RM (Research Methodology)

RM (Research Methodology)

:: Survey Research :: Medium: Personal (response rate = 30-35%) Telephone (25-30%) Computer (0.5%) Mail/post (2%) :: To decide which type to use: Do the respondents & interviewers have common understanding of the information sought? Is the respondent able to provide a truthful answer? Is the respondent willing to provide a truthful answer?


:: Survey Research :: Criteria for selecting method: Complexity of questions Amount of data/time Data accuracy required sensitive questions, interviewer effects, error sources Cost Sample control Response rate :: Unstructured indirect interview: Projective techniques, underlying beliefsEg: Sentence completion, picture/story completion


EXPERIMENTAL RESEARCH :: Experimentation: Experimentation is the manipulation of one or more variables to measure their effect on one or more variables. That is, cause and effect studies :: Types of variables: Independent Dependant variable :: Treatment group: Ample exposed to manipulation of independent variable


EXPERIMENTAL RESEARCH :: Control group: The independent variable is unchanged. To ensure that the change in independent variable is caused by independent variable, other variables need to be controlled/measured in terms of their effects. Randomization Matching :: Experimental design features are: Error control Time/Sample/Data Monetary requirements


EXPERIMENTAL RESEARCH :: Symbols:: MB MA X R = = = = Pre-measurement Post-measurement Treatment Random selection


EXPERIMENTAL RESEARCH :: Basic designs :i) After only design : : : R1 R2 MB MB1 MB2 MB X X MB1 MB2 X X X MA MA1 MA2 MA1 MA2 MA3 MA4 X X X X MA MA MA1 MA2 ii) Before After Design iii) Before After with design control

(iv) Simulated Before After design : R1 R2 (v) After only with control : R1 R2 (vi) Solomon 4 group control :R R R R


EXPERIMENTAL RESEARCH DESIGN :: Statistical design: They permit measurement of effect of more than 1 independent variable. It allows researchers to control for specific extraneous variables that may affect results. It is more economical :: Types : Randomized Blocks Design Latin Square Design Factorial Design


EXPERIMENTAL RESEARCH DESIGN (i) Randomized Blocks Design (RBD) Completely random design assumes that each treatment group is similar in reaction to independent variable and is similar initially in terms of dependent variable. This may be invalid. Hence RBD is used. In RBD, experimental units are blocked/grouped on the basis of blocking / grouping variable. Hence, experimental/treatment group & control group are better matched.1 IV 1 IV 1 DV

1 EV 1 EV


EXPERIMENTAL RESEARCH DESIGN Q1. Hoppers Hop has 800 outlets all over India. They are planning a major sales promotion during the peak Diwali buying period. To determine the costing and maximized profitability, they have identified three different price levels P1, P2, P3 at which they can offer their goods. The sales volumes at their outlets vary from Rs.3,00,000 pm to Rs.30,00,000 pm. They are apprehensive about trying out all the 3 prices at each location as it may disturb their customer base. Hence, they have approached you to design an ext which would minimize customer disturbance, and at the same time provide solution profit maximization during Diwali. Additional information indicates that sales of the product specified are a function of the total sales at that particular store. You have identified 27 stores for your experiment and the process used is RBD.


EXPERIMENTAL RESEARCH DESIGN

Block no 1 2 3 4 5 6 7 8 9

Store rank X1 1,2,3 4,5,6 7,8,9 10,11,12 13,14,15 16,17,18 19,20,21 22,23,24 25,26,27 3 4 8 10 14 17 20 22 25

Treatment group X2 2 5 7 11 13 18 19 23 26 X3 1 6 8 12 15 16 21 24 27


EXPERIMENTAL RESEARCH DESIGN (ii) Latin Square Design (LSD) This allows control of non-interacting extraneous variables in addition to independent variables. It is similar to RBD technique. Q2. GKK Ltd. markets a face cream, Hair & Lovely thru 3 types of shops medical sore, super market, grocery (kirana) store. Sales of the product vary based on the store type. Sales also vary based on seasonality, which could be summer, monsoon, winter. The company desires to test out the impact of 3 different price discounts so as to rationalize its product pricing all India. For this purpose they have asked you to conduct an experiment which can be completed in 6-7 months. The process used is LSD.


