Sampling Techniques.
Simple Random Sampling A sampling procedure that assures that each element in the population has an equal chance of being selected is referred to as simple random sampling .Let us assume you had a school with a 1000 students, divided equally into boys and girls, and you wanted to select 100 of them for further study. You might put all their names in a drum and then pull 100 names out. Not only does each person have an equal chance of being selected, we can also easily calculate the probability of a given person being chosen, since we know the sample size (n) and the population (N) and it becomes a simple matter of division: n/N x 100 or 100/1000 x 100 = 10% Systematic Sampling At first sight this is very different. Suppose that the N units in the population are numbered 1 to N in some order. To select a systematic sample of n units, if then every k-th unit is selected commencing with a randomly chosen number between 1 and k. Hence the selection of the first unit determines the whole sample, e.g., N = 5,000, n = 250 therefore k = 5000/250 = 20. Therefore, select every 20th item commencing with (say) 6. Question : Is it equivalent to simple random sampling? Strictly speaking the answer is No!, unless the list itself is in random order, which it never is (alphabetical, seniority, street number, etc). Advantages (i) easier to draw, without mistakes (cards in file)
MIXING AND SAMPLING
MIXING AND SAMPLING NAME OF AUTHOR: MIKE NAME OF INVESTIGATORS: BLITS DATE OF INVESTIGATION: XXXXXXX DATE OF SUBMISSION: XXXXXXX NAME OF DEMONSTRATOR: XXXXX . Abstract The main aims of this investigation are to find the relationship between agitation and salt concentration as a function of position and how this relationship varies with time, and also to verify the effect of particle size of the salt on these relationships. In order to measure the ability of the solution to conduct electricity, a conductivity meter was used. It was done by using a conductivity probe and putting it in the solution, this measured the ability of the solution to conduct an electric current between the two electrodes. The solution was made by firstly weighing 30g of sodium chloride and emptying it in a water-mixed vessel. In the vessel, the salt was dissolved by using an impeller at an agitation speed of 3. A series of baseline samples were taken before injecting the salt into the vessel. This was done as a control for the experiment. After the salt was injected into the vessel, 25 cm3 samples of the solution were collected in letter-numbered test tubes from the 6 valves of the vessel every 3 minutes. The conductivity values of these samples were measured with an EC meter and the results were recorded in a table. Two different particle sizes of the same salt were used to observe the
The Advantages and Disadvantages of Quota Sampling Compared to Random Sampling
The Advantages and Disadvantages of Quota Sampling Compared to Random Sampling Introduction Quota sampling is a non-probability sampling method, compared to random sampling methods, which are known as probability sampling methods. Examples of probability methods are stratifying sampling, cluster sampling, systematic sampling and simple random sampling. When a sample needs to be taken from a population, the issue of which type of sampling method to use arises; probability or non-probability. Since we are looking at specifically quota sampling, we need to define it. Quota sampling involves stratifying a population into mutually exclusive sub-groups, as if using the stratified sampling method. However, the difference is, in quota sampling, judgement is used instead of randomness to select units from each stratum. The number of sampling units chosen from each stratum is based on proportion. Random sampling is defined as when every unit in the population has a probability of being chosen. For a random sample to be carried out, there also needs to be a sampling frame. Advantages of Quota Sampling Although quota sampling is criticised heavily by academics, it does have its advantages. The biggest case for it is that is incredibly cheap to carry out. Travel costs are much cheaper, as your objective is to satisfy your quota, of course this would be constrained by the control,
DNA sampling
Should you have to provide a DNA sample to enroll in FCPS? There are many different opinions on whether people should provide a DNA sample to enroll in FCPS schools. Their opinions may be based on different ethics and privacy matters. For example, one person might not want to give a sample just because they don't want to, but one other person might do it because they feel like it will help society somehow. Personally, I feel like you should provide a DNA sample to enroll in FCPS, even though there are some points that aren't efficient about it. DNA, for example, can help identify criminals and vandals. If all the kids and teachers were to provide DNA samples upon enrolling in FCPS, FCPS could keep a database of DNA that they can check at anytime. If South Lakes were ever vandalized by students from another school in FCPS, then the little DNA that is left behind could be checked in the database to find a match. Also, this kind of information could clear the blame off so many innocent and wrongfully arrested people. This use of DNA sampling could also reduce the amount of crime on school property since the students now know that they have a greater chance of getting caught. Even though this is a very efficient way of decreasing crime, there is one major set back. Evidence may not be available at the scene of the crime, which would mean that the DNA database would be of no
maths coursework sampling
GCSE Coursework : INTRODUCTION The data which I have to use in this coursework was collected from 100 Year 7 (50 boys, 50 girls) and from 100 Year 10 (50 girls , 50 boys). All the pupils were asked to estimate measurements on the data collection sheet given to them. i. the lengths of two lines ii. the sizes of two angles iii. the area of two shapes Aim: Statistics is a very important tool in analysing data and it is the science of summarising and analysing data that are subject to random variation. The main purpose of this investigation is to test 3 hypothesis by analysing the data . . Plan: Sampling Usually it is not possible to study the entire population in which one is interested. It is therefore necessary to consider a sample and to relate its characteristics to the total population. To begin my task I need a sizeable and manageable set of data to use and test. The data provided comprises of 200 pupils. I wish to sample this data so that samples could be analysed statistically to see the relationship between two selected variables for the entire data collected from upper and middle sets of year 7 and year 10. Although there are various ways of sampling the data, but I will stick to three main types of sampling which would be random, stratified and systematic. I shall also make sure that any bias is avoided during this sampling technique
Random sampling using a quadrat
Random sampling using a quadrat Data Collection: Below are two tables showing the number of roots of dandelions collected by all the groups involved in my class in two contrasting parts of public Park - the data pooled. NB: Shaded areas in the tables are the results obtained by my group only Site 1: Number of the roots of dandelions obtained by each throw of random sampling using quadrats. 7 5 2 9 4 2 3 8 4 4 3 4 4 2 6 0 6 3 4 3 4 2 8 6 7 4 5 0 0 7 2 6 2 3 2 0 5 4 8 6 0 0 7 3 7 4 3 0 6 3 8 3 5 3 4 4 8 2 4 0 2 5 6 2 5 4 6 8 8 7 5 Site 2: Number of the roots of dandelions obtained by each throw of random sampling using quadrats. 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 * The sum of the roots of dandelions obtained by my group in site 1 is 105 roots and site 2 is 9 roots. * The sum of the roots of dandelions obtained by all the groups in site 1 is 325 roots and site 2 is 32 roots. * These results are shown in percentage in the pie charts on the next page. The percentage of the population of dandelions can be calculated by: Sum of the roots of dandelions obtained in one site Sum of the roots of dandelions obtained in both sites * The percentages may not be exactly
Woodlands: Random Quadrat Sampling Technique.
