The scientist does not study nature because it is useful; he studies it because he delights in
Question:
The scientist does not study nature because it is useful; he studies it because he delights in it, and he delights in it because it is beautiful.
If nature were not beautiful , it would not be worth knowing, and if nature were not worth knowing, life would not be worth living.
HENRI POINCARÈ
EMATH 4–ENGINEERING DATA ANALYSIS
Module 2- 3. Sampling Techniques
Properties of Random Sampling
Random Sampling Techniques
Non-Probabilistic sampling(non-random or judgment sampling)
Prepared by: Engr. R.P. Roselo Instructor
SAMPLING TECHNIQUES:
*Random Sampling ( Fair sampling) - is a method of selecting a sample size(n) from a universe (N) such that each member of the population has an equal chance of being included in the sample and all possible combinations of size (n) have an equal chance of being selected as the sample.
* Non-Random Sampling (Bias sampling) - a method of collecting a small portion of the population by which not all the members in the population are given the chance to be included in the sample.
Properties of Random Sampling
Equiprobability- each member of the population has equal chance of being selected and included in the sample.
Independence - the chance of one member being drawn does not affect the chance of the other member.
Kinds of Random Sampling
Restricted Random Sampling - involves certain restriction intended to improve the validity of the sampling. This is applicable only when population being investigated requires homogeneity.
Ex. A study on effectiveness of a new drug can be tested to two groups of animals. The experimental group will be treated with the new drug; and the controlled group will not treated with the new drug. The selection of sample paired animals should be with restrictions according to their degree of illness so that the significant difference between the two groups will be accepted.
Unrestricted Random Sampling - the best random sampling design because there were no restrictions imposed.
Random Sampling Techniques
1.Lottery or Fishbowl sampling - done by simply writing the names or number of all members of the population in small rolled pieces of paper which are later placed in a container drum . The drum must be shaken thoroughly then draws n out of N as desired for a sample.
2. Table of random Numbers - It is use if the population is large in which the selection of each member of population has an equal chance of being chosen.
a. Direct selection method - used when there are only few sample units to be selected right away.
Table of Random Numbers
Example for Direct method:
Mang Paustino has 5 complimentary tickets to a music concert. However, he has 8 children and he would want to distribute the
5 tickets without being accused of favouritism. So what he does is to write the names of his children (in their presence, of course, to avoid bickering later on) in pieces of paper of the same size. He then folds the pieces of paper uniformly and places them in a container.
Mang Paustino using Table of Random Numbers- direct method.
Procedure:
1. List the 8 names of Mang Paustino’s children; and assigned a number per child.
Number | Name |
1 ……………………… | Jofel |
2 ……………………… | Annie |
3 ……………………… | Lucy |
4 ……………………… | Karla |
5 ……………………… | Jonie |
6 ……………………… | Karen |
7 ……………………… | Matt |
8 ……………………… | Jasmine |
2.From column B of the Table of Random
Numbers, let us take the first digits of each of the following numbers:
537658- get number 5 …1st ticket for Jonie 971282- not included 97820 - not included 918210 - not included 228904 - get number 2…2nd ticket for Annie 163802 - get number 1… 3rd ticket for Jofel 965725 - not included 536062 - skip 276676 - skip
187856 - skip
190606 - skip
344580 - get number 3… 4th ticket for Lucy
338874 - skip
6331- get number 6… 5th /last ticket for Karen
b. Remainder Method – is used whenever the direct selection method cannot be applied.
Example: N=123 (population), n= 10 ( sample size)
Soln:
Since our N is three-digit number, we make use of numbers not exceeding 3digits. Thus 1-999.From table of Random Number-column A.
1st set ---123x 1= 123---( 1-123) 7th set--123x7=861--(739-861)
2nd set--- 123x2= 246---(124-246) 8th set--123x8=984-(862-984)
3rd set---123x3=369---(247-369) 9th set-- 123x9=1,170--rejected
4th set---123x4=492---(370-492)
5th set---123X5=615---(493-615) Exceeded- 3digits
6th set---123x6=738---(616-738)
Then the sample units are:
from 2nd set:(upper limit of the set- number obtained from table) 246-163 = 83…is the remainder, the first sample unit
from 8th set:
984- 903 = 81….is the remainder, the 2nd sample unit
from 8th set: 984- 970= 14… the 3rd sample
from 3rd set: 369-327= 42… the 4th sample
from 4th set: 492-465= 27…the 5th sample
from 5th set: 615- 603= 12 … the 6th sample
from 7th set: 861- 813= 48… the 7th sample • from 4th set: 492- 479= 13 …the 8th sample
from 5th set: 615- 518 =97… the 9th sample
from 2nd set: 246-243= 3… the 10th sample.
therefore the sample units: 83,81, 14, 42, 27,12,48, 13,97 & 3.