EXPERIMENTAL RESEARCH DESIGN Process : Each extraneous variable is divided into equal number of blocks/levels. Independent variable is divided into same number of levels. Extraneous variables make up rows and columns of the table. IV is assigned to each cell such that each IV level appears only once in each row/column. Then use basic design on each cell. 3 x 3 Latin Square:Store Type Time period 1 2 3 Drug store Price 2 P1 P3 Super market P3 P2 P1 Grocery store P1 P3 P2


EXPERIMENTAL RESEARCH DESIGN (iii) Factorial Design This is used t measure the effect of 2 or more IV especially if interaction is likely. Interaction effect: Sum of combined effect Effect of IV1 + effect of IV2 Q3. Pesti Ltd. desires to launch a new soft drink for which they have options of (a) 5 levels of sweetness (b) 5 levels of carbonation. They desire to know the best combination for the new product. For this purpose, they have conducted an experiment using factorial design.


EXPERIMENTAL RESEARCH DESIGN Process : Each level of 1 IV is row, and the other is the column. A separate cell is for each combination. Each combination/cell is rated and average rating value is put into the cell using basic design). Analysis of Variance (ANOVA) is used to analyze favorable outcome and interaction.Carbonation 1 1 2 3 4 5 2 2 4 10 13 2 4 3 6 15 9 Sweetness 3 7 4 8 11 6 4 10 7 5 6 3 5 12 8 5 4 2


EXPERIMENTAL ENVIRONMENT :: LAB Design : This is widely used in package pretesting, ads, products and product concepts (i) Package testing (projector used): Respondents exposed to package options Allowed to examine while shopping(thru a controllable screen)

Shopping/identification speed measured (ii) Ads test (Tachistoscope used): Number of ads screened for visual impact Designs/messages evaluated fro recall.


EXPERIMENTAL ENVIRONMENT (iii) Products tests (blind tests used): Mainly for taste/utility :: FIELD Experiments Advertising copy field tests (using Day After Recall) Test marketing :- Standard Test Marketing (thru manufacturer distribution) - Controlled Test Marketing (thru marketing research firm) - Electronic Test Marketing (using electronic test marketing tools) - Simulated Test Marketing (pre-qualify users)


MEASUREMENT :: Definition: Assignment of numbers to characteristics of objects, persons, states or events, acc to some rules. :: Concept : A concept is an invented name for an object, person, state or event.(The above characteristics are called concept) eg : Sales (measured by volume or by value), Market share (Own sales / Total sales . Eg: For Bajaj Chetak, market share is calculated as sales of B.Chetak / total sales of all motorcycles/scooters. Therefore, be careful when using the term M.S bcoz the Denominator may vary. So always specify "MS of what??"), Brand Loyalty (cud be towards product, store, manufacturer)


MEASUREMENT Every concept is broken down into conceptual defn (defines a concept in terms of other concepts) & operational defn (describes activities to be completed in order to assign a value to the concept) Eg : take the concept 'Social class'. Conceptual defn will be "Hierarchical divisions in society to categories individuals / families with similar values, lifestyle, interests, behavior" Operational definition will be "Reputational: Ranking by people who know them Subjective : Based on self ranking Objective : Based on some / combined chars such as income, education, occupation"


MEASUREMENT :: Measurement Scales : There are 4 types of scales :(a) NOMINAL Numbers used to characterize objects or events (numbersused as symbols such as 0 for male & 1 for female)

(b) ORDINAL Numbers/letters/symbols used to rank items (Rank 1, 2 etc.But the problem is that 1st rank may have got 99% and 2nd rank might have got 88%)

(c) INTERVAL Numerically equal distance on the scale represents equal distance in property being measured. Location of 'zero point' not fixed. Eg : body temperature, CGPA scores (d) RATIO Interval scale with a meaningful zero. Eg : sales (if A sold10 units & B sold 20, B sold twice as much as A)


MEASUREMENT :: Measurement Accuracy : M M C E = C+E measurement correct value errors(occurs consistently for

Errors could be systematiceach measurement)

or variable

(occurs randomly for each measurement)


MEASUREMENT :: Measurement Development : Specify concept domain Generate item samples Collect data Purify measure Collect data Assess reliability Assess validity Develop norms


MEASUREMENT :: QUESTIONNAIRE DESIGN : Formalized set of questions for eliciting information A sound questionnaire requires applying: - Applicable principles - Common sense - Concern for the respondent - Clear concept of what information is needed - Thorough pre-testing


QUESTIONNAIRE DESIGN

Decision areas involved in questionnaire construction are: (a) Preliminary decisions (b) Decisions about question content (c) Decisions about question phrasing (d) Response format (e) Question sequence (f) Layout of the questionnaire (g) Pretest & revision


QUESTIONNAIRE DESIGN Preliminary decisions The factors that determine this are - Required information - From which respondents to get it (whom) - Interview technique cud be direct/indirect, structured/unstructured, medium personal, mail, telephone, computer


QUESTIONNAIRE DESIGN Question content: For each question, the researcher must ascertain I. Need for data

II. Ability of the question to produce data III. Ability of respondent to answer accurately cud be uninformed/forgetful/inarticulate IV. Willingness of respondent to answer accurately may not be willing in case of personal information/embarrassing information/prestige or normative information V. Potential for external events to bias answer.


