Sample Method of Collection of Data
Meaning of Population:
A population is a pool of similar objects, items, or events that are used to define the subject of study, which is related to some questions or events under study. In statistics, it means the aggregate of all items about which we want to collect information.
The population can be of any size, it can be large as well as small and can have a varying number of characteristics. While statistics population can be vague as well as specific depending on what the statistician desire.
Example: The entire student body in a University or the population might be all the apples in an orchard at any given time.
Meaning of Sample:
The sample is a subset of a population selected to represent the population as a whole. In research, a population does not only mean the human population all the time, it can be factories or schools. The population is denoted by the capital N and the sample by n. The method chosen to take the sample depends on the nature of the population and the resources available in terms of time and money. In an unbiased sample, the ideal state for each object in a population is likely to be equally chosen as a part of the sample. It is also desirable for the sample to be representative of the population.
For example, A population can be all the apples in an orchard at any given time. Now, if we wish to measure how big the apples are, then we cannot measure all of them, so we take a sample and measure them. So here the sample will be a small lot of apples, which we choose to measure the apples, which adequately represent the whole population.
Meaning of Sample Method:
The sample method is a method in which data is collected about a sample on a group of items taken from the population for examination, and conclusions are drawn from it.
Suitability of Sample Method:
- Large Sample Size: To use this method of sampling, a large sample size is required because in case if the sample size is too small, then this could give inaccurate and inefficient results. This method requires managing a small portion of overall demographics.
- Low Accuracy: As in this method, every member of the population does not get studied for the research or data collection, instead a small sample is selected out of the population, which is considered to be a true representation of the whole population. So here, a researcher cannot expect a very high level of accuracy, as the results can vary from sample to sample selected based on a different method. Therefore, this method is generally suitable for those research in which a very high level of accuracy is not expected.
- Intensive Examination of the Diverse Items: This method can be used for data collection in those cases where there is no compulsion that every member of the population is to be considered for carrying out the research.
- Uniformity: In cases where it is visible that every other member of the population is a true representation of each other, then this method is very apt to apply, as samples can be chosen very accurately out of the population, which can give desired results.
Merits of Sample Method:
- Economical: This method of investigation is economical because only some units of the population are studied.
- Time-saving: In this method, only a limited number of items are investigated out of the whole population, so investigation time is time-saving instead of time-consuming.
- Identification of Error: Because this method covers only a limited number of items, so errors can be identified easily. To that extent, the sample method shows better accuracy.
- Large Investigation: The sample method is more feasible in those situations where a large area of investigation is involved as compared to those methods where there is a small area of investigation. So, this method involves affordable cost as compared to the unaffordable cost of other methods.
- Administrative Convenience: There is an administrative convenience in handling a limited number of items because of which more capable and efficient investigators can be appointed.
- More Scientific: This method is more scientific because the sample data can be conveniently investigated from various angles.
Demerits of Sample Method:
- Partial: It is only a partial investigation of the universe or the population. The investigator’s bias in the selection of the sample can not be ruled out. Accordingly, the result can be biased as well.
- Wrong Conclusion: If the selected sample does not represent the characteristics of the universe, the study may end up with wrong conclusions, as only the sample is selected from the population, which is considered representative of the whole population, and if the wrong sample gets selected, then the results of the study will be of no use.
- Difficulty in Selecting Representative Sample: It is not very easy to select a sample that would represent the characteristics of the entire population, as sometimes it can happen that the population is quite diverse so in such cases, it becomes difficult to select those samples which are the right representative of the whole population.
- Difficulty in Framing a sample: Sometimes the universe may be so diverse that it becomes difficult to frame a sample.
- Specialized Knowledge: To be effective, the sampling technique requires a particular level of specialized knowledge. If the service of experts is not used in the collection and analysis of sample data, the results of the investigation are likely to be unsatisfactory.
Essentials of Sample:
- Adequacy: The number of items in the sample should be fairly adequate so that some reliable conclusions can be drawn, which will cover the characteristics of the universe as a whole.
- Representative: A sample must represent all the characteristics of the universe. It is possible only when each unit of the universe stands an equal chance of being selected in the sample. Therefore the probability of each member of the population should always be the same.
- Homogeneity: If more than one sample is selected from a universe, these samples should be homogeneous( and not contradictory) to each other.
- Independent: All units of a sample must be independent of each other. In other words, the inclusion of one item in the sample should not be dependent upon the inclusion of some other items of the universe.