3. Systematic Sampling- involves selecting every kth element of a series representing the population. A complete listing is required in this method.
Ex. N= 100 n= 10
Find k: k= N/n thus, K= 100/10= 10
So the 10 samples are: 10,20,30,40,50,60,70,80,90, and 100
Ex. We put 100pcs of paper in the box or container and sake them thoroughly. If number 7 is picked as the random start, the ten sample are: 7,17,27,37,47,57,67,77,87,97.
Other Types of Sampling
Stratified Sampling- a random sampling technique in which the population is divided into non-overlapping subpopulation called strata. Ideally, strata are homogenous groups of population units.
Cluster or Area Sampling- involves dividing the population into non-overlapping clusters.
Multi-stage Sampling-This consider different stages or phases. n1=( N1/N)n n= total size of the stratified random sample
N= total population
N1= no. of 1st stratum elements
N2= no. of 2nd stratum elements
N3= no. of 3rd stratum elements
Note: To determine the appropriate sample size without resorting to your subjective decision. Using Sloven’s formula: n=N/1+Ne2
where: n= sample size N= population size e=0.05( sampling)
• Stratified sampling
a.) Simple Stratified Random Sampling
Ex. Population of students taking Civil Engineering Course of size N= 800 , sample size n= 200 is to be taken. The population can be group according to year level. Then random sampling applied to take 50 students per year level.
Year Levels | Population | Sample |
4th year | 185 | 50 |
3rd year | 200 | 50 |
2nd year | 215 | 50 |
1st year | 200 | 50 |
Total | N=800 | n=200 |
b.) Stratified Proportional Random Sampling
Ex. At a state college, the student may be classified according to the following: Determine appropriate sample size AND NO. OF SAMPLE UNITS PER YEAR LEVEL.
Classification | Population | Sample UNITS |
Senior | 119 | 34 |
Junior | 210 | 60 |
Sophomore | 325 | 93 |
Freshmen | 346 | 99 |
total | 1000 | 286 |
By Sloven’s Formula n= 286
N3=(325/1000)*(286)= 93
N1=(119/1000)*(286)= 34
N4=(346/1000)*(286)= 99
N2=(210/1000)*(286)= 60
• Cluster sampling(Area sampling)-usually applied on a geographical basis. It is cost efficient when the population is widely scattered. The population is grouped into cluster or small units( blocks, districts, municipality or city), where clusters may be of heterogeneous characteristics or attributes.
Non-Probabilistic sampling(non-random or judgment sampling)
Purposive sampling - based on criteria laid down by the researcher.
Quota sampling - relatively quick and inexpensive method to operate since the choice of the number of persons or elements to be included in a sample is done at researcher’s own convince or preference and is not predetermined by some carefully operated randomizing plan.
Incidental Sampling- applied to those samples which are taken because they are the most available.
Convenience sampling- method widely used in television and radio programs to find out opinions of TV viewers or listeners regarding a controversial issue.
Activity 2
Please file this in your portfolio.
Using the third column of the Table of Random Numbers, pick 10 sample units from a population of 1,150. Using Remainder Method
A sample units of 15 is to be taken from population of 90. Use Systematic sampling method
Determine a.) the sample size if 5% margin of error (b.) % share per strata (c.) number of sample units per strata. Use Stratified Proportional
Random method
Departments | Employees | % share | # Samples units |
Administrative | 230 | ||
Manufacturing | 130 | ||
Finance | 95 | ||
Warehousing | 25 | ||
Research and Development | 10 | ||
Total | ? |
Kindly answer the file! here is the reference answering this file.. t
https://drive.google.com/file/d/1NxfryOhH-sjn0YIKpTfRYNbgyzKh2xY4/view?usp=sharing
Project Management A Systems Approach to Planning Scheduling and Controlling
ISBN: 978-0470278703
10th Edition
Authors: Harold Kerzner