SlideShare a Scribd company logo
1 of 17
Measurement & Scaling
Techniques
Dr. D. Heena Cowsar
Assistant Professor of Commerce
Bon Secours College for Women,
Thanjavur
heena.raffi@gmail.com
Objective of the study
• Introduction on Measurement & Scaling Techniques
• An understanding of the four levels of measurement
that can be taken by researchers
• The ability to distinguish between comparative and
non-comparative measurement scales,
• A basic tool-kit of scales that can be used for the
purposes of marketing research.
https://www.slideshare.net/ujjmishra1/measurement-
and-scaling-techniques
Measurement
Measurement means assigning numbers or
other symbols to characteristics of objects
according to certain pre-specified rules.
– One-to-one correspondence between the
numbers and the characteristics being
measured.
– The rules for assigning numbers should be
standardized and applied uniformly.
– Rules must not change over objects or time.
Scaling
Scaling technique is a method of placing
respondents in continuation of gradual change in
the pre-assigned values, symbols or numbers based
on the features of a particular object as per the
defined rules. All the scaling techniques are based
on four pillars, i.e., order, description, distance and
origin.
Eg., Consider an attitude scale from 1 to 100. Each
respondent is assigned a number from 1 to 100, with
1 = Extremely Unfavorable, and 100 = Extremely
Favorable. Measurement is the actual assignment of
a number from 1 to 100 to each respondent. Scaling
is the process of placing the respondents on a
continuum with respect to their attitude toward
Why Numbers are assigned?
Numbers are usually assigned for two
reasons:
– First, numbers permit statistical analysis of
the resulting data
– Second, numbers facilitate the
communication of measurement rules and
results
Issues in Measurement
When the researcher is interested in the
measuring the attitude, feelings or opinion of
the respondents, he should be clear of the
following
What is to be measured?
Who is to be measured?
The choices available in data collection
techniques
Scale characteristics determine the
level of measurement
• Description
• Order
• Distance
• Origin
Scaling Techniques
• Types
– Primary Scaling Techniques
• Nominal Scale
• Ordinal Scale
• Interval Scale
• Ratio Scale
– Other Scaling Techniques
• Comparative Scales
• Non-Comparative Scales
Nominal Scale
Nominal scales are adopted for non-quantitative (containing no numerical
implication) labeling variables which are unique and different from one
another.
Types of Nominal Scales:
•Dichotomous: A nominal scale that has only two labels is called
‘dichotomous’; for example, Yes/No.
•Nominal with Order: The labels on a nominal scale arranged in an
ascending or descending order is termed as ‘nominal with
order’; for example, Excellent, Good, Average, Poor, Worst.
•Nominal without Order: Such nominal scale which has no sequence, is
called ‘nominal without order’; for example, Black, White.
Ordinal Scale
The ordinal scale functions on the concept of the relative
position of the objects or labels based on the individual’s
choice or preference.
For example, At Amazon.in, every product has a customer
review section where the buyers rate the listed product
according to their buying experience, product features,
quality, usage, etc.
The ratings so provided are as follows:
•5 Star – Excellent
•4 Star – Good
•3 Star – Average
•2 Star – Poor
•1 Star – Worst
Interval Scale
• Interval scale refers to the level of measurement in which the attributes
composing variables are measured on specific numerical scores or values
and there are equal distances between attributes. The equal distances
between attributes on an interval scale differ from an ordinal scale.
• An interval scale is also called a cardinal scale which is the numerical
labeling with the same difference among the consecutive measurement
units.
• With the help of this scaling technique, researchers can obtain a better
comparison between the objects.
• For example; A survey conducted by an automobile company to know the
number of vehicles owned by the people living in a particular area who can
be its prospective customers in future.
• It adopted the interval scaling technique for the purpose and provided the
units as 1, 2, 3, 4, 5, 6 to select from.
• In the scale mentioned above, every unit has the same difference, i.e., 1,
whether it is between 2 and 3 or between 4 and 5.
