Further Details: Steve McClure Tel: - +441376 536838 / +447703519426 -----------------------

HS&E bulletin 07/2004

Recently, a serious incident occurred following the sampling of an LPG vessel. The inspector obtained hydrocarbon liquefied gas samples using two gas sample cylinders, commonly called ‘gas bombs’. These cylinders were delivered to a client’s laboratory for testing but the correct procedure for delivering the samples was not followed, partially because it had not been adequately communicated. Within a short time the bursting discs on the cylinders ruptured releasing the gas samples into the laboratory environment. If the releases had been close to live ignition sources or within a vehicle, the results could have been catastrophic.

The subsequent investigation revealed that the immediate cause of the rupture was primarily overfilling of the sample cylinder but further exacerbated by an increase in temperature between the filling source and the ambient laboratory temperature. A root cause was that the inspector had limited training and experience in sampling liquefied gases.

POINTS WORTH REMEMBERING:

➢ Bursting discs will rupture if the ullage space in the cylinder is less than 5%. ➢ Sampling cylinders must be fitted with an ullage tube that is designed to reduce the possibility of overfilling and normally allow an ullage space of approximately 20% to be achieved. ➢ Overfilling can occur if the cylinder is not fitted with an ullage tube, OR ➢ The cylinder is not filled in the vertical position, for example, horizontally, OR ➢ The cylinder is connected to the sampling point upside down with the ullage tube assembly at the bottom, OR ➢ The ullage tube is not ‘vented’.

WHAT YOU CAN DO: -
➢ Follow the procedure “BS EN ISO 4257:2001 Liquefied petroleum gases – Method of sampling”. ➢ Ensure that Inspectors...

...Purposive sampling
Purposive sampling, also known as judgmental, selective or subjective sampling, is a type of non-probability sampling technique. Non-probability sampling focuses on sampling techniques where the units that are investigated are based on the judgement of the researcher.
Purposive sampling explained
Purposive sampling represents a group of different non-probability sampling techniques. Also known as judgmental, selectiveor subjective sampling, purposive sampling relies on the judgement of the researcher when it comes to selecting the units(e.g., people, cases/organisations, events, pieces of data) that are to be studied. Usually, the sample being investigated is quite small, especially when compared with probability sampling techniques.
Unlike the various sampling techniques that can be used under probability sampling (e.g., simple random sampling, stratified random sampling, etc.), the goal of purposive sampling is not to randomly select units from a population to create a samplewith the intention of making generalisations (i.e., statistical inferences) from that sample to the population of interest. This is the general intent of research that is guided by a quantitative research design.
The main goal of...

...Evaluation
Professor: Dr. Elidio T. Acibar
Reporter: Evelyn L. Embate
Topic: SamplingSAMPLING
Measuring a small portion of something and then making a general statement about the whole thing.
Advantages of samplingSampling makes possible the study of a large, heterogeneous population
It is almost impossible to reach the whole population to be studied. Thus, sampling makes possible this kind of study because in sampling only a small portion of the population may be involved in the study, enabling the researcher to reach all through this small portion of the population.
* Sampling is for economy
A research without sampling may be too costly. For an instance if you are to take the whole population, it will take you an expensive cost because of the number of questionnaire copies.
* Sampling is for speed
A research without sampling might be too time consuming. If a research takes a long time to finish, there may be many intervening factors that deter the researcher from finishing his research.
* Sampling is for accuracy
A time too long to cover the whole study population, may ne inaccurate. By the time the last person is interviewed, the data gathered from the first interviewees may be obsolete already so that the conclusions are no longer accurate. It is important that the research must be finished...

...SAMPLING AND ITS CHARACTERISTICS
INTRODUCTION:
For studying any problem it is impossible to study the entire population. It is therefore convenient to pick out a sample out of the population proposed to be covered by the study. Sampling method is an important tool in the realm of social science researches. It was first introduced and used in social research in 1754 A.D. by Bowley.
DEFINITION:
“A sample is finite part of a statistical population whose properties are studied to gain information about the whole.” – Webster Dictionary, 1985
“a smaller representation of large whole.” – Goode and Hatt
‘a subject of cases from the population chosen to represent it.” – Nan Lin
“Sampling method is the process or the method of drawing a definite number of the individuals, cases or the observations from a particular universe, selecting part of a total group for investigation.” – Mildred Parton
Therefore, Sampling can be defined as the method, or the act, process, or technique of selecting a suitable sample, or a representative part of a population for the purpose of determining parameters or characteristics of the whole population. For this, population is divided into a number of parts called Sampling Units.
Or, we can say, that when a small group is selected as representative of the whole it is known as sample.
Or, a sample size is a small percentage of a population that is used for statistical...

