RESEAECH METHODOLOGY

UNIT - III

QUANTITATIVE & QUALITATIVE DATA

TYPES OF DATA NOMINAL DATA-- The observations on

qualitative variables may also be assigned numbers. The categorical data can be made into numerical data .

Ex: recording yes or no answers to a question as ‘0’ and ‘1’.

This data do not share the properties of numbers, like greater or less or difference.

ORDINAL DATA In situations when we can not do any

thing except set up inequalities ,it is referred as ordinal data.

Ex: the hardness of minerals can be referred as 1 to 10 like talc-1, gypsum-2 , calcite-3 ,fluorite-4, apatite-5, feldspar-6, quartz-7, topa-8, sapphir-9 and diamond-10.we can write 5>2 or 6<9 as apatite is harder than gypsum and feldspar is softer than sapphire.

INTERVAL DATA In addition to setting up inequalities ,if

we can form differences it is known as interval data.

Ex: temperature readings 58˚,63˚,70˚,95˚,110˚, 126˚. We can write 100˚>70˚, or 95˚>135˚

also95˚--70˚=135˚--110˚. Also 126˚does not mean that it is twice

as hot as 63˚.

RATIO DATA In addition to setting up inequalities

and forming differences we can also form quotients, which includes all the usual measurement of length , height, money etc.

MEASUREMENT & SCALING

MEASUREMENT

MEASUREMENT

The process of assigning numbers to objects or observations, the level of measurement being a function of the rules under which the numbers are assigned is known as measurement.

MEASUREMENT SCALES The scales of measurement can be

considered in terms of their mathematical properties.

CLASSIFICATION OF MEASUREMENT SCALES

NOMINAL SCALE This is simply a system of scales

assigning number symbols to events in order to label them.

This scale provides convenient ways of keeping track of people , objects and events .

Ex: answers to certain questions like yes or no can be recorded as 0 or 1.

ADVANTAGES Nominal scale is the least powerful level of

measurement. It indicates no order or distance relationship and

has no arithmetic origin. This is very useful and are widely used in surveys. This scale is restricted to use mode as the measures

of central tendency. The most common test of statistical significance that

can be utilized is the Chi-square test. The measures of correlation that can be worked out is

the contingency coefficient. There is no generally used measure of dispersion for

nominal scales.

ORDINAL SCALE

This scale places events in order, but there is no attempt to make the intervals of the scale equal in terms of some rule.

Ex: Role numbers of 5 students in class is as follows,Anu—1, Binu—2, Dinu—3, Hema—4, Rinu—5, in this Rinu’s number is 5 but it doesn’t mean that she is superior to Anu , Binu, Dinu or Hema.

ADVANTAGESOrdinal scales are frequently used in research relating to

qualitative phenomena. This scales only permits the ranking of items from highest

to lowest. These have no absolute values. The real differences between adjacent ranks may not be

equal. The appropriate measure of central tendency is median. The measures of correlations are restricted to various

rank order method. The measures of statistical significance are restricted

to non-parametric methods. The measures of dispersion used is percentile or

quartile.

INTERVAL SCALE

In this intervals are adjusted in terms of some rule that have been established as a basis for making the units equal.

Ex: An increase in temperature from 30˚to 40˚involves the same increase in temperature 60˚ to 70˚, but one cannot say that the temperture of 60˚ is twice as warm as the temperture of 30˚.

ADVANTAGES Interval scales provide more powerful

measurement than ordinal scales. These scales have an arbitrary zero, but not

possible to determine the unique origin or absolute zero.

The appropriate measure of central tendency is the Mean.

The correlation techniques used is product moment correlation.

The generally used statistical significance are the t—test and F—test .

The mostly used measure of dispersion is standard deviation.

RATIO SCALES

This scales represents the actual amount of variables.

Ex: weight , height, distance etc.

ADVANTAGES All statistical techniques are usable with ratio

scales. This scales have an absolute or true zero of

measurement. The measures of central tendencies are geometric

and harmonic means. The measures of dispersion can be calculated using

coefficients of variation. The ratio involved does have significance and

facilities , a kind of comparison which is not possible in case of an interval scale.

Ex: Jyothi’s typing performance was twice as good as that of Reetu.