• Temperature (Farenheit), Temperature (Celcius), pH, SAT score (200-800),
Ratio Scale
• One of the most superior measurement technique is the ratio
scale. Similar to an interval scale, a ratio scale is an abstract
number system. It allows measurement at proper intervals,
order, categorization and distance, with an added property
of originating from a fixed zero point. Here, the comparison
can be made in terms of the acquired ratio.
• For example, A health product manufacturing company
surveyed to identify the level of obesity in a particular
locality. It released the following survey questionnaire:
Select a category to which your weight belongs to:
• Less than 40 kilograms
• 40-59 Kilograms
• 60-79 Kilograms
• 80-99 Kilograms
• 100-119 Kilograms
• 120 Kilograms and more
Difference between the Primary scaling techniques:
PARTICULAR
NOMINAL
SCALE
ORDINAL
SCALE
INTERVAL
SCALE
RATIO SCALE
Characteristics Description Order Distance Description,
Order, Distance &
Origin
Sequential
Arrangement
Not Applicable Applicable Applicable Applicable
Fixed Zero Point Not Applicable Not Applicable Not Applicable Applicable
Multiplication &
Division
Not Applicable Not Applicable Not Applicable Applicable
Addition and
Subtraction
Not Applicable Not Applicable Applicable Applicable
Difference
between Variables
Non-Measurable Non-Measurable Measurable Measurable
Mean Not Applicable Not Applicable Applicable Applicable
Median Not Applicable Applicable Applicable Applicable
Mode Applicable Applicable Applicable Applicable
Primary Scale of Measurement
Primary Scale of Measurement
Case Study
ChemCo is a leading manufacturer of car batteries in the
U.K. market started in 1965. Since then, it has been under the charge
of Mr. Jones, the founder-owner of the firm.
In 1999, the company decided to go for a diversification by
expanding the product line. The new product was batteries for fork-
lift trucks.
At the same time, Mr. Marek was appointed the Senior Vice
President of marketing in the company. However, soon after its
successful diversification into fork-lift batteries, the sales in this
segment began dropping steadily.
Mr. Marek wanted to introduce some radical changes in the
advertising and branding of the new business but the proposal was
turned down by the old-fashioned Mr. Jones.
At this juncture in 2002, the firm is losing heavily in the fork-
lift batteries business and its market share in car batteries is also on a
decline.
Mr. Jones has asked Mr. Marek to show a turnaround in the
company within a year. What steps should Mr. Marek take to take
the company out of its troubles?
Case Study
The Nakamura Lacquer Company (NLC) of Kyoto, Japan, employed several
thousand men and produced 500,000 pieces of lacquer tableware annually, with its
Chrysanthmum brand becoming Japan's best known and bestselling brand. The annual profit
from operations was $250,000.
The market for lacquerware in Japan seemed to have matured, with the production steady at
500,000 pieces a year. NLC did practically no business outside Japan.
In May 2000, (much to your chagrin!) the ambitious and dynamic, Mr. Nakamura (Chairman,
NLC) received two offers from American companies wishing to sell lacquer ware in America.
The first offer was from the National China Company. It was the largest manufacturer of good
quality dinnerware in the U.S., with their “Rose and Crown” brand accounting for almost 30%
of total sales. They were willing to give a firm order for three years for annual purchases of
400,000 sets of lacquer dinnerware, delivered in Japan and at 5% more than what the Japanese
jobbers paid. However, Nakamura would have to forego the Chrysanthemum trademark to
“Rose and Crown” and also undertake not to sell lacquer ware to anyone else in the U.S.
The second offer was from Sammelback, Sammelback and Whittacker (henceforth SSW),
Chicago, the largest supplier of hotel and restaurant supplies in the U.S. They perceived a U.S.
market of 600,000 sets a year, expecting it to go up to 2 million in around 5 years. Since the
Japanese government did not allow overseas investment, SSW was willing to budget $1.5
million for the next two years towards introduction and promotion. Nakamura would sell his
“Chrysanthemum” brand but would have to give exclusive representation to SSW for five
years at standard commission rates and also forego his profit margin toward paying back of
the $ 1.5 million.
What should Mr. Nakamura do?

