Sample and Populations Research Methodology:
Any type of research, especially in biological fields involves collection of data related to the problem of study. This data is then compiled, sorted and finally analyzed before arising at a inclusion or result. For the accurate analysis of the data, various statistical methods are employed.
These include classification, tubulation, comparison, correlation and interpretation. The quantitative application of statistical methods to biological facts/ data is known as biometry.
There are two methods by which data can be collected, namely census method and sample method.
(i) Census Method:
In this method, information regarding each member of the population is collected. This method is preferred only when very accurate results are needed. This method is not feasible in certain cases such as quality control, where analysis of each item would render the product useless.
(ii) Sampling Method:
In this method, only a part or fraction of the total population is considered for the actual experiments and data collected from them. The sample is considered as the representative of the total population and conclusions and inferences are drawn on that basis.
Methods of Sampling:
Sample may be selected in two ways-deliberate selection or random sampling.
(i) Deliberate Selection:
In this method, the investigator chooses a few samples from the population, which he thinks are the best representatives of that population. The demerit of this method is that the degree of accuracy is not reliable.
(ii) Random Sampling:
This technique is based on the theory of probability according to which each item of the population has an equal chance of being included in the sample. This method is economical and saves time.
Biological data are usually classified in either of the following ways:
(i) Classification according to attribute
(ii) Classification according to class intervals.
(i) Classification according to Attribute:
This is qualitative grouping where the data are classified on the basis of some attributes which are possessed by the population like intelligence, coIol of hair, etc. This type of classification may be two types:
(a) Simple Classification:
Usually only one parameter is considered, e.g., gender, mental status, literacy status.
(b) Manifold Classification:
Here more than one type of attributes are considered simultaneously, e.g., the students in a class can be divided on the basis of the gender. Also they can be grouped based on their intelligence quotient.
(ii) Classification according to Class Interval:
This type of classification is known as quantitative classification or frequency distribution. Here classification is based on some measurable quantity.
This method can be used in studies related to height, weight, productivity, etc. When a large number of observations varying over a wide range are available, these are classified according to the size of the values. Each of these groups is defined by an interval called class interval or class. Frequency distribution table can be overlapping or non-overlapping.