Quantitative Research Methods for Social Scientists: Levels of Measurement, Central Tendency, Dispersion, Descriptive vs Inferential Statistics, SPSS Output Interpretation

LC572 Quantitative Research Methods
for Social Scientist

TABLE OF CONTENTS
Presenting four level of measurement.........................................................................................1
Measure of Central tendency and Measure of Dispersion...........................................................1
Difference between Descriptive statistics and Inferential Statistics............................................1
Definition.....................................................................................................................................2
Interpretation of SPSS output......................................................................................................2
REFERENCES................................................................................................................................4

Presenting four level of measurement
The four level of measurement are as mentioned below:
 Nominal: In this, the data can be categorized and mainly used for qualitative labels. For
example, in a survey, it is mention about gender then it can be categorizing into two form
i.e. male and female.
 Ordinal: Under this, data is ranked from higher to lower like likert scale in which options
are provided in the form of strongly disagree, disagree, neither agree nor disagree, agree,
strongly agree (Marees and et.al., 2018).
 Interval: There is a space interval between each of the values in order to show the value.
For example, the temperature in Fahrenheit with a difference between 10 and 20 degrees.
 Ratio: The data used under this measurement ranked evenly spaced and also has a natural
zero (Salkind and Frey, 2021). For example, weight which can be in a zero however,
value of temperature cannot be measured under this, as it cannot be a zero.
Measure of Central tendency and Measure of Dispersion
Measure of central tendency is all about numbers that are tend to be cluster around the
middle of the values (Chakrabarty, 2021). In this, mean, mode and median are fall that describe
the different indication of a typical value distribution.
Measure of dispersion is estimated the normal value of a dataset which is also an
important part that helps to describe the spread of a data and variable towards a dataset. In this,
range, interquartile range, standard deviation and variance are fall that provide measure of
variability (Campbell, 2021).
Difference between Descriptive statistics and Inferential Statistics
Descriptive statistics is mainly concerned with describing a population under a study and
in this, the data is organised in such a well manner way that helps to determine the results.
However, under inferential statistics, observation is performed in order to draw conclusion in
better manner (Ali, Bhaskar and Sudheesh, 2019). Inferential test mainly compares, test and
predicts data and provide results in the form of probability. The main function of descriptive
statistics is to summarise the sample whereas inferential statistics try to reach in a conclusion by
examining about the population. That is why, it can be stated that descriptive statistics
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