Notes

The various sample approaches were one of the topics we covered in our last discussion of Chapter 3's sections. Sample methods can be classified into two categories: probability sampling, which involves selecting participants at random and knowing the population's final result, and non-probability sampling, which is subjective because it cannot estimate the population as a whole for each element and selects participants based on specified criteria. Now let's, discuss the probability sampling some examples is systematic where taking every kth element in the population as sample who chooses data point to predetermined, because it easily to select and can identified easily. the second one is cluster that only requires to selects only certain group by populations. the second one is the non-probability sampling in which have the puposive sampling where it using the researcher's judgement on that it can base on the believes of researchers that it will be easy, knowledgeable than the other and the objective of the study it easy to understand because it call "on purpose". the other one is convenience sampling a selecting a groups of individuals that based on their accesibility, willingness, and availability for the study. These sampling technique will help us to be knowledgeable when we are going to make an chapter 3.


The various sample approaches were one of the topics we covered in our last discussion of Chapter 3's sections. Sample methods can be classified into two categories: probability sampling, which involves selecting participants at random and knowing the population's final result, and non-probability sampling, which is subjective because it cannot estimate the population as a whole for each element and selects participants based on specified criteria. The various sample approaches were one of the topics we covered in our last discussion of Chapter 3's sections. Sample methods can be classified into two categories: probability sampling, which involves selecting participants at random and knowing the population's final result, and non-probability sampling, which is subjective because it cannot estimate the population as a whole for each element and selects participants based on specified criteria. Now let's discuss probability sampling. Some examples are systematic sampling, where taking every kth element in the population as a sample and choosing the data point to be predetermined because it is easy to select and can be identified easily. The second one is clustering, which only requires selecting a certain group by population. The second type is non-probability sampling, which includes purposive sampling, which is based on the researcher's belief that it will be easier, more knowledgeable than the other, and that the objective of the study will be simple to understand because it is called "on purpose." The other one is convenience sampling, which involves selecting groups of individuals based on their accessibility, willingness, and availability for the study. These sampling techniques will help us to be knowledgeable when we are going to make Chapter 3.