More Related Content

What's hot

measurement and scaling techniques
measurement and scaling techniques measurement and scaling techniques
measurement and scaling techniques Akanksha Gupta
 
Sampling merits & Demerits.pptx
Sampling merits & Demerits.pptxSampling merits & Demerits.pptx
Sampling merits & Demerits.pptxheencomm
 
SCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptx
SCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptxSCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptx
SCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptxAnshutChitransh
 
processng and analysis of data
 processng and analysis of data processng and analysis of data
processng and analysis of dataAruna Poddar
 
Measurement & scaling ,Research methodology
    Measurement & scaling ,Research methodology    Measurement & scaling ,Research methodology
Measurement & scaling ,Research methodologySONA SEBASTIAN
 
Sampling design
Sampling designSampling design
Sampling designNijaz N
 
Errors in Sampling - Types, Examples and Concepts
Errors in Sampling - Types, Examples and ConceptsErrors in Sampling - Types, Examples and Concepts
Errors in Sampling - Types, Examples and ConceptsSundar B N
 
Data processing and analysis
Data processing and analysisData processing and analysis
Data processing and analysisSrividhya Ramaswamy
 
Presentation on stratified sampling
Presentation on stratified samplingPresentation on stratified sampling
Presentation on stratified samplingKrishna Bharati
 
Measurement and scaling techniques
Measurement and scaling techniquesMeasurement and scaling techniques
Measurement and scaling techniquesKritika Jain
 
Methods of Statistical Analysis & Interpretation of Data..pptx
Methods of Statistical Analysis & Interpretation of Data..pptxMethods of Statistical Analysis & Interpretation of Data..pptx
Methods of Statistical Analysis & Interpretation of Data..pptxheencomm
 
Sampling design
Sampling designSampling design
Sampling designKiran182729
 
Non probability sampling
Non probability samplingNon probability sampling
Non probability samplingSENTHILKUMARAN
 
Measurement and scaling
Measurement and scalingMeasurement and scaling
Measurement and scalingBalaji P
 
SAMPLING DESIGN AND STEPS IN SAMPLE DESIGN
SAMPLING DESIGN AND STEPS IN SAMPLE DESIGNSAMPLING DESIGN AND STEPS IN SAMPLE DESIGN
SAMPLING DESIGN AND STEPS IN SAMPLE DESIGNpra098
 

What's hot (20)

measurement and scaling techniques
measurement and scaling techniques measurement and scaling techniques
measurement and scaling techniques
 
Type of Sampling design
Type of Sampling  designType of Sampling  design
Type of Sampling design
 
Sampling merits & Demerits.pptx
Sampling merits & Demerits.pptxSampling merits & Demerits.pptx
Sampling merits & Demerits.pptx
 
SCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptx
SCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptxSCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptx
SCALE , CLASSIFICATION OF SCALE AND IMPORTANCE OF SCALING TECHNIQUES.pptx
 
processng and analysis of data
 processng and analysis of data processng and analysis of data
processng and analysis of data
 
Measurement & scaling ,Research methodology
    Measurement & scaling ,Research methodology    Measurement & scaling ,Research methodology
Measurement & scaling ,Research methodology
 
Sampling design
Sampling designSampling design
Sampling design
 
Sample design
Sample designSample design
Sample design
 
Errors in Sampling - Types, Examples and Concepts
Errors in Sampling - Types, Examples and ConceptsErrors in Sampling - Types, Examples and Concepts
Errors in Sampling - Types, Examples and Concepts
 
Data processing and analysis
Data processing and analysisData processing and analysis
Data processing and analysis
 
Presentation on stratified sampling
Presentation on stratified samplingPresentation on stratified sampling
Presentation on stratified sampling
 
Measurement and scaling techniques
Measurement and scaling techniquesMeasurement and scaling techniques
Measurement and scaling techniques
 
Methods of Statistical Analysis & Interpretation of Data..pptx
Methods of Statistical Analysis & Interpretation of Data..pptxMethods of Statistical Analysis & Interpretation of Data..pptx
Methods of Statistical Analysis & Interpretation of Data..pptx
 
