Sampling and Scaling

8/2/2019 Sampling and Scaling

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Sampling


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POPULATION

This is not the entire population of a given geographicalarea, but the pre-defined set of potential respondents(elements) in a geographical area.

Population may be : Study on Branded baby foods in

Bangalore : All mothers who buy branded baby food inBangalore"

Perception of MTV among teens in India :

All teens who watch MTV in the country

Preferred Celebrities among Alliance students All the students of Alliance University


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Sample vs. Census

Census -- every population member included.

collecting data from every mother who usebranded baby food (ex: 10,000)

Sample is part of the Population.

With sampling, researcher infers populationcharacteristics from a sample.

Colleting data from defined set of mothers whouse branded baby food (ex:100)


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Why sample?

Saves money

Saves time

Inevitable


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Sampling element

Element: Unit about which information is

sought

Most common units in marketing:

Individuals/households


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Sampling terms

Sample Frame: A list of population members

Telephone directory of Mumbai as a

sampling frame to represent the target

population defined as "the adult residents of

Mumbai".

List of students (from the office of the dean)

in alliance university


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Sample Types

Two broad categories:

Probability Sampling: each populationelement has a known, and equal chance of

being included in the sample

Known Population

Non-probability sampling: cannot

mathematically estimate the probability of apopulation element being included in the

sample

Unknown Population


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Known Population

Analysis of specializations preferences

among alliance university students

Known Population : you can use any one ofthe probability sampling methods.

Measuring dealers satisfaction for Ultratech

cement


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unknown population

Consumers preference in Potato chips

unknown Population :

you can use any one of the non-probabilitysampling methods.

Measuring customers satisfaction for Pepsi


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ass cat on o amp ngTechniques

Sampling Techniques

Nonprobability

Sampling Techniques

Probability

Sampling Techniques

Convenience

Sampling

Judgmental

Sampling

Quota

Sampling

Snowball

Sampling

Systematic

Sampling

Stratified

Sampling

Cluster

Sampling

Other Sampling

Techniques

Simple Random

Sampling


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Convenience Sampling

Convenience samplingattempts to obtain asample of convenient elements. Often,

respondents are selected because they

happen to be in the right place at the right

time.

Use of students, and members of social organizations

Mall intercept interviews without qualifying the

respondents

People on the street interviews


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Judgmental Sampling

Judgmental samplingis a form of

convenience sampling in which the

population elements are selected based

on the judgment of the researcher.

-Test markets


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Snowball Sampling

Insnowball sampling, an initial group of

respondents is selected, usually at random.

After being interviewed, these respondents are asked to

identify others who belong to the target population of

interest.

Subsequent respondents are selected based on the

referrals.


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Quota Sampling

Attempt to be representative by selecting

sample elements in proportion to their

known incidence in the population Determine the stratum or quota based on

some criteria: age, sex, education etc


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Quota Sampling

Example: Surveying undergraduate students

about campus food services

Step 1: Identify attributes researcher

believes is important, e. g. sex and class

level

Class levelFirst Year

Final year

SexMale

Female


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Probability Sampling


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Simple Random Sampling

Each element in the population has a known and equalprobability of selection.

Each possible sample of a given size (n) has a known andequal probability of being the sample actually selected.

Generate random number through MS-excel

Rand between (1,10) : give the random no between 1 and10.


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Systematic Sampling

Systematically spreads sample through a list

of population members

Example: If a population contained 10,000people, and need a size of 1000, select

every 10th list name

In nearly all practical examples, theprocedure results in a sample equivalent to

SRS


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Stratified Sampling

A two-step process in which the population ispartitioned into subpopulations, or strata.

The strata should be mutually exclusive and

collectively exhaustive in that every populationelement should be assigned to one and only onestratum and no population elements should be omitted.

Next, elements are selected from each stratum by a

random procedure, usually SRS.

A major objective of stratified sampling is to increaseprecision without increasing cost.