CONCLUSION Thus proceeding from the least precise type of

scale, the nominal scale to the most precise type of scale, the ratio scale relevant information is obtained increasingly.

A researcher should use the scale that provides the most precise description if the nature of the variables permits.

Ex: Physical science researchers are generally limited to describe variables in ratio scale form while Behavioral science researchers are generally limited to describe variables in interval scale form.

GOODNESS OF MEASUREMENT SCALES

VALIDITY This is the most critical criterion

and indicates the degree to which an instrument measures what it is supposed to measure.

It can also be thought of as utility. There are three types of validity Content validity, criterion—related

validity, construct validity, Accuracy.

1.CONTENT VALIDITY This is the extent to which a measuring

instrument provides adequate coverage of the topic under study.

If the instrument contains a representative sample of the universe , the content validity is good.

It can also be determined by using a panel of persons who shall judge how well the measuring instruments meets the standards, but there is no numerical way to express it.

2. CRITERION—RELATED VALIDITY

This relates our ability to predict some outcome or estimate the existence of some current condition.

This form of validity reflects the success of measures used for some empirical estimating purpose.

This must possess the qualities like Relevance(proper measure), Freedom from bias(when criterion gives each subject an equal opportunity to score well), Reliability (stable or reproducible), Availability (Information must be available).

This validity is a broad term which refers a) Predictive validity ( the usefulness of a test in

predicting some future performance) b) Concurrent validity (the usefulness of a test in closely

relating to other measures of known validity)

3.CONSTRUCT VALIDITY This is the most complex and abstract

validity. It is the degree to which scores on a test can be accounted for by the explanatory constructs of a sound theory.

For determining construct validity associate a set of other propositions with the results received from using our measurement instrument.

If measurements in our devised scale correlate in a predicted way with these other propositions ,we can conclude that there is some construct validity.

RELIABILITY A measuring instrument is reliable if it

provides consistent results. A valid instrument is always reliable. Two aspects of reliability are stability and

equivalence. stability is concerned with securing consistent

results with repeated measurements of the same person and with the same instruments.

Equivalence considers how much error may get introduced by different investigators or different samples of the items being studied.

PRACTICALITY This characteristic of a measuring instrument can

be judged in terms of economy, convenience and interpretability.

Economy consideration suggests some trade—off is needed between the ideal research project and that which the budget can afford.

Ex: the length of measuring instrument is an important area where economic pressures are quickly felt. More items may give reliability but in order to limit the observation time or interview time we have to take only a few items.

Similarly data collection methods to be used are also dependent at times upon this factor.

Convenience test suggests that the measuring instrument should be easy to administer.

Ex: a questionnaire with clear instructions(illustrated by examples) is certainly more effective and easier to complete.

Interpretability consideration is specially important when persons other than the designers of the test are to interpret the results.

In order to be interpretable, the measuring instruments must be supplemented by

a) detailed instructions for administering the tests

b)scoring keys c) evidence about the reliability and d) guides for using the test and for interpreting

results.

ACCURACY The characteristic of accuracy of a

measurement scale means it should be a true representative of the observation underlying characteristic.

Ex: measuring with an inch scale will provide accurate value only up to one—eighth of an inch, while measuring with centimeter scale provide more accurate value.

SOURCES OF ERRORS IN MEASUREMENTMeasurement should be precise and unambiguous in an ideal research study. Following are the possible

sources of error in measurement.

# RESPONDENT At times the respondent may be

reluctant to express strong negative feelings , so it is likely to result in an interview of guesses.

Transient factors like fatigue, boredom, anxiety, etc may limit the ability of the respondent to respond accurately and fully.

# SITUATIONS Any condition which places a strain on

interview can have serious effects on the interview respondent rapport.

Ex: if someone else present the respondent is not sure about the anonymity ,he may reluctant to express certain feelings.

# MEASURER The interviewer can distort responses

by rewording or reordering questions. His behavior style and looks may

encourage or discourage certain replies from respondents.

Errors may also creep in because of incorrect coding, faulty tabulation or statistical calculations, particularly in the data analysis stage.

# INSTRUMENT Error may arise because of the defective

measuring instrument. The use of ambiguous meanings, poor printing, inadequate space for replies, response choice omissions etc., are a few things that make the measuring instrument defective.