Motivation research
Motivation researchMotivation research
Motivation research
 
Sampling
Sampling Sampling
Sampling
 
Sampling design
Sampling designSampling design
Sampling design
 
5.measurement
5.measurement5.measurement
5.measurement
 
Non probability sampling
Non probability samplingNon probability sampling
Non probability sampling
 
Measurement and scaling
Measurement and scalingMeasurement and scaling
Measurement and scaling
 
SAMPLING DESIGN AND STEPS IN SAMPLE DESIGN
SAMPLING DESIGN AND STEPS IN SAMPLE DESIGNSAMPLING DESIGN AND STEPS IN SAMPLE DESIGN
SAMPLING DESIGN AND STEPS IN SAMPLE DESIGN
 

Similar to Measurement & Scaling Techniques.pptx

Measurement Concept/Scaling techniques
Measurement Concept/Scaling techniquesMeasurement Concept/Scaling techniques
Measurement Concept/Scaling techniquesviveksangwan007
 
Business Research Methods lol.pptx
Business Research Methods lol.pptxBusiness Research Methods lol.pptx
Business Research Methods lol.pptxMasterChief8
 
Measurement&scaling
Measurement&scalingMeasurement&scaling
Measurement&scalingMario Leonard
 
Scalling technique
Scalling technique Scalling technique
Scalling technique Ravindra Sharma
 
Scaling in research
Scaling  in researchScaling  in research
Scaling in researchankitsengar
 
Measurement and scaling techniques
Measurement and scaling techniquesMeasurement and scaling techniques
Measurement and scaling techniquesSarfaraz Ahmad
 
Research methodology for business .pptx
Research methodology for business .pptxResearch methodology for business .pptx
Research methodology for business .pptxParmeshwar Biradar
 
5.Measurement and scaling technique.pptx
5.Measurement and scaling technique.pptx5.Measurement and scaling technique.pptx
5.Measurement and scaling technique.pptxHimaniPandya13
 
Measurement and scaling techniques
Measurement  and  scaling  techniquesMeasurement  and  scaling  techniques
Measurement and scaling techniquesUjjwal 'Shanu'
 
Chotu scaling techniques
Chotu scaling techniquesChotu scaling techniques
Chotu scaling techniquesPruseth Abhisek
 
Marketing Mix
Marketing MixMarketing Mix
Marketing MixDialight
 
Measurement scales
Measurement scalesMeasurement scales
Measurement scalesKritika Jain
 
Measurement scales
Measurement scalesMeasurement scales
Measurement scalesKritika Jain
 
Measurement scales
Measurement scalesMeasurement scales
Measurement scalesKritika Jain
 
Topic 1 ELEMENTARY STATISTICS.pptx
Topic 1 ELEMENTARY STATISTICS.pptxTopic 1 ELEMENTARY STATISTICS.pptx
Topic 1 ELEMENTARY STATISTICS.pptxmoisespadillacpsu19
 
LPP application and problem formulation
LPP application and problem formulationLPP application and problem formulation
LPP application and problem formulationKarishma Chaudhary
 

Similar to Measurement & Scaling Techniques.pptx (20)

Measurement Concept/Scaling techniques
Measurement Concept/Scaling techniquesMeasurement Concept/Scaling techniques
Measurement Concept/Scaling techniques
 
Business Research Methods lol.pptx
Business Research Methods lol.pptxBusiness Research Methods lol.pptx
Business Research Methods lol.pptx
 
Measurement&scaling
Measurement&scalingMeasurement&scaling
Measurement&scaling
 
Scalling technique
Scalling technique Scalling technique
Scalling technique
 
Measurement
MeasurementMeasurement
Measurement
 
Scaling in research
Scaling  in researchScaling  in research
Scaling in research
 
Measurement and scaling techniques
Measurement and scaling techniquesMeasurement and scaling techniques
Measurement and scaling techniques
 
Research methodology for business .pptx
Research methodology for business .pptxResearch methodology for business .pptx
Research methodology for business .pptx
 
