Advantages And Disadvantages Of Sampling Techniques Pdf

advantages and disadvantages of sampling techniques pdf

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Simple Random Sample: Advantages and Disadvantages

Data is gathered on a small part of the whole parent population or sampling frame, and used to inform what the whole picture is like. Therefore an appropriate sampling strategy is adopted to obtain a representative, and statistically valid sample of the whole.

The sample size chosen is a balance between obtaining a statistically valid representation, and the time, energy, money, labour, equipment and access available. Most approaches assume that the parent population has a normal distribution where most items or individuals clustered close to the mean, with few extremes.

This also means that up to five per cent may lie outside of this - sampling, no matter how good can only ever be claimed to be a very close estimate. Least biased of all sampling techniques, there is no subjectivity - each member of the total population has an equal chance of being selected.

Type that into a cell and it will produce a random number in that cell. Copy the formula throughout a selection of cells and it will produce random numbers. You can modify the formula to obtain whatever range you wish, for example if you wanted random numbers from one to , you could enter the following formula:. These can then be used as grid coordinates, metre and centimetre sampling stations along a transect, or in any feasible way. Pairs of coordinates or grid references are obtained using random number tables, and marked on a map of the study area.

Random number tables generate coordinates or grid references which are used to mark the bottom left south west corner of quadrats or grid squares to be sampled. Can lead to poor representation of the overall parent population or area if large areas are not hit by the random numbers generated. This is made worse if the study area is very large. There may be practical constraints in terms of time available and access to certain parts of the study area.

A grid can be used and the points can be at the intersections of the grid lines, or in the middle of each grid square. Sampling is done at the nearest feasible place. The eastings or northings of the grid on a map can be used to identify transect lines. Alternatively, along a beach it could be decided that a transect up the beach will be conducted every 20 metres along the length of the beach. Patterns can be any shape or direction as long as they are regular.

This method is used when the parent population or sampling frame is made up of sub-sets of known size. These sub-sets make up different proportions of the total, and therefore sampling should be stratified to ensure that results are proportional and representative of the whole.

The population can be divided into known groups, and each group sampled using a systematic approach. The number sampled in each group should be in proportion to its known size in the parent population.

For example: the make-up of different social groups in the population of a town can be obtained, and then the number of questionnaires carried out in different parts of the town can be stratified in line with this information. A systematic approach can still be used by asking every fifth person. A wide range of data and fieldwork situations can lend themselves to this approach - wherever there are two study areas being compared, for example two woodlands, river catchments, rock types or a population with sub-sets of known size, for example woodland with distinctly different habitats.

Random point, line or area techniques can be used as long as the number of measurements taken is in proportion to the size of the whole. For example: if an area of woodland was the study site, there would likely be different types of habitat sub-sets within it. The sample points could still be identified randomly or systematically within each separate area of woodland. If the proportions of the sub-sets are known, it can generate results which are more representative of the whole population.

It can be hard to stratify questionnaire data collection, accurate up to date population data may not be available and it may be hard to identify people's age or social background effectively. By placing a booking, you are permitting us to store and use your and any other attendees details in order to fulfil the booking.

We will not use your details for marketing purposes without your explicit consent. Please login to continue. Cookies on the RGS website This site uses cookies to enhance your user experience. Back to Resources for schools. Sampling techniques. What is sampling? A shortcut method for investigating a whole population Data is gathered on a small part of the whole parent population or sampling frame, and used to inform what the whole picture is like Why sample? Methodology A. Random line sampling Pairs of coordinates or grid references are obtained using random number tables, and marked on a map of the study area These are joined to form lines to be sampled C.

Random area sampling Random number tables generate coordinates or grid references which are used to mark the bottom left south west corner of quadrats or grid squares to be sampled Advantages and disadvantages of random sampling Advantages: Can be used with large sample populations Avoids bias Disadvantages: Can lead to poor representation of the overall parent population or area if large areas are not hit by the random numbers generated. This is made worse if the study area is very large There may be practical constraints in terms of time available and access to certain parts of the study area Systematic sampling Samples are chosen in a systematic, or regular way.

Systematic point sampling A grid can be used and the points can be at the intersections of the grid lines, or in the middle of each grid square. Systematic line sampling The eastings or northings of the grid on a map can be used to identify transect lines. Alternatively, along a beach it could be decided that a transect up the beach will be conducted every 20 metres along the length of the beach C.

Advantages and disadvantages of systematic sampling Advantages: It is more straight-forward than random sampling A grid doesn't necessarily have to be used, sampling just has to be at uniform intervals A good coverage of the study area can be more easily achieved than using random sampling Disadvantages: It is more biased, as not all members or points have an equal chance of being selected It may therefore lead to over or under representation of a particular pattern Stratified sampling This method is used when the parent population or sampling frame is made up of sub-sets of known size.

Stratified systematic sampling The population can be divided into known groups, and each group sampled using a systematic approach.

Stratified random sampling A wide range of data and fieldwork situations can lend themselves to this approach - wherever there are two study areas being compared, for example two woodlands, river catchments, rock types or a population with sub-sets of known size, for example woodland with distinctly different habitats.

Advantages and disadvantages of stratified sampling Advantages: It can be used with random or systematic sampling, and with point, line or area techniques If the proportions of the sub-sets are known, it can generate results which are more representative of the whole population It is very flexible and applicable to many geographical enquiries Correlations and comparisons can be made between sub-sets Disadvantages: The proportions of the sub-sets must be known and accurate if it is to work properly It can be hard to stratify questionnaire data collection, accurate up to date population data may not be available and it may be hard to identify people's age or social background effectively Further details about sampling can be found within our A Level Independent Investigation Guide.

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Sampling Definition, Advantages and Disadvantages

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Suppose you have to run a survey about the coffee drinking habits of high school students of USA. The population of the students is about 4 million. You can not even imagine running the survey by asking each and every student to get the relevant data because of requirement of huge amount of time, money and other resources. The cost of the survey in this case would be too monumental to justify the effort. To solve these types of problem, sampling can be used. In simple terms, sampling is the process of selection of limited number of elements from large group of elements population so that, the characteristics of the samples taken is identical to that of the population. In above examples, suppose you choose students among 4 millions students.

In probability sampling, each population member has a known, non-zero chance of participating in the study. Randomization or chance is the core of probability sampling technique. In non-probability sampling , on the other hand, sample group members are selected non-randomly; therefore, in non-probability sampling only certain members of the population has a chance to participate in the study. You chose survey primary data collection method to achieve research objectives. Identifying an appropriate sampling frame based on your research question s and objectives. ABC Company has employees and accordingly, your sampling frame would be

Simple Random Sample: Advantages and Disadvantages

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Data is gathered on a small part of the whole parent population or sampling frame, and used to inform what the whole picture is like. Therefore an appropriate sampling strategy is adopted to obtain a representative, and statistically valid sample of the whole. The sample size chosen is a balance between obtaining a statistically valid representation, and the time, energy, money, labour, equipment and access available. Most approaches assume that the parent population has a normal distribution where most items or individuals clustered close to the mean, with few extremes.

Sampling may be defined as the procedure in which a sample is selected from an individual or a group of people of certain kind for research purpose. In sampling, the population is divided into a number of parts called sampling units. Sampling ensures convenience, collection of intensive and exhaustive data, suitability in limited resources and better rapport.

Type of Sampling

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Sampling techniques: Advantages and disadvantages. Technique. Descriptions. Advantages. Disadvantages. Simple random. Random sample from whole.

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