QUESTIONNAIRE DESIGN I. Need for data The issue is how am I going to use the data obtained?. The technique is - create responses - analyse - ensure sufficiency - delete questions not required

II. Ability of the question to produce data Is one question adequate or should I break it up. Eg: Do u like big, sporty cars is ambiguous. It is better to ask Do u like big cars? and Do u like sporty cars?


QUESTIONNAIRE DESIGN III. Ability of respondent to answer accurately * uninformed (eg: National Bureau for Consumer Complaints) (eg: what is the current assessed value of your house can be answerd by the owner of the house. There may be three types of respondents - a genuine respondent who does not know; A genuine respondent who knows; Not genuine respondent. To avoid this u can ask Are u aware of the CAV of your house? Ans: Y/N. What do you think the CAV is? How close do you think your estimate is to the actual assessed value? Options: Rs.10000, Rs. 100000, Rs. 200000, Dont Know * forgetfulness ** omission use aided recall with condition ** telescoping something that happened in your distant past, u feel it happened in the near past. Use split interval + reverse position (split ballot)


QUESTIONNAIRE DESIGN **creation use aided recall with condition * inarticulate use projective techniques like sentence/story completion, and 2nd level association


QUESTIONNAIRE DESIGN IV.) Willingness of respondent to answer accuratelyPersonal information give explanation Ask at the end Ask in broad terms Build rapport first Use counterbiasing technique Use randomized response technique

Embarrassing information -

Prestige & normative technique Ask questions with graceful exits Eg: reading best-selling book


QUESTIONNAIRE DESIGNRandomized Response Technique: Used when sample size is large (>1000). It should be a large sample because when applying such probability you should work on large numbers. Used when information needed is embarrassing. The assumption is if the respondent is assured that the response cannot be tracked down to him/her, then he/she would speak the truth. It is typically used when the incidence of occurrence of certain events/conditions need to be found out.


QUESTIONNAIRE DESIGN Decisions about question phrasing Researcher & respondent should assign same meaning to questions. Issues:1. Words used (individual & together) should be understandable Eg: Would you be interested to buy any of these products? is different from Which one of these products would you be interested in buying? 2. Biased words/leading questions : Do you think India should allow public speeches against democracy? is different from Do you think India should ban p.s. against democracy?


QUESTIONNAIRE DESIGN Decisions about question phrasing 3. Clearly state alternatives involved in the questions (clarify): If there is further shortage of power, do u think there should be a law to reduce use of A/Cs in establishments in summer? or Do u oppose such a law? or Should it be left to each establishments choice? 4. Implied assumptions :Do you favor a ban on ads in movie halls? Clarify this by asking Would you mind paying extra for this? 5. Frame of reference assumed : Does GIC provide satisfactory settlement of claims? DO you believe that GIC provides.? Were you satisfied with GICs settlement of your latest claim?


QUESTIONNAIRE DESIGN Response format(i) Open ended Advantages : No influence on respondents Wide variety of responses Feel for quality Quotes can be used Disadvantages : Not easy to analyze and interpret Respondent may not answer adequately Interviewer may not probe adequately (ii) Close ended multiple choice/dichotomous


QUESTIONNAIRE DESIGN Response formatMultiple choice: Advantages : Easy to administer Reduces interviewer bias Tabulation & analysis is simple Disadvantages : Development needs a lot of effort Issues: 1. Number of alternatives (each should appear only once, all possible alternatives should be included) 2. Alternative to be balanced 3. Remove position bias by using split-ballot technique (if alternatives are read out, preference is for last alternative) (if alternatives are given together, preference is for first)


QUESTIONNAIRE DESIGN Response formatDichotomous: Issues: 1. May include 3rd option (dont know, no opinion, cant say) 2. Form may influence results, so use split ballot technique.


QUESTIONNAIRE DESIGN Question sequence1. Start with simple, interesting objective questions 2. Complete questions of one topic before moving to next topic 3. Move from topic to topic in a logical way 4. Initial questions to avoid providing biased frame of reference, or suggest answers to future questions.