5.Measurement and scaling technique.pptx
5.Measurement and scaling technique.pptx5.Measurement and scaling technique.pptx
5.Measurement and scaling technique.pptx
 
Measurement and scaling techniques
Measurement  and  scaling  techniquesMeasurement  and  scaling  techniques
Measurement and scaling techniques
 
ch 13.pptx
ch 13.pptxch 13.pptx
ch 13.pptx
 
Chotu scaling techniques
Chotu scaling techniquesChotu scaling techniques
Chotu scaling techniques
 
Marketing Mix
Marketing MixMarketing Mix
Marketing Mix
 
Demand forecasting
Demand forecastingDemand forecasting
Demand forecasting
 
Measurement scales
Measurement scalesMeasurement scales
Measurement scales
 
Measurement scales
Measurement scalesMeasurement scales
Measurement scales
 
Measurement scales
Measurement scalesMeasurement scales
Measurement scales
 
CHAP 1.pptx
CHAP 1.pptxCHAP 1.pptx
CHAP 1.pptx
 
Topic 1 ELEMENTARY STATISTICS.pptx
Topic 1 ELEMENTARY STATISTICS.pptxTopic 1 ELEMENTARY STATISTICS.pptx
Topic 1 ELEMENTARY STATISTICS.pptx
 
LPP application and problem formulation
LPP application and problem formulationLPP application and problem formulation
LPP application and problem formulation
 

More from heencomm

Data Presentation & Analysis.pptx
Data Presentation & Analysis.pptxData Presentation & Analysis.pptx
Data Presentation & Analysis.pptxheencomm
 
Hypothesis Testing.pptx
Hypothesis Testing.pptxHypothesis Testing.pptx
Hypothesis Testing.pptxheencomm
 
Sampling.pptx
Sampling.pptxSampling.pptx
Sampling.pptxheencomm
 
Sampling merits & Demerits.pptx
Sampling merits & Demerits.pptxSampling merits & Demerits.pptx
Sampling merits & Demerits.pptxheencomm
 
Questionnaire Vs schedule.docx
Questionnaire Vs schedule.docxQuestionnaire Vs schedule.docx
Questionnaire Vs schedule.docxheencomm
 
Pretesting.pptx
Pretesting.pptxPretesting.pptx
Pretesting.pptxheencomm
 
Pretesting.pptx
Pretesting.pptxPretesting.pptx
Pretesting.pptxheencomm
 
Questionnaire Vs schedule.docx
Questionnaire Vs schedule.docxQuestionnaire Vs schedule.docx
Questionnaire Vs schedule.docxheencomm
 
Measurement & Scaling Techniques.pptx
Measurement & Scaling Techniques.pptxMeasurement & Scaling Techniques.pptx
Measurement & Scaling Techniques.pptxheencomm
 
Data Collection.pptx
Data Collection.pptxData Collection.pptx
Data Collection.pptxheencomm
 
Data Collection.pptx
Data Collection.pptxData Collection.pptx
Data Collection.pptxheencomm
 
B. Com LMS.pptx
B. Com LMS.pptxB. Com LMS.pptx
B. Com LMS.pptxheencomm
 
Income from house property .pptx
Income from house property .pptxIncome from house property .pptx
Income from house property .pptxheencomm
 
Holding company continue 1
Holding company continue 1Holding company continue 1
Holding company continue 1heencomm
 
Holding company
Holding companyHolding company
Holding companyheencomm
 
Types of research
Types of researchTypes of research
Types of researchheencomm
 

More from heencomm (16)

Data Presentation & Analysis.pptx
Data Presentation & Analysis.pptxData Presentation & Analysis.pptx
Data Presentation & Analysis.pptx
 
Hypothesis Testing.pptx
Hypothesis Testing.pptxHypothesis Testing.pptx
Hypothesis Testing.pptx
 
Sampling.pptx
Sampling.pptxSampling.pptx
Sampling.pptx
 
Sampling merits & Demerits.pptx
Sampling merits & Demerits.pptxSampling merits & Demerits.pptx
Sampling merits & Demerits.pptx
 