...<i>1. State the five assumptions of the Kinetic-Molecular Theory of gases.</i><br><br>a) Gases consist of large numbers of tiny particles. These particles, usually molecules or atoms, typically occupy a volume about 1000 times larger than occupied by the same number of particles in the liquid or solid state. Thus molecules of gases are much further apart than those of liquids or solids.<br><br>Most of the volume occupied by a gas is empty space. This accounts for the lower density of gases compared to liquids and solids, and the fact that gases are easily compressible.<br><br>b) The particles of a gas are in constant motion, moving rapidly in straight lines in all directions, and thus passes kinetic energy. The kinetic energy of particles overcomes the attractive forces between them except near the temperature at which the gas condenses and becomes a liquid. Gas particles travel in random directions at high speeds.<br><br>c) The collisions between particles of a gas and between particles and container walls are elastic collisions. An elastic collision is one in which there is no net loss of kinetic energy. Kinetic energy is transferred between two particles during collisions, but the total kinetic energy of the two particles remains the same, at constant temperature and volume.<br><br>d) There are no forces of attraction or repulsion between the particles of a gas. You can think of ideal gas molecules as...

...Copyright 2010 Graham Elliott. All Rights Reserved.
Sampling
We are now putting all of the pieces together. Considering each observation xi as an outcome from a random variable Xi , we have that functions g(x1 ; x2 ; :::; xn ) are draws from the random variable
Pn g(X1 ; X2 ; :::; Xn ):
For 120a the function we are interested in is the sample mean — g(x1 ; x2 ; :::; xn ) = n1 i=1 xi : In this chapter
we work with this function for distributions with many random variables.
1
From the Text
Question 1. Problem 6-10, p.206
Question 2: Problems 6-16,6-22.
Question 3: Problem 6-36.
2
Sampling Questions
Question 1. A study suggests that in a trial of 50 people the average decrease in cholestorol from using a
particular drug is 18 points with a standard deviation of 10 points.
(a) What is the chance that, given the true e¤ect is a reduction of 20 points, that a particular person
has no decrease in cholestorol when they take this drug?
(b) A reporter writes a newspaper article discussing the drug. They report that although the study claims
that the reduction is 18 points, they have found a user that actually had no change to their cholestorol. They
use this persons story to argue that the results are misleading. What is the chance that, if the real e¤ect
was zero, that the average in a trial might be 18 just by chance?
(c) Is the counter example found by the reporter useful in understanding the results for the study?
Question 2. In the questions...

...“Deciding on a sampling procedure for a study on understanding teaching and learning relations for minority children in Botswana classrooms”
Sampling is a very important statistical tool used by researchers to find accurate results that represents the complete attributes of population.
Different types of sampling are used for different type of data. For example: probability sampling is used for quantitative data as attributes of such data can easily be generalized to population.
While dealing with the qualitative data, on probabilistic methods of sampling are used because such data represents social attributes. Researchers use generalization, comparability, totalization or transitivity methods for qualitative data.
To understand the learning and teaching relations of minority children in Botswana school, we have to understand the social, cultural and learning environment of such kids. Then the role of teacher and their teaching methods are analyzed.
Researchers like Le Compte, Preissle and Merriam say that population or data units are basics to determine the sampling procedures that are used for sampling.
As per the nature of the analyzing learning and teaching relations of Botswana children, we use purposive sampling strategy to analyze difference between school sites.beacause
Purposive...

...Sampling is the use of a subset of the population to represent the whole population. Probability sampling, or random sampling, is a sampling technique in which the probability of getting any particular sample may be calculated. Nonprobability sampling does not meet this criterion and should be used with caution. Nonprobability sampling techniques cannot be used to infer from the sample to the general population.
The advantage of nonprobability sampling is its lower cost compared to probability sampling. However, one can say much less on the basis of a nonprobability sample than on the basis of a probability sample. Of course, research practice appears to belie this claim, because many analysts draw generalizations (e.g., propose new theory, propose policy) from analyses of nonprobability sampled data. One must ask, however, whether those published works are publishable because tradition makes them so, or because there really are justifiable grounds for drawing generalizations from studies based on nonprobability samples.
Some embrace the latter claim, and assert that while probability methods are suitable for large scale studies concerned with representativeness, non-probability approaches are more suitable for in-depth qualitative research in which the focus is often to understand complex social phenomena (e.g., Marshall 1996; Small 2009). These assertions...

...
6 Types of Probability Sampling
Simple Random - Each element in the population has an equal probability of selection and each combination of elements has an equal probability of selection.
Systematic Random - Each element has an equal probability of selection, but combinations of elements have different probabilities.
Stratified Random - Divides population into groups that differ in important ways. The basis for grouping must be known before sampling. Researcher selects random sample from within each group.
Random Cluster - If done correctly, this is a form of random sampling. Population is divided into groups, usually geographic or organizational.
Stratified Cluster - Reduce the error in cluster sampling by creating strata of clusters. Researcher samples one cluster from each stratum. Possesses the cost-savings of clustering with the error reduction of stratification.
Complex Multi-Stage Random – Multi-stage sampling is a complex type of cluster sampling. Multi-stage sampling is used in researches where the entire universe is very large, for example the entire country. The researcher selects samples in various levels.
4 Types of Non Probability Sampling
Convenience (Accidental) Sample - units are selected on the basis of availability
Quota Sample - units are selected on the basis of availability with "quotas" being selected...