Machine Learning - The Nature of Probability and Statistics - Exercise on Sampling Techniques

In this video we are going to discuss exercise on sampling techniques

So in the previous video we have discussed that what is a sampling technique and what are

the different ways in which we can do the sampling. So one of the way was your random sampling where a subject was selected from the population

by chance. Another one was our systematic sampling where the kth element of the population will be selected

for the sampling. we had our stratified sampling where the population will be divided into certain strata's

certain groups depending upon some attribute, and then we shall select some of the members

from each strata and group and that will produce the sampling population, that is a sampling

So next one, we're having the cluster sampling where a particular population will be divided into certain number of groups

or clusters and then after doing that division creation of the clusters then we shall be selecting

some of the clusters and we shall take all the members of those clusters selected as a sample

so there are four different ways we discuss that mainly the sampling can be done so here we are

having some respective examples and we are going to suggest what kind of sampling we are

going to apply there. Classify each sample as random systematic stratified or cluster

So here we are having the problem number one. In a large school district, all teachers

from two buildings are interviewed to determine whether they believe the students have

less homework to do now than in previous years So this is the respective problem we are having So now here we are having multiple buildings for the respective large school district but we are selecting only two buildings

and interrogating interviewing all the teachers in those two buildings so obviously it is a good example of cluster sampling every seventh customer

entering a shopping mall is asked to select her or he's favorite store so as

we are going for each seventh customer so we can consider it as a good example of systematic

sampling nursing supervisors are selected using random number of random numbers to determine annual

salaries so now we are using some random numbers to determine annual salaries so obviously

it is we're going to get the flavor of random sampling here every hundredth hamburger manufacturer

manufactured is checked to determine its flat fat content. So here we are having the hundred hamburger

So to determine the fat content, so 100, so from there we are getting this idea that

it is a good example of systematic sampling. Male carriers of a large city are divided into four groups according to gender, male or female

and according to whether they walk or ride on their roots. So, then 10 are selected from each group and interview to determine whether they have been

beaten by a dog in the last year. So, here we are having four groups and we are taking some of the members from each group

and then we are going for the interviewing. So, that means it is a good example of our cluster sampling

So we have taken five examples and we have discussed that how the sampling technique can

be decided on them. Thanks for watching this video