Descriptive Statistics
Introduction
Tests, experiments and studies in psychology provide valuable information, most of
the time in numerical scores, known as data. Data in its raw form has little meaning for the
reader and in order to be able to understand and interpret the data it needs to be arranged in a
systematic way. Descriptive statistics involves describing, organizing, presenting and
summarizing data via numerical calculations, graphs or tables. Descriptive statistics is useful
for two reasons- first, it provides basic information about a particular population or data set
and second, it helps highlight possible relationships between variables.
Graphical Representation of Data
Graphical or pictorial methods provide a visual representation of data, therefore
enhancing a researcher’s understanding of variables and the relationship between them. There
are various different methods for the graphical representation of data which include
histograms, frequency distributions, scatter plots, contingency tables etc.
Measures of Central Tendency
The most basic yet one of the most important and informative aspect of descriptive
statistics are the Measures of Central Tendency. They provide information regarding the
“average” of the population being studied. Measure of central tendency may be defined as a
sort of average or typical value of items in the series and its function is to summarize the
series in terms of this average value (Tate, 1955).
First, the mean also known as the arithmetic mean may be considered the most useful
measure of central tendency, it is the average computed. That is, the sum of all the variables
values divided by the number of values.
Second, the median is the middle value in a set of values arranged in and ascending or
descending series. Therefore, the median of distribution is the point on the scale below which
half of the scores fall. The central item itself is not the median but rather, it is the measure or
value of the central item.
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