WOODLANDS: RANDOM QUADRAT SAMPLING TECHNIQUE INTRODUCTION Dog's mercury is one of the first plants to break through the dark earth in damp and woodland areas. It turns its still pale green stems towards the light. Both environmental and genetic factors influence dog's mercury during this period of growth, therefore variable factors such as light, temperature, water and nutrient availability affect it growth. This study will attempt to investigate random sampling at a number of sites and taking measurements of light intensity with a light meter. Graphs should then be plotted of light intensity against number of shoots per 0.5m2 and against shoot height. METHOD * Two sites are chosen at random, one north facing the other south facing. A group was assigned to each site. * A light intensity reading was taken in an open area and was accounted for as 100% light intensity. * Starting at a site in a clearing providing a sunny open position, random sampling using 50cm2 quadrats took place. * The number of shoots of dog's mercury within it where recorded and the mean shoot height of five shoots. Light intensity and % canopy cover was also recorded. * Nine further random quadrats were taken, as the group moved further into the dense shaded area of the woodland. * Results were then compared to the other site. RESULTS Influence Of Shading: North Facing. QUADRAT NUMBER NUMBER
Basic Probability, Central Limit Theorem, Sampling and Indexes
Basic Probability, Central Limit Theorem, Sampling and Indexes Mary Margaret Maloney University of Phoenix QRB/501 - Quantitative Reasoning for Business Professor Robert Batiste August 3, 2009 Sevilla & Somers. Topic 18 - Basics of Probability Exploration 3. The following table contains information on the 2002 resident population of the U.S., by age. (Source: The New York Times Almanac 2004, page 277). AGE Younger than 18 years old 8 to 24 years old 25 to 44 years old 45 to 64 years old 65 years and older Number in Thousands ,107,108 452, 196 ,270,419 ,068,243 588,542 Age Count Cumulative Count Younger than 18 years old 1,107,108 1,107,108 18 to 24 years old 452,196 1,559,304 25 to 44 years old 1,270,419 2,829,723 45 to 64 years old 1,068,243 3,897,966 65 years and older 588,524 4,486,508 4,486,508 A. If a resident of the U.S. is chosen at random, find the probability that he or she is 25 to 44 years old. P =
APPLICABILITY OF PROBABILITY SAMPLING TECHNIQUE IN AFRICAN CONTEXT
APPLICABILITY OF PROBABILITY SAMPLINIG TECHNIQUE IN AFRICAN CONTEXT WRITTEN BY NWOSU KINGSLEY.U. M.Sc (CRIMINOLOGY), NNAMDI AZIKIWE UNIVERSITY AWKA, ANAMBRA STATE. OCTOBER, 2012. BACKGROUND Traditionally, probability method involves quantitative form of research which makes use of statistical tools in data presentation and analysis. Sampling is part and parcel of probability technique which involves the process of selecting a sub-set of individuals from within a population to estimate the characteristics of the whole population (Lindsey and Beach 2002). This is because; researchers rarely survey the entire population taking into consideration, the cost, time, and energy. Therefore, to avoid going into a big task, the sample of the entire population is taking to represent the whole. In doing this, the researcher takes into consideration; the validity and the reliability of the sample size. Probability sampling therefore is a method of selecting the elements that would be a representative of the entire population in such a manner that all the elements within the population are given an equal opportunity of being included in the sample. The emphasis here is that each element of the population stands a chance of being included in the sample and not that each element must be included in the sample (Ezeah: 2004). One great importance of this method is that the data collected from
PLAN - Discuss three sampling techniques appropriate to qualitative research
Discuss three sampling techniques appropriate to qualitative research * The purpose is to generate samples that are representative through random selection of participants * Classified as either probability (related to statistical probability and representativeness) or non-probability sampling. * Presents key characteristics of a population which can then be evaluated * Samples are small and not intended to be statistically representative. The three types of sampling: Purposive Sampling * Targets a particular group of people * The participants are chosen on the basis of particular characteristics that will help the researcher to explore their chosen topic. (Important to have diversity) * Useful in situations where the researcher needs to obtain a sample quickly to investigate an urgent problem. * May also be the only option, if the desired population for the study is rare or difficult to locate. * A big problem is that the sample may be biased * Believe that if the sampling process is based on objective criteria, and these are clearly documented or explained, the bias is limited. * Population Validity - cannot generalise from a particular group of people Snowball Sampling * A way of sampling which is used to get hold of participants without investing a lot of time and energy. * Researcher simply asks participants in the study if they know potential
