Page 92 - DMGT404 RESEARCH_METHODOLOGY

Research Methodology

Notes them. However, it must be recognized that the zero point on an interval scale is arbitrary and is
not a true zero. This, of course, has implications for the type of data manipulation and analysis
we can carry out on data collected in this form. It is possible to add or subtract a constant to all
of the scale values without affecting the form of the scale but one cannot multiply or divide the
values. It can be said that two respondents with scale positions 1 and 2 are as far apart as two
respondents with scale positions 4 and 5, but not that a person with score 10 feels twice as
strongly as one with score 5. Temperature is interval scaled, being measured either in Centigrade
or Fahrenheit. We cannot speak of 50°F being twice as hot as 25°F since the corresponding
temperatures on the centigrade scale, 100°C and -3.9°C, are not in the ratio 2:1.
Interval scales may be either numeric or semantic.

Characteristics

1. Interval scales have no absolute zero. It is set arbitrarily.
2. For measuring central tendency, mean is used.
3. For measuring dispersion, standard deviation is used.

4. For test of significance, t-test and f-test are used.
5. Scale is based on the equality of intervals.
Use: Most of the common statistical methods of analysis require only interval scales in order
that they might be used. These are not recounted here because they are so common and can be
found in virtually all basic texts on statistics.

Example:
1. Suppose we want to measure the rating of a refrigerator using interval scale. It will appear
as follows:
(a) Brand name Poor …………………… Good
(b) Price High …………………….. Low
(c) Service after-sales Poor …………………… Good

(d) Utility Poor …………………….Good
The researcher cannot conclude that the respondent who gives a rating of 6 is 3 times more
favourable towards a product under study than another respondent who awards the rating
of 2.
2. How many hours you spend to do class assignment every day?
(a) < 30 min.

(b) 30 min. to 1 hr.
(c) 1 hr. to 1½ hrs.
(d) > 1½ hrs.
Statistical implications: We can compute the range, mean, median, etc.

Task Analyse the difference between interval and ordinal scales.

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