19 Measurement Techniques

P. Deivanai

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Introduction

 

Measurement is the process observing and recording the observations that are collected as part of a research effort. Measurement is the foundation of all scientific investigation. It may be defined as the assignment of numbers to characteristics of objects or events according to rules. It is important to note that is the characteristics of objects or events that are measured and not the objects or events themselves. Measurement defines “measurement is the assignment of numbers to objects” it means measuring the personality characteristics by assigning a number” (a score on the test) to an object (a Person). For example, we can measure buyers preference, income and attitude and products’ wetness. A business man engaged in marketing the products is interested in measuring the market potential for a new product, buyer’s attitude, perceptions or preferences towards a new brand. This measurement process gives scope for providing meaningful information for decision making. There are two basic kinds of data Non-Metric (qualitative data) and metric (quantitative).

 

Non-Metric (Qualitative data)

 

Non-metric data are attributes, characteristics or categorical properties that identify or describe subject. Non metric data describe differences in type or kind by indicating the presence or absence of a characteristic or property. Many properties are discrete in that by having a particular feature, all other features are excluded’; for example, if one is male, one cannot female. There is no ‘amount’ of gender, just the state of being male or female.

 

In  contrast metric  data  metrically  measured  variables  reflect  relative  quantity  or  degree. Measurements are made so that subjects may be identified as differing in amount or degree.

 

Metrically measured variables reflect relative quantity or degree. Metric measurements are appropriate for cases involving amount or magnitude, such as height, weight, temperature, rainfall, etc.

 

The table 1 summarizes the four types of measurement. Table 1

Understanding of the different types of measurement scales is important for two reasons: one, to avoid the incorrect use of non metric data as metric data and vice versa and two, to determine which multivariate techniques are the most applicable to the data.

 

Components of measurement

 

Ideally speaking, there should be only one component of a measurement and this component should be a direct reflection of the characteristic being measured. Unfortunately, such a situation seldom exists. Very often, a measurement consists of not one but two components-one representing the influence of the characteristic being measured and the other representing the influence of those characteristics which the researcher is not interested in measuring but which still creep in against his wishes. These other characteristics are as follows:

  1. Additional stable characteristics of the object or event, for example the respondents tendency to give only favorable responses independent of his true feelings.
  2. Short – term characteristics of the objects, for example fatigue, health, hunger, and emotional state.
  3. Situational characteristics, for example, the presence or absence of some of the person or of location under which the measurement is taken.
  4. Characteristics of the measurement process, for example, sex, age, ethnic background, and style of dress for the interviewer or the method of interviewing- telephone, mail, personal interview, etc.
  5. Characteristics of the measuring instrument, for example, unclear instructions ambiguous questions, confusing terms, omitted questions, etc
  6. Characteristics of the response process, for example, mistakes caused by checking a wrong response.
  7. Characteristics of the analysis, for example mistake caused by wrong coding, tabulating,etc.

 

Six out of these seven characteristics (2 to 7) give raise to variable errors in a measurement, i.e., errors which occur randomly each it something is measured. First characteristics gives rise to a systematic error, i.e., error that occurs in a consistent manner each time something is measured. It is also called bias.

 

Thus, the general situation is: M = C +VE +SE,

 

where M stands for the measurement, C stands for the characteristic being measured, VE stands for variable errors and SE stands for systematic errors.

 

Accuracy of measurement

 

Accuracy of measurement depends upon the extent to which it is free from systematic and variable errors. Freedom from variable errors is known as the reliability of a measurement and freedom from systematic errors is known as the validity of a measurement. Reliability and validity are thus, two essential criteria of every measure and its important for every researcher to know how they are measured.

 

MEASUREMENT IN SCALE

 

Scale is a yardstick like any instrument for finding length, weight, volume and the like The scale does not possess the properties associated with most physical measures. The scales can be generally classified into following major categories.

Nominal scale

 

In nominal scale, numbers are used to identify or categories objects or events. For example, the population of a town may be classified according to sex into “male” and Female or accordingto religion into “Hindus”, “Muslims”, Christians”. In marketing research nominal scales are needed to measure brands, store types, sales territories, geographical locations, heavy versus light users, working versus non-working women and brand awareness versus non-awareness. The following table gives an idea regarding the use of nominal scale.

As it could be seen from the illustration, males are concerned with speed and females are concerned with weight. Nominal scales cab be developed from a response to a question Does your car have chakra tyres? The responses may be yes, No and don’t know. For nominally scaled data, statistical analysis such as mode, percentages, the binomial test and chi-squared test can be use. A mean or median cannot be calculated.

 

ii) Ordinal Scale

 

The ordinal scale indicates the relative position of two or more obects or some characteristics. The consumers are asked to rank preference for several brands, flavors or package designs. The measures of such preference ]are ordinal in nature. One may rank two or more households according to their annual income. Suppose we have five households with annual incomes as shown below:

The marketing data involves ordinal measurement. Most data collected by the process of interrogation have ordinal properties. For example, the measurement of attitude, opinion preference and perception involves’ greater than’ or “less than’ Judgments.

 

iii)   Interval scale:

 

The interval scale has all characteristics of the ordinal scale and in addition, the units of measure or intervals between successive positions are equal. For example, a research scaled brands A, B and C on an interval scale regarding the buyers’ degree of liking of the brands. Brand a receives the highest liking score of 6 B receives 3 and C receives 2. First the linking for brand A is more favorable than that for brand B. Second the degree of liking between A and B is three times greater than the liking between B and C.

 

The statistical tools used to analyzer the interval data are range, mean, standard deviation and the like. Interval scales are frequently used in commercial marketing research studies, especially in collecting attitudinal and overall brand rating information.

 

Ratio Scales

 

The ratio scales have all the properties of nominal scale, ordinal scale and intervals scale. They have order, distance and unique origin. Once a ration scale has been established, its value can be transformed only by multiplying each value by a constant. Thus, on a ratio scale, a score of 90 is twice that of 45.

 

Errors

 

Re-zero the instrument if possible, or measure the displacement of the zero reading from the true zero and correct any measurements accordingly. … Parallax (systematic or random) – This error can occur whenever there is some distance between the measuring scale and the indicator used to obtain a measurement. The measurement of an amount is based on some international standards which are completely accurate compared with others. Generally, measurement of any quantity is done by comparing it with derived standards with which they are not completely accurate. Thus, the errors in measurement are not only due to error in methods, but are also due to derivation being not done perfectly well. So, 100% measurement error is not possible with any methods. It is very important for the operator to take proper care of the experiment while performing on industrial instruments so that the error in measurement can be reduced. Some of the errors are constant in nature due to the unknown reasons, some will be random in nature, and the other will be due to gross blunder on the part of the experimenter.

 

Sources of Error in Measurement scale

 

Measurement scale should be precise the source of error and unequivocal in an ideal researches. This objective, however, is often not met with in entirety. As such the researcher must be aware about the sources of error in measurement. The following content may expresses the possible sources of error on measurement.

 

Instrument error refers to the combined accuracy and precision of a measuring instrument, or the difference between the actual value and the value indicated by the instrument (error). Measuring instruments are usually calibrated on some regular frequency against a standard.

 

Respondent error

 

  • The respondent error consist the respondent providing information for research it may be inaccurate or wrong information.
  • They occur because of memory biases or respondents giving inaccurate or false information when they believe that they are protecting their personal interests or integrity.
  • They can also arise from the way the respondent interprets the questionnaire and the wording of the answer that the respondent gives.
  • Careful questionnaire design and effective questionnaire testing can overcome these problems to some extent

Respondent: The respondent it may be reluctant to explain the thought about the negative(-) feelings, instead that just favorable that they have very little knowledge but may not admit his ignorance. All this lack of enthusiasm 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.

 

Situation: Situational factors may also come in the way of correct measurement. The condition which is places a strain on interview can have serious effects on the interviewer-respondent rapport. For instance, if someone else is present, he can distort responses by joining in or merely by being present. If the respondent feels that anonymity is not assured, he may be reluctant to express certain feelings.

 

Measurer: The interviewer can distort responses by rewording or reordering questions. His behaviour, style and looks may encourage or discourage certain replies from respondents. Careless mechanical processing may distort the findings. Errors may also creep in because of incorrect coding, faulty tabulation and/or statistical calculations, particularly in the data-analysis stage.

 

Instrument: Error may arise because of the defective measuring instrument. The study beyond the understanding of the respondent would make the ambiguous meanings of poor printing, and insufficient space for response and choice omissions, there are a few things that make the measuring instrument defective and it result in measurement errors. Another type of instrument deficiency is the poor sampling of the universe of items of concern. The study it may extent possible and try to eliminate, neutralize or otherwise deal with all the possible sources of error so that the final results may not be contaminated.

 

Errors in Measurement System

 

An error may be defined as the difference between the measured value and the actual value. For example, if the two operators use the same device or instrument for finding the errors in measurement, it is not necessary that they may get the similar results. There may be a difference between both measurements. The difference that occurs between both the measurements is referred to as an ERROR. Sequentially, to understand the concept of errors in measurement, you should know the two terms that define the error. They are true value and measured value. The true value is impossible to find out the truth of quantity by experimental means. It may be defined as the average value of an infinite number of measured values. Measured value can be defined as the estimated value of true value that can be found by taking several measured values during an experiment.

                                                                               Random Errors

TECHNIQUE OF DEVELOPING MEASUREMENT SCALE

 

The technique of developing measurement tools consists four-stages of process. It consisting of the following:

 

Understanding of major concepts.

 

The first and foremost step is that of concept development which means that the analysis should clarified and an understanding of the major concepts needed to his study. This study concentrate to develop the concept and making the analysis should be most suitable apparent in theoretical studies than in the more pragmatic research, where the fundamental concepts are often already established.

 

Concepts of Dimensions

 

The II steps requires the researcher to specify the dimensions of the concepts that he developed in the first stage. This task should be accomplished based on deduction. It means that the adopting a new intuitive approach to taken by empirical correlation which is based on the individual dimensions with the total concept. It think more or less several dimensions like that reputation of products, treatment of customers, leading the corporate leadership, concern forindividuals, sense of social responsibility and so forth when one is thinking about the image of a certain industry. The dimensions concepts specified, the analysis should in-depth develop indicators for measuring step by step development of research elements.

 

Perfect measure of a concept

 

Indicators are specific questions, scales, or other devices by which respondent’s knowledge, opinion, expectation, etc., are measured. As there is seldom a perfect measure of a concept, the researcher should consider several alternatives for the purpose. The use of more than one indicator gives stability to the scores and it also improves their validity.

 

Combining the various indicators

 

The fourth step is that of combining the different indicators into an index that is formation of an index. The study have different kind of dimensions concept, and it may be consists the various dimension of measurements, it need to combine them into a single index. The one or more simplest methods are there to getting an overall index is to proved the scale values to the customers and calculate the total score with the help of scale value to find out the corresponding scores. The overall index given a satisfactory measurement tool to indicate a single indicator i.e that the fact which indicate the individual indicator had the probability chance identification and what we really want to know. This way it may obtain an overall index for the different dimension concepts of the research study.

 

Conclusion

 

The measurement research in science or social science which is help to provide meaningful information for decision making process. The scale of measurement which is help to marketing research to measure brands, store types, sales territories, geographical locations, heavy versus light users, working versus non-working women and brand awareness versus non-awareness. Measurement is the assignment of numbers or other symbols to characteristics of objects according to set rules. Scaling involves the generation of a continuum upon which measure objects or located. Scaling techniques can be classified as comparative or non comparative. It involves a direct comparison of stimulus objects. The statistics measurement techniques which are highly need to research.

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Web links

  • https://www.wisdomjobs.com/e-university/research-methodology-practice-tests-355-327240
  • https://www.wisdomjobs.com/e-university/research-methodology-tutorial-355/sources-of-error-in-measurement-11479.html
  • https://www.wisdomjobs.com/e-university/research-methodology-tutorial-355/sources-of-error-in-measurement-11479.html
  • https://uk.sagepub.com/sites/default/files/upm-binaries/4553_Smith_Chp_10.pdf
  • https://www.slideshare.net/charurastogi/attitude-measurement-and-scaling-techniques
  • http://www.micquality.com/six_sigma_glossary/index.htm
  • https://www.slideshare.net/KaranKhaneja/measurement-and-scales?next_slideshow=1