QUESTIONNAIRE DESIGN Layout of the questionnaire1. Physical appearance should make it easy to use 2. Layout to minimize mistakes (avoid go to statements)


QUESTIONNAIRE DESIGN Pretest & revision1. Mandatory for all questionnaires 2. Decisions involved are: - What items to pretest? - How should it be conducted (std administration,debriefing, protocol analysis)

- Who should conduct it(Field exec, research associate, research head)

- Which respondents should be involved(known people, unknown people, part of sample)

- How many respondents?(Field exec should go to as many respondents as he can cover in one working day, research associate should go to as many respondents as required until further pre-testing does not result in any change in the questionnaire, research head should pre-test it with 5-8 respondents outside the office)

3. Language issues: (Especially in India). Do back-translation


QUESTIONNAIRE DESIGN :: Direct Response Attitude ScaleAttitude is a persons enduring organization of cognitive, affective & behavioral components & processes with respect to some aspect of an individuals world. Cognitive Affective Behavioral : persons beliefs or information about the object : persons feelings of like/dislike about object : Action tendencies towards object

Substantial part of marketing effort is to assess/influence attitudes of consumers & intermediaries.


QUESTIONNAIRE DESIGN :: Direct Response Attitude ScaleAttitudes can be measured - directly (DRAS) - indirectly (Derived AS) Measures attitude directly Two types: - Rating scale (to measure single dimension) - Attitude scales (to measure multi dimensions,

it is a combination of rating scales).

Rating scales: Attribute of an object being marked on a numerically valued continuum or in numerically ordered category.


QUESTIONNAIRE DESIGNTypes of rating scales:Rating Scale Non-comparative (monadic) Graphic Itemised Graphic Comparative Itemised Specific Paired comparison Rank order Constant sum


QUESTIONNAIRE DESIGNNon-comparative (monadic): Respondent not provided with a standard to use in the rating. Only one product/brand is evaluated (hence, monadic). Commonly used at product concept testing stage in new product development processEg: Intention to buy, using a Juster scale (11 pt)10. Certain/practically certain 9. Almost sure 8. Very possible 7. Probable 6. Good possibility 5. Fairly good possibility 4. Fair possibility 3. Some possibility 2. Slight possibility 1. Very slight possibility 0. No chance/almost no chance (99 in 100) (9 in 10) (8 in 10) (7 in 10) (6 in 10) (5 in 10) (4 in 10) (3 in10) (2 in 10) (1 in 10) (1 in 100)


QUESTIONNAIRE DESIGNNon-comparative (monadic): Reduce position bias by reversing order on 50% of questionnaires Top box score is used for prediction. Top box : % of respondents who mark one of two most favourable ratings. If at least x% threshold of top box score is crossed, product concept is taken forward.


QUESTIONNAIRE DESIGNGraphic Non-Comparative Rating Scale: Requires respondent to indicate rating by placing a mark on the line that runs from one extreme to the attitude being studied to the other extreme Response is then broken up into categories for analysis. Never used.


QUESTIONNAIRE DESIGNItemized Non-Comparative Rating Scale: Requires respondent to select one of a limited number of categories, ordered in terms of their scale positions Types: (i) D-T scale (Delighted Terrible) scale. Eg: How do u feel after seeing the movie KKHH? Scale varies as Delighted, Pleased, Mixed, Unhappy, Terrible. (ii) Percentage scale. Eg: How much did u like KKHH? Scale varied from 0, 25, 50..100%. 100 is completely satisfied,0 is not at all satisfied. (iii) Need semantic differential scale: Eg: To what extent does your AC meet your needs? Scale is from 1 to 7. 1 is poorly. 7 is extremely well.


QUESTIONNAIRE DESIGNRecommendations on using itemized rating scales: 1. Use precise verbal definitions for at least some categories 2. Use 5 categories when several scales are to be summed up for 1 scale 3. Use up to 9 categories when attributes are being compared across objects by knowledgeable respondents. 4. Use balanced scales as much as possible. 5. Use odd number of categories if respondent could feel neutral, even if this is unlikely 6. Let the choice not be forced upon the respondent. That is, give option of not knowing/not applicable unless it is known that all respondents have required knowledge. 7. Adjust rating scale to nature of information required and characteristics of respondents.