Questionnaire Vs schedule.docx
Questionnaire Vs schedule.docxQuestionnaire Vs schedule.docx
Questionnaire Vs schedule.docx
 
Pretesting.pptx
Pretesting.pptxPretesting.pptx
Pretesting.pptx
 
Pretesting.pptx
Pretesting.pptxPretesting.pptx
Pretesting.pptx
 
Questionnaire Vs schedule.docx
Questionnaire Vs schedule.docxQuestionnaire Vs schedule.docx
Questionnaire Vs schedule.docx
 
Measurement & Scaling Techniques.pptx
Measurement & Scaling Techniques.pptxMeasurement & Scaling Techniques.pptx
Measurement & Scaling Techniques.pptx
 
Data Collection.pptx
Data Collection.pptxData Collection.pptx
Data Collection.pptx
 
Data Collection.pptx
Data Collection.pptxData Collection.pptx
Data Collection.pptx
 
B. Com LMS.pptx
B. Com LMS.pptxB. Com LMS.pptx
B. Com LMS.pptx
 
Income from house property .pptx
Income from house property .pptxIncome from house property .pptx
Income from house property .pptx
 
Holding company continue 1
Holding company continue 1Holding company continue 1
Holding company continue 1
 
Holding company
Holding companyHolding company
Holding company
 
Types of research
Types of researchTypes of research
Types of research
 

Recently uploaded

Historical philosophical, theoretical, and legal foundations of special and i...
Historical philosophical, theoretical, and legal foundations of special and i...Historical philosophical, theoretical, and legal foundations of special and i...
Historical philosophical, theoretical, and legal foundations of special and i...jaredbarbolino94
 
What is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERPWhat is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERPCeline George
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Jisc
 
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersDATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersSabitha Banu
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
Final demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxFinal demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxAvyJaneVismanos
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsanshu789521
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxiammrhaywood
 
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfFraming an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfUjwalaBharambe
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfMahmoud M. Sallam
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentInMediaRes1
 
Earth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatEarth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatYousafMalik24
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon AUnboundStockton
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for BeginnersSabitha Banu
 

Recently uploaded (20)

Historical philosophical, theoretical, and legal foundations of special and i...
Historical philosophical, theoretical, and legal foundations of special and i...Historical philosophical, theoretical, and legal foundations of special and i...
Historical philosophical, theoretical, and legal foundations of special and i...
 
What is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERPWhat is Model Inheritance in Odoo 17 ERP
What is Model Inheritance in Odoo 17 ERP
 
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Tilak Nagar Delhi reach out to us at 🔝9953056974🔝
 
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝Model Call Girl in Bikash Puri  Delhi reach out to us at 🔝9953056974🔝
Model Call Girl in Bikash Puri Delhi reach out to us at 🔝9953056974🔝
 
Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...Procuring digital preservation CAN be quick and painless with our new dynamic...
Procuring digital preservation CAN be quick and painless with our new dynamic...
 
DATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginnersDATA STRUCTURE AND ALGORITHM for beginners
DATA STRUCTURE AND ALGORITHM for beginners
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
Final demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptxFinal demo Grade 9 for demo Plan dessert.pptx
Final demo Grade 9 for demo Plan dessert.pptx
 
Presiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha electionsPresiding Officer Training module 2024 lok sabha elections
Presiding Officer Training module 2024 lok sabha elections
 
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptxECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
ECONOMIC CONTEXT - PAPER 1 Q3: NEWSPAPERS.pptx
 
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdfFraming an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
Framing an Appropriate Research Question 6b9b26d93da94caf993c038d9efcdedb.pdf
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
Pharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdfPharmacognosy Flower 3. Compositae 2023.pdf
Pharmacognosy Flower 3. Compositae 2023.pdf
 
Alper Gobel In Media Res Media Component
Alper Gobel In Media Res Media ComponentAlper Gobel In Media Res Media Component
Alper Gobel In Media Res Media Component
 
Earth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice greatEarth Day Presentation wow hello nice great
Earth Day Presentation wow hello nice great
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
Crayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon ACrayon Activity Handout For the Crayon A
Crayon Activity Handout For the Crayon A
 
