how the sample is drawn from the overall population of data. Hmm it’s a tricky question! The population is the total set of observations or data. Remember at your home mom while cooking vegetables put some salt in certain quantity and after sometimes check if it is good enough for serving purpose or not and then proceeding further as per the requirements. The population is divided into different groups that … Shivanshu Shekhar Example. Each point in the population must only belong to one stratum so each point is mutually exclusive. Have you observed what happens here ? Are perfect competition models in economics useful? Suppose we have survey 200 people in a college out of 10,000 and we have already a data of constituents like we know how many are teachers (25%), staffs (20%), UG students (35%), PG students (20%). In contrast, stratified random sampling divides the population into smaller groups, or strata, based on shared characteristics. Out of the total population whom we are going to take survey, in other terms, how to select what members of the population to sample!!