Descriptive and Inferential Statistics - Essay Example

The role of descriptive statistics is to organize, summarize, and describe the given data. The fundamental idea employed in this type of statistical application is that it summarizes a set of data with one number or graph. Furthermore, it should be noted that this type of statistic is cannot be used to produce generalizations, but only to summarize the values and to describe data based on one or more samples. , they too are called descriptive. On the other hand, inferential statistics as the name implies is purposely to draw conclusions as well as to draw inferences, or to generate predictions on a given population derived from sample data.

It is also one method that takes account of the variables, the moment samples are used to arrive at the conclusions (or formulate inferences about). Like for instance, if a teacher would like to find out if teaching strategies affect the learning of the students or if there is a significant difference in the performances of the two classes; if the physician would like to determine if one antibiotic is more effective than the other; also if an environmentalist is curious and would search whether environmental factors like tides and rainfall is related to global warming.

Inferential statistics is normally geared towards creating inferences on a large group of people through the collection of data from a small component of its sample size. Unlike descriptive statistics, inferential statistics techniques are not too common to many people, and most often used techniques that serve to draw out inferences are the t-tests, Chi-Square, and the Analysis of variance or ANOVA. As with this type of statistics, there are other types of inferential statistics tests depending on the nature of categories of data (ordinal, nominal, interval or ratio scaled), the sample size, the number of the samples being analyzed as well as the relationships of that samples being analyzed.

In the totality, experts in statistics and researchers express research problems and their solutions through statistical terminology. To simulate the behavior, mathematical representations can be expressed; while academic resources such as textbooks, journals, and periodicals that contain significant knowledge-based information employ statistical jargon.