Types of Sampling Methods (4.1)

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Learn about the types of samples such as biased samples, convenience samples, voluntary response sam...
Video Transcript:
foreign population refers to the group of things that we want information about and a sample refers to part of the population that we take out to examine and draw conclusions from in this video we will be looking at the different methods of obtaining a sample but first let's look at the types of biased samples bias samples occur when one or more parts of the population are favored over others the two types of biased samples include the convenience sample and the voluntary response sample a convenient sample only includes people who are easy to reach if this
is our population and a researcher comes along to interview people then you would only talk to the people that are closer to him to be part of the sample this is a biased sampling method because not everyone in the population has an equal chance of being part of the sample only people that are of convenience to the researcher will be interviewed now a voluntary response sample consists of people that have chosen to include themselves in the sample so the researcher lets people come to him this is a buy sampling method because people with a strong
interest for the survey topic are the ones who are most likely to respond whereas the people who don't feel as strongly about the topic may not even care to respond remember that our good sample is one that is representative of the entire population and it gives each thing an equal chance of being chosen when you have these conditions you have what is known as an unbiased sample we will be looking at three different types stratified random sampling multi-stage sampling and simple random sampling the most basic type of sampling is the simple random sample also known
as an SRS since an SRS is unbiased each individual has an equal chance of being chosen to be surveyed in other words to be part of the sample you can think of an SRS as putting names into a hat and selecting n of them so if I wanted a sample size of 6 I would select 6 papers and come up to the randomly chosen people to interview them for a stratified random sample we take the population and we divide it into something called a strata strata refers to the groups of similar people within each stratum
we take an SRS and combine the srs's to get the full sample for example we could take an SRS of two people from each group so that we get the total of six people a stratified random sample is good for making sure that whoever is administering the sample gets in contact with each kind of group the last type of sampling is called multi-stage sampling for multi-stage sampling we use a combination of two or more simple random samples as the name suggests multi-stage sampling means you have to go through different stages to find where your sample
comes from for example if we have three groups stage one could be selecting which group will be picked using an SRS let's say that I picked out Group 1 then that means I would only look at group 1. then for stage 2 I would do another SRS to get the six random people we go through different stages of simple random samples to get the actual sample and this is why this is called multi-stage sampling I'd like to point out that instead of putting names in a hat there's another way to pick things randomly we can
use something called the random digits table the random digits table consists of a long string of random numbers and it can help us do an SRS to use it I would first have to label each member of the population with a number we have 30 people in this population so I will label each person from 1 to 30. notice how I have written 0 1 instead of just one doing this helps us use the random digits table since each label has two digits we will read the string of numbers two digits at a time so
let's say I want a sample size of four we will use the random digits table to randomly select four people the first number on the table is 19 so person 19 will be part of the sample the second number is 22 so person 22 will be part of the sample the third number is 39 but our sample size doesn't go up to 39 so we will ignore it we will also ignore 50 and 34 but we will keep number five we will also ignore 75 62 and 87 but we will keep number 13. as a
result these are the people we would survey thank you
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