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The Role of Statistics in Decisionmaking

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It is from this data we get to know more information about the population or universe. The data is obtained from a small portion of a population (sample), carefully selected to represent all population. Analyzing such a small data is easier and cheap as compared to analyzing the whole population. It is worth noting that population is either infinite or finite and sometimes, in the process of analyzing, a sample may be destroyed e.g. testing compression strength in concrete bricks. Therefore, it is advisable that the sample must be representative of the population so that whatever conclusion made based on the sample infer also to the population. This is never absolutely certain hence inductive or statistical inference. The phase of statistics that only describe and analyze a given data without drawing conclusions or inferences about a population is a descriptive or deductive statistic (Murray amp. Larry, 1999).
Variable is a symbol representing the aspect being investigated. This can be a height of trees or students, rebound strength value on the brick. It is constant when a variable takes one value otherwise it is either continuous or discrete. Discrete variables are variables whose values are integers i.e. 1, 2, 3, 4, 5… Examples are number of children in a family, number of cows in a flock etc. on the other end, continuous variable takes all values including those between the integers of the domain. An example is the height of students in college (Murray amp. Larry, 1999).