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Stratified Sampling

For example, a consumer population may be

divided into age brackets ofbelow 25 and

above 25 years sex male or female. Then, a

sample is taken from each of the strata

defined earlier.

Malebelow 25

Femalebelow 25

Male above 25

Female above 25


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How is this different from quota

sampling?

Sample is taken from known Population. It

has known and equal probability of being

selected.


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Area (or Cluster) Sampling

Elements are geographically grouped into

relatively homogenous clusters (e.g. a city

is divided into 40 areas) From these areas, 10 are randomly selected

From these larger areas, blocks within areas

will be randomly selected Within each block, attempt to survey each

household


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Determining Sample Size in a

Non-statistical way


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Ad Hoc Methods (non-statistical)

Rules of thumb: Collect sample size largeenough so that when divided into groups, eachgroup will have a minimum sample of 100 .

Comparable studies: Find similar studieswhich are successful and getting sufficientlyreliable results

Budget constraints: calculate the cost of

interview and data analysis per respondent.Divide total budget by this amount to getmaximum sample size.


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Drinking Tea Prevents Cancer in Women

Having 2 cups of tea every day reduces the chancesof being affected by cancer.

A research study in the University of Washingtonand in the National Institute of EnvironmentalMedicine in Stockholm has just proved the fact.

ECGC an oxidant present in the tea (mainly in black

and green tea) prevents the production of HSP90,therefore this will reduce the chances of gettingeffected by the protein.


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SCALING


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Definition: Scaling

The Generation of continuum upon which

measured objects are located.


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SCALE CHARACTERISTICS

DESCRIPTION : Refers to the use of a uniquedescriptor or label, to stand for each designation inthe scale. Yes or no, agree and disagree

ORDER : refers to the relative sizes of thedescriptors. Greater than or lesser than.

DISTANCE: when absolute difference between thedescriptors are known and may be expressed inunits.

ORIGIN: A scale is said to have the characteristicsof origin if there is a unique beginning or true zeropoint for the scale.


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PRIMARY SCALES

Nominal Scale : The numbers serve only as labelsor tags for identifying and classifying objects.

Ordinal Scale : A ranking scale in which numbersare assigned to objects to indicate the relative extentto which the objects possess some characteristic.

Interval Scale :Numerically equal distances on thescale represent equal values in the characteristicbeing measured.

Ratio scale : Possesses all the properties of thenominal, ordinal, and interval scales. It has anabsolute zero point.


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Primary Scales of Measurement

7 38

Scale

Nominal Numbers

Assigned

to Runners

Ordinal Rank Orderof Winners

Interval PerformanceRating on a

1 to 10 Scale

Ratio Time to Finish

in Seconds

Third

place

Second

place

First

place

6 8 10

15.2 14.1 13.4


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Find out the scale

Please indicate your gender: Male female

Which brands do you prefer : Nokia, Samsung ,apple

Please rank the above brands based on your preference.

Please rate above three brands on following parameters

Style very good 5 4 3 2 1 very poor

Colors

Price

How much do you think Apple phone valuable?

What is the probability that you will buy apple nexttime?


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Primary Scales of Measurement

Scale Basic

Characteristics

Common

Examples

Marketing

Examples

Nominal Numbers identify

& classify objects

Social Security

nos., numbering

of football players

Brand nos., store

types

Percentages,

mode

Chi-square,

binomial test

Ordinal Nos. indicate therelative positions

of objects but not

the magnitude of

differences

between them

Quality rankings,rankings of teams

in a tournament

Preferencerankings, market

position, social

class

Percentile,median Rank-ordercorrelation,

Friedman

ANOVA

Ratio Zero point is fixed,

ratios of scale

values can be

compared

Length, weight sales, income,

costs

Geometric

mean, harmonic

mean

Coefficient of

variation

Permissible Statistics

Descriptive Inferential

Interval Differences

between objects

Temperature

(Fahrenheit)

Attitudes,

opinions, index

Range, mean,

standard

Product-

moment

Documents

Sampling and Scaling