Question

 

Question 1

When studying characteristics of a population, there are many practical reasons why we prefer to select portions or samples of a population to observe and measure. Explain why a sample is often the only feasible way to learn something about a population? Provide examples.

Question 2

In probability sampling, every item has a chance of being selected. There are 4 types of probability sampling. Can you name them and provide examples.

Question 3

What is sampling “error”? Could the value of the sampling error be zero and what would this mean? Provide examples.

Answer 1

Question 1: Why sample is the only feasible way:

Answer: (i) When the population is extremely large, it is almost impossible to enumerate the whole population. For example, suppose you want the average height of a person in USA, we have to serort to sampling only. (ii) In case of destructive testing, sampling is the only way. For example, if you want to find the average life of a bulb in a factory, if you resort to compete enumeration, we will be left with nothing after the test.

Question 2: 4 types of probability sampling:
Type 1: Simple Random Sampling (SRS): The probability of selection is the same for every case in the population. Example: Suppose you want to select 10 students from you class containg 100 students. You write each student's name in a seperate paper, suffle the papers and select 10 papers.

Type 2: Stratified Random Sampling: Population is divided into two or more mutually exclusive segments based on some sategories and select the sample from each segment.

EXAMPLE: If yu want to select 10 students from your calss of 100 students, first group the 100 students into 5 segments: each segment represnting the area of resident of the student and then select 2 students from each of the 5 segments.

Type 3: Systematic Sampling: First list all the elements of the population and then select event nth element.

EXAMPLE: First give Roll Numbers to each student from 1 to 100 in the class. The, select every th student of the roll numbers.

Type 4: Cluster sampling: Divide the population into clusters. Obtain a simple random sample of so many clusters from all possible clusters. Obtain data on every sampling unit in each of the randomly selected clusters.

EXAMPLE: Suppose you want to find average height of a man in USA. The 4 clusters in this case are the 4 Time Zones in the USA. Then select 2 Time Zones from the 4 Time Zones. Then draw sample from every person in the selectyed Time Zone.

Question 3: What is sampling Error? Can it be zero?

Sampling Error is the error caused by observing a sample instead of the whole population.

Sampling Error can be zero only when we measure the entire population instead of sampling so that there is no sampling error as there is no sample taken.

Example, suppose you want average mark of all sstudents of your class of 100 students. If you calculate the average of all the 100 students instead of sampling, the sample error is zero.