TECHNIQUES OF DEVELOPING

MEASUREMENT TOOLS

1.CONCEPT DEVELOPMENT In this stage researcher should arrive at

an understanding of the major concepts pertaining to his study.

This is more apparent in the theoretical studies than in pragmatic research, where the fundamental concepts are often already established.

2.SPECIFICATION OF CONCEPT DIMENSIONS

This step accomplished by deduction, ie, by adopting a more or less intuitive approach or by empirical correlation of the individual dimensions with the total concept or the other concepts.

Ex: when one is thinking about the image of a certain company, he may think about the dimensions such as product reputation, customer treatment ,etc. of that company.

3.SELECTION OF INDICATORS Once the dimensions of a concept have

been specified, the researcher must develop indicators for measuring each concept element.

Ex: indicators—scales, questions etc by which respondent’s knowledge, opinion etc are measured.

The use of more than one indicator gives stability to the scores and it also improves their validity.

4.FORMATION OF INDEX When we have several dimensions of a

concept or different measurements of a dimension, we may need to combine them into a single index.

One simple way for getting an overall index is to provide scale values to the responses and then sum up the corresponding scores. Such an overall index would provide a better measurement tool than a single indicator because of the fact that an individual indicator has only a probability relation to what we really want to know.

SCALINGProcedure for the assignment of

numbers to a property of objects in order to impart some of the characteristics of numbers to the properties in question

SCALING This describes the procedures of assigning

numbers to various degrees of opinion, attitude and other concepts.

A scale is a continuum , consisting of the highest point and the lowest point along with several intermediate points between these two extreme points.

Scaling has been defined as a procedure for the assignment of numbers to a property of objects in order to impart some of the characteristics of numbers to the properties in question.

Scaling can be done in two ways

1. Making a judgment about some characteristics of an individual and then placing him directly on a scale that has been defined in terms of that characteristics.

2.Constructing questionnaires on such a way that the score of individual’s responses assigns him a place on a scale.

SCALE CLASSIFICATION BASES

1.SUBJECT ORIENTATION Scale may designed to measure the

characteristics of the respondent who completes it or judge the stimulus object which is presented to the respondent.

2.RESPONSE FORM Under this two types of scales 1.Cateogorical scales—(Rating scales) This is used when a respondent

scores some object without direct reference to other objects.

2. Comparative scales—(Ranking scales) In this the respondent is asked to

compare two or more objects. Ex: the respondent may rank different

brand pens as 1, 2 and 3.

3.DEGREE OF SUBJECTIVITY With this the scale data may be based on

whether we measure subjective personal preferences or simply make non—preferences judgements.

In subjective personal preferences the respondent is asked to choose which person he favours or which solution he would like to see employed.

In non—preferences judgements, the respondent is simply asked to judge which person is more effective in some aspect.

4.SCALE PROPERTIES Considering scale properties we may

classify the scales as nominal, ordinal , interval and ratio scales.

5.NUMBER OF DIMENSIONS

With respect to this scales, can be classified as uni—dimensional and multi—dimensional.

In uni—dimensional measure only one attribute of the respondent or object.

In multi—dimensional the respondent or object is measured by an attribute space of “n” dimensions rather than a single dimension continuum.

6.SCALE CONSTRUCTION TECHNIQUES

Following are the Five main techniques by which scales can be ddeveloped.

1.Arbitrary approach—is an approach where scale is developed on adhoc basis.

2.Consensus approach– a panel of judges evaluate the items chosen for inclusion in the instrument in terms of whether they are relevant to the topic area and unambiguous in implication.

3.Item analysis approach—a number of individual items are developed into a test which is given to a group of respondents

After administering the test, the total scores are calculated for every one.

Individual items are then analysed to determine which items discriminate between persons or objects with high total scores and those with low scores.

4. Cumulative scales– are chosen on the basis of their confirming to some ranking of items with ascending and descending discriminating power.

5.Factor scales—may constructed on the basis of inter correlations of items which indicate that a common factor accounts for the relationship between items. This is measured through factor analysis method.

SCALING TECHNIQUES This is broadly classified into

comparative scaling techniques and non—comparative scaling techniques.

THANK YOUREENA ANDREW , Mphil SCHOLAR.