QUESTIONNAIRE DESIGNComparative rating scales: In non-comparative, rater evaluates the object without direct response to a specific standard. Hence respondent may apply different reference points. Eg: rate quality of brand X? - ideal brand - current brand - average ebrand To obtain uniformity, use known reference pt (pre-specify). Eg: Compared to the soft drink I generally drink, Diet Coke is: You have to find out what soft drink the guy usually drinks (ref pt). Otherwise it is like non-comparative scale.


QUESTIONNAIRE DESIGNComparative rating scales:A A B C D E B C D E

Visual inspection Brand B is preferred


QUESTIONNAIRE DESIGNRank order rating scale :

Requires respondent to rank a set of objects according to some criterion. All relevant brands need to be included (options). Simulates actual shopping environment. Faster response time. Produces only ordinal data.


QUESTIONNAIRE DESIGNConstant sum scale :

Requires respondent to divide a constant sum (10 or 100) among two or more objects/attributes in order to reflect respective relative preference for each objects/attributes. Can be used for 2 objects (paired comparison) More than 2 : quadric comparison Eg: Suppose 2 wheeler attributes are to be ranked with 1 being more important. Following median ranks are produced: Price Economy Reliability Safety Comfort Style : : : : : : 1 2 3 4 5 6



In constant sum, divide 100 pts among characteristics so that the division indicates how important each characteristic is in he purchase decision. Economy: Style: Price: Comfort: Reliability: Safety: TOTAL = 100



3 groups emerge:Group A Price Eco Rel Saf Comf Style 35 30 20 10 3 2 Group B 20 18 17 16 15 14 Group C 65 9 8 7 6 5

Findings are more detailed than rank order. Can even help to determine target market. If total > 100 or < 100, adjust it to 100.


QUESTIONNAIRE DESIGNAttitude scales:: scales:

Carefully constructed set s of rating scales designed to measure individuals attitude towards objects. Response to various scales may be summed up or examined independently. Scale developed using method studied before. Forms 1. Semantic differential scale 2. Stapel scale 3. Likert scale


QUESTIONNAIRE DESIGN1. Semantic differential scale Rater is required to rate objects on a number of itemized 7point rating scale, bounded by oppositely adjectives at each end (bipolar adjectives). Eg: for the Zen Fast ----------------- Slow Plain -------------- Stylish You can also compare 2/more brands on the same scale: Fast ----------------- Slow Plain -------------- Stylish


QUESTIONNAIRE DESIGN1. Semantic differential scale People place the Zen, Alto, Matiz on different scales. Numbers can be assigned to each option (1-7) Analysis may be through - Aggregate analysis (combination of constant sum and SDscale. Multiply the weight by the rating, for each product)

- Profile analysis


QUESTIONNAIRE DESIGN2. Stapel scale: Simplified version of the SD. Standard is unipolar, 10 interval rating scale with values from +5 to -5. Any number of values can be used. Values can be all positive. Eg: What are your views about XYZ stores: Large 3 2 1 -1 -2 Friendly 3 2 1 -1 -2 Low priced 3 2 1 -1 -2 -3 -3 -3

It is good for telephonic interviews, because it saves time. It is similar to SD, and easy to administer.19


QUESTIONNAIRE DESIGN3. Likert scale (summated scale): Respondent needs to indicate agreement/disagreement to a series of statements related to objects. Value may be assigned to each option for analysis. 5 pt Likert 7 pt : Strongly agree, agree, neither, disagree, strongly disagree : SA, moderately agree, mildly agree, neither..etc

Eg: XYZ is one of the most attractive stores (SA,A,N,D,SD) Service at XYZ is not satisfactory (SA,A,N,D,SD) Service is very important to me (SA,A,N,D,SD)


QUESTIONNAIRE DESIGNWhich Scale to Use ?

Depends on: Information requirements of the problem Characteristic of response Means of administration Cost In general, - Use multiple measures since summation of measurements is more accurate.


SAMPLING Need for sample planning:Objective of MR is - estimation - hypothesis testing. Each involves making inferences about a population on the basis of information from a sample. Accuracy of survey results are affected by the manner of sampling.


SAMPLING Steps in sample planning:Define Population

Census Vs Sample

Sample Design

Sample Size

Estimation of sampling costs Execute sampling process


SAMPLINGPopulation definition:

Definition should include - element - sampling unit - extent - time Eg: MR for detergents: The population should include price of each brand kirana outlets, in Mah & Guj, from Jan-Mar 200508-23 Eg: Financial institution with new loan instruments: Population should be all depositors who have borrowed money from NBFCs, in metