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**Statistics** refers to collecting, presenting, interpreting and making sense of numerical facts to draw sensible conclusion. In psychology there are enormous data that has been collected or observed which needs viable interpretation to make usable conclusion for the study or research. These study or research are done by psychologists to measure psychological attributes using tests or scales to describe individuals or at times, there are also measurements used for describing general properties of people or animals.

Statistics provides vital services

- To collect evidences or facts and these can be either numerical or otherwise.
- For the organization, classification and summarization of numerical data.
- To test a hypothesis and to determine whether it should be accepted or rejected.
- To draw inferences, conclusions or make predictions on the basis of facts, evidences, and particulars.

**Evaluation and Measurement:** Various tests and measures that are used in the field of psychology carry out the task of evaluation and measurement which are to be constructed and standardized. Such tests may include achievement tests, attitude scales, social distance scales, intelligence tests, aptitude tests, and interest inventories among others. With the help of statistical methods not only are construction and standardization carried out for these tests and measures but even the proper presentation, comparing, analysis, and interpretation of the results can be done.

**Research:** There is abundant research work in psychology where the researchers need to use statistical methods. They are useful for any researchers doing their research as they enable the accurate description, summarization of results in a meaningful and convenient form, to predict and draw conclusions, and to analyze the causal factors that may be underlying any complex or bizarre events. Researchers or even teachers, students, social workers, psychologists and educationists can use statistics and its methods to their advantage to keep track of the latest research and developments. Through this, they get help to simplify the reports of applied and theoretical research including the statistical terms used in it. And with proper knowledge of statistics, interpretation and correct use of the results of these researches will become feasible. Through these usages, it can be concluded that through statistics contribution and enrichment can be done significantly for useful research and innovations which also benefits both the society and humanity as a whole.

**Day-to-Day Tasks:** There are numerous day-to-day tasks that psychologists, researchers, students and teachers need to carry out where statistics will be crucial to make the tasks easier. These tasks may include knowing the individual difference of subjects, to compare the aptness of one technique to the other, to maintain various types of records, to compare results of one type of evaluation to the other, to collect important information through a survey, to survey and carry out tasks of guidance and reporting, to make predictions on the future progress of student, etc.

In psychology, there are certain variables that can be found in subjects or individuals. These differences may be found in age, sex, attitude, intelligence, height and weight, education, religion, attitude towards women, etc. Generally, the variables are classified into two- continuous and discontinuous or discrete variables.

**Continuous Variables:** Continuous variables are continuous series that are capable of showing no real gaps in any degree of sub-division and in practice. Hence, this variable can remain continuous by indefinitely small changes even when it passes from one value to the next. To identify continuous variable a question should be posed on if the smallest degree of measurement can be applied on that variable. Hence, weight, height, temperature, and length are examples of this variable as they can be measured in different measurements. The variables that are mostly dealt in psychology are continuous or treated as continuous instead of discontinuous or discrete.

**Discontinuous or Discrete Variables:** In contrast, discontinuous or discrete variables form a discontinuous or discrete series which exhibits real gap. Therefore, when there are real gaps between one value and the next, a variable is said to be in discontinuous or discrete form. The data of this variable unlike continuous variables can only be expressed in whole units which are numbers. For example, the number of children in a family, the number of cars in a family, the number of schools in a town, and the number of books in the library.

To conduct statistical analyses, measurement of variables is needed. Different types of variables involved in the analysis are measured differently. Hence, there are various scales employed for measurements that are listed below:

**Nominal Scale:**In this scale there are simply names, responses, numbers or symbols. The imperative point regarding nominal scale is that there is no ordering of responses and to not assign the same numeral or objects to different classes, individuals or objects and vice versa. Hence, in nominal scale based on similarities or differences observed in a characteristic or property, classification or numbering is always made. Due to this, the functioning of nominal scale only enables the making of statements based on difference or equality.**Ordinal Scale:**As compared to nominal scale which only serves as labels to identify objects or individuals, ordinal scale allows comparison to inspect the degree of dependent variable two subjects or individuals may possess. The numbers in ordinal scale represent a subject or individual’s merit position or rank order that they may hold within their own class or group in regards to property, performance or quality. However, this scale fails to capture principal information that other scales might possess as the units along the scale are not equal in size. Assumptions on the parity of two levels of an ordinal scale with other levels cannot be made as they are not necessarily equal. Nevertheless, there are numerous cases where ordinal scale and measures are used in the field of psychology. Few statistical methods like percentiles, rank order correlation coefficient, and median can be enumerated using these data.**Interval Scale:**This type of scale is much more advanced than the nominal and ordinal scale as it specifies both the relative quantitative and qualitative differences. And unlike ordinal scale which does not have parity of difference between two levels, interval scale has consistent intervals of same interpretation throughout its scale. The examples of this scale are Centigrade and Fahrenheit thermometers. However, interval scale has its setback as it does not possess a true zero. Hence, on testing a subject with intelligence test, no psychologists, researchers or anyone from the field of psychology conducting this test can conclude that the subject has zero intelligence based solely on standard scores provided in that intelligence tests. This is the reason why approximation and estimates are usually used in psychology rather than exact computation or true measurements.**Ratio Scale:**This type of scale is the highest and final in terms of measurement and is considered the most informative. Here the measures are expressed in equal units and are also taken from a true zero. In this scale, true zero indicates that there is an absence of either quality or attribute being assessed or measured. Additionally, if there is a same ratio at two places present on the scale, they also carry the same meaning. Few examples of such scales are the measures of width, length, capacity, weight, and loudness. However, this type of measures or measurement scales is hardly found in the field of psychology.

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