Full Stack Web Development Course for Beginners
Full Stack Web Development Course  for BeginnersFull Stack Web Development Course  for Beginners
Full Stack Web Development Course for Beginners
 

Measurement & Scaling Techniques.pptx

  • 1. Measurement & Scaling Techniques Dr. D. Heena Cowsar Assistant Professor of Commerce Bon Secours College for Women, Thanjavur heena.raffi@gmail.com
  • 2. Objective of the study • Introduction on Measurement & Scaling Techniques • An understanding of the four levels of measurement that can be taken by researchers • The ability to distinguish between comparative and non-comparative measurement scales, • A basic tool-kit of scales that can be used for the purposes of marketing research. https://www.slideshare.net/ujjmishra1/measurement- and-scaling-techniques
  • 3. Measurement Measurement means assigning numbers or other symbols to characteristics of objects according to certain pre-specified rules. – One-to-one correspondence between the numbers and the characteristics being measured. – The rules for assigning numbers should be standardized and applied uniformly. – Rules must not change over objects or time.
  • 4. Scaling Scaling technique is a method of placing respondents in continuation of gradual change in the pre-assigned values, symbols or numbers based on the features of a particular object as per the defined rules. All the scaling techniques are based on four pillars, i.e., order, description, distance and origin. Eg., Consider an attitude scale from 1 to 100. Each respondent is assigned a number from 1 to 100, with 1 = Extremely Unfavorable, and 100 = Extremely Favorable. Measurement is the actual assignment of a number from 1 to 100 to each respondent. Scaling is the process of placing the respondents on a continuum with respect to their attitude toward
  • 5. Why Numbers are assigned? Numbers are usually assigned for two reasons: – First, numbers permit statistical analysis of the resulting data – Second, numbers facilitate the communication of measurement rules and results
  • 6. Issues in Measurement When the researcher is interested in the measuring the attitude, feelings or opinion of the respondents, he should be clear of the following What is to be measured? Who is to be measured? The choices available in data collection techniques
  • 7. Scale characteristics determine the level of measurement • Description • Order • Distance • Origin
  • 8. Scaling Techniques • Types – Primary Scaling Techniques • Nominal Scale • Ordinal Scale • Interval Scale • Ratio Scale – Other Scaling Techniques • Comparative Scales • Non-Comparative Scales
  • 9. Nominal Scale Nominal scales are adopted for non-quantitative (containing no numerical implication) labeling variables which are unique and different from one another. Types of Nominal Scales: •Dichotomous: A nominal scale that has only two labels is called ‘dichotomous’; for example, Yes/No. •Nominal with Order: The labels on a nominal scale arranged in an ascending or descending order is termed as ‘nominal with order’; for example, Excellent, Good, Average, Poor, Worst. •Nominal without Order: Such nominal scale which has no sequence, is called ‘nominal without order’; for example, Black, White.
  • 10. Ordinal Scale The ordinal scale functions on the concept of the relative position of the objects or labels based on the individual’s choice or preference. For example, At Amazon.in, every product has a customer review section where the buyers rate the listed product according to their buying experience, product features, quality, usage, etc. The ratings so provided are as follows: •5 Star – Excellent •4 Star – Good •3 Star – Average •2 Star – Poor •1 Star – Worst
  • 11. Interval Scale • Interval scale refers to the level of measurement in which the attributes composing variables are measured on specific numerical scores or values and there are equal distances between attributes. The equal distances between attributes on an interval scale differ from an ordinal scale. • An interval scale is also called a cardinal scale which is the numerical labeling with the same difference among the consecutive measurement units. • With the help of this scaling technique, researchers can obtain a better comparison between the objects. • For example; A survey conducted by an automobile company to know the number of vehicles owned by the people living in a particular area who can be its prospective customers in future. • It adopted the interval scaling technique for the purpose and provided the units as 1, 2, 3, 4, 5, 6 to select from. • In the scale mentioned above, every unit has the same difference, i.e., 1, whether it is between 2 and 3 or between 4 and 5. • Temperature (Farenheit), Temperature (Celcius), pH, SAT score (200-800),
  • 12. Ratio Scale • One of the most superior measurement technique is the ratio scale. Similar to an interval scale, a ratio scale is an abstract number system. It allows measurement at proper intervals, order, categorization and distance, with an added property of originating from a fixed zero point. Here, the comparison can be made in terms of the acquired ratio. • For example, A health product manufacturing company surveyed to identify the level of obesity in a particular locality. It released the following survey questionnaire: Select a category to which your weight belongs to: • Less than 40 kilograms • 40-59 Kilograms • 60-79 Kilograms • 80-99 Kilograms • 100-119 Kilograms • 120 Kilograms and more
  • 13. Difference between the Primary scaling techniques: PARTICULAR NOMINAL SCALE ORDINAL SCALE INTERVAL SCALE RATIO SCALE Characteristics Description Order Distance Description, Order, Distance & Origin Sequential Arrangement Not Applicable Applicable Applicable Applicable Fixed Zero Point Not Applicable Not Applicable Not Applicable Applicable Multiplication & Division Not Applicable Not Applicable Not Applicable Applicable Addition and Subtraction Not Applicable Not Applicable Applicable Applicable Difference between Variables Non-Measurable Non-Measurable Measurable Measurable Mean Not Applicable Not Applicable Applicable Applicable Median Not Applicable Applicable Applicable Applicable Mode Applicable Applicable Applicable Applicable
  • 14. Primary Scale of Measurement
  • 15. Primary Scale of Measurement
  • 16. Case Study ChemCo is a leading manufacturer of car batteries in the U.K. market started in 1965. Since then, it has been under the charge of Mr. Jones, the founder-owner of the firm. In 1999, the company decided to go for a diversification by expanding the product line. The new product was batteries for fork- lift trucks. At the same time, Mr. Marek was appointed the Senior Vice President of marketing in the company. However, soon after its successful diversification into fork-lift batteries, the sales in this segment began dropping steadily. Mr. Marek wanted to introduce some radical changes in the advertising and branding of the new business but the proposal was turned down by the old-fashioned Mr. Jones. At this juncture in 2002, the firm is losing heavily in the fork- lift batteries business and its market share in car batteries is also on a decline. Mr. Jones has asked Mr. Marek to show a turnaround in the company within a year. What steps should Mr. Marek take to take the company out of its troubles?
  • 17. Case Study The Nakamura Lacquer Company (NLC) of Kyoto, Japan, employed several thousand men and produced 500,000 pieces of lacquer tableware annually, with its Chrysanthmum brand becoming Japan's best known and bestselling brand. The annual profit from operations was $250,000. The market for lacquerware in Japan seemed to have matured, with the production steady at 500,000 pieces a year. NLC did practically no business outside Japan. In May 2000, (much to your chagrin!) the ambitious and dynamic, Mr. Nakamura (Chairman, NLC) received two offers from American companies wishing to sell lacquer ware in America. The first offer was from the National China Company. It was the largest manufacturer of good quality dinnerware in the U.S., with their “Rose and Crown” brand accounting for almost 30% of total sales. They were willing to give a firm order for three years for annual purchases of 400,000 sets of lacquer dinnerware, delivered in Japan and at 5% more than what the Japanese jobbers paid. However, Nakamura would have to forego the Chrysanthemum trademark to “Rose and Crown” and also undertake not to sell lacquer ware to anyone else in the U.S. The second offer was from Sammelback, Sammelback and Whittacker (henceforth SSW), Chicago, the largest supplier of hotel and restaurant supplies in the U.S. They perceived a U.S. market of 600,000 sets a year, expecting it to go up to 2 million in around 5 years. Since the Japanese government did not allow overseas investment, SSW was willing to budget $1.5 million for the next two years towards introduction and promotion. Nakamura would sell his “Chrysanthemum” brand but would have to give exclusive representation to SSW for five years at standard commission rates and also forego his profit margin toward paying back of the $ 1.5 million. What should Mr. Nakamura do?