welcome to research Hub we know that statistical research helps in drawing several conclusions based on the requirement of the experts this uses the data collected for a specific purpose we can collect the data using various sampling methods in statistics however the type of sampling method is chosen based on the objective of the statistical research the statistical research is of two forms population and Sample first you need to understand the difference between a population and a sample and identify the target population of your research the population is the entire group that you want to draw conclusions about the population can be defined in terms of geographical location age income or many other characteristics if the population is very large demographically mixed and geographically dispersed okay the sample is the specific group of individuals that you will collect data from the sampling frame is the actual list of individuals that the sample will be drawn from ideally it should include the entire Target population and nobody who is not part of that population so in this video let us discuss the different sampling methods in research such as probability sampling and non-probability sampling methods and various methods involved in those two approaches in detail let's start so first what is sampling sampling is a technique of selecting individual members or a subset of the population to make statistical inferences from them and estimate the characteristics of the whole population sampling is of two types probability sampling and nonprobability sampling let's take a closer look at these two methods of sampling one probability sampling probability sampling is a samp technique where a researcher selects a few criteria and chooses members of a population randomly all the members have an equal opportunity to participate in the sample with this selection parameter there are four types of probability sampling techniques one simple random sampling two cluster sampling three systematic sampling for stratified random sampling one simp random sampling one of the best probability sampling techniques that helps in Saving Time and resources is the simple random sampling method it is a reliable method of obtaining information where every single member of a population is chosen randomly each individual has the same probability of being chosen to be a part of a sample for example in an organization of 500 employees if the HR team decides on conducting team building activities they would likely prefer picking chits out of a bowl in this case each of the 500 employees has an equal opportunity of being selected two cluster sampling cluster sampling is a method where the researchers divide the entire population into sections or clusters representing a population clusters are identified and included in a sample based on demographic parameters like age sex location Etc this makes it very simple for a survey Creator to derive effective inferences from the feedback for example suppose the United States government wishes to evaluate the number of immigrants living in the mainland Us in that case they can divide it into clusters based on states such as California Texas Florida Massachusetts Colorado Hawaii Etc this way of conducting a survey will be more effective as the result results will be organized into States and provide insightful immigration data for a stratified random sampling stratified random sampling is a method in which the researcher divides the population into smaller groups that don't overlap but represent the entire population while sampling these groups can be organized and then draw a sample from each group separately for example a researcher looking to analyze the characteristics of people belonging to different annual income divisions will create straight groups according to the annual family income less than $20,000 $21,000 to $30,000 $31,000 to $40,000 $41,000 to $50,000 Etc by doing this the researcher concludes the characteristics of people belonging to different income groups marketers can analyze which income groups to Target and which ones to eliminate to create a ro map that would bear fruitful results all right there are multiple uses of probability sampling one reduce sample bias using the probability sampling method the research bias in the sample derived from a population is negligible to non-existent the sample selection mainly depicts the researcher's understanding and inference probability sampling leads to higher quality data collection as the sample appropriately represents the population two diverse population when the population is vast and diverse it is essential to have adequate representation so that the data is not skewed toward one demographic three create an accurate sample probability sampling helps the researchers plan and create an accurate sample this helps to obtain well-defined data okay next non-probability sampling in nonprobability sampling the researcher randomly chooses members for research this sampling method is not a fixed or predefined selection process this makes it difficult for all population elements to have equal opportunities to be included in a sample the nonprobability method is a sampling method that involves a collection of feedback based on a researcher or statistician sample selection capabilities and not on a fixed selection process that I in most situations the output of a survey conducted with a non-pro sample leads to skewed results which may not represent the desired Target population but there are situations such as the preliminary stages of research or cost constraints for conducting research okay for types of nonprobability sampling explain the purpose of this sampling method in a better manner one convenient sampling two judgmental or purposive sampling three snowball sampling four quota sampling one convenience sampling this method depends on the ease of access to subjects such as surveying customers at a mall or passers by on a busy street it is usually termed as convenient sampling because of the researchers ease of carrying it out and getting in touch with the subjects researchers have nearly no authority to select the sample elements and it's purely done based on proximity and not representativeness this nonprobability sampling method is used when there are time and cost limitations in collecting feedback in situations with resource limitations such as the initial stages of research convenience sampling is used for example startups and NOS usually conduct convenience sampling at a mall to distribute leaflets of upcoming events or promotion of a cause they do that by standing at the mall entrance and giving out pamphlets randomly two judgmental or purposive sampling judgmental or purposive samples are formed at the researchers discretion researchers purely consider the purpose of the study along with the understanding of the target audience for instance when researchers want to understand the thought process of people interested in studying for their master's degree the selection criteria will be are you interested in doing your Master's in and those who respond with a no are excluded from the sample three snowball sampling snowball sampling is a sampling method that researchers apply when the subjects are difficult to trace for example surveying shelterless people or illegal immigrants will be extremely challenging in such cases using the snowball Theory researchers can track a few categories to interview and derive results researchers also implement this sampling method when the topic is highly sensitive and not open openly discussed for example surveys to gather information about HIV AIDS not many victims will readily respond to the questions still researchers can contact people they might know or volunteers associated with the cause to get in touch with the victims and collect information for quota sampling in Quota sampling members in this sampling technique selection happens based on a preset standard that I in this case as a sample is formed based on specific attributes the created sample will have the same qualities found in the total population nonprobability sampling is used for the one create a hypothesis researchers use the nonprobability sampling method to create an assumption when limited to no prior information is available this method helps with the immediate return of data and builds a base for further research two exploratory research researchers use this sampling technique widely when conducting qualitative research pilot studies or exploratory research three budget and time constraints the nonprobability method when there are budget and time constraints and some preliminary data must be collected since the survey design is not rigid it is easier to pick respondents randomly and have them take the survey or questionnaire okay why are Samples used in research samples are used to make inferences about populations samples are easier to collect data from because they are practical cost effective convenient and manageable don't forget like share and subscribe my channel