Mathematics

Methods used in Data Collection and Interpretation



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All psychological theories are based on the interpretation of data that is either collected or observed. The manner in which this is interpreted is aided by several techniques or “tools” that help with categorizing data. The following are some of the primary methods in data collection and interpretation techniques:

—Most often, collected data will initially be divided into a table, which helps to classify, list, and name the data collected from whatever study has been conducted. Having information readily available in this format is a helpful starting point to assessing data.

—Another tool in data assessment is the graph. Graphs are commonly used when tracking trends in the data collected, we are then able to view a more wider perspective of the relation between one set of values against another. Graphs are used by scientists, economists, and many other professions to show the relation of one value against another.

—Histograms are a graphical illustration that divide data into bars that show the distribution of numbers within certain groups. They generally illustrate the number of subjects that fall under each class interval. Histograms are useful when needing to assess a large amount of data within a set, as it aids in evaluating the amount of variation within a given data set.

—Finding the average (or mean) in a set of numerical data is calculated by adding all of the given scores together and dividing by the number of scores. This is helpful to know when assessing a midpoint between a range of scores. To find the “range” (which is the difference between the highest and lowest scores), you would subtract the lowest score from the highest score, and plus one.

—When assessing the closeness and direction of the relationship between two variables, correlation data is presented in a scattergram. Scattergrams are marked on a graph chart by small marks. If the marks rise from the lower left to the upper right, then the variables have a positive correlation.

In any of the realms of science, or within any profession or sphere of knowledge that must analyze and interpret data, one or more of the above methods are used in order to interpret the raw data that has been collected or analyzed. The data is then studied using the above means to evaluate whether the results support or refute a hypothesis, or to analyze and find new trends or patterns that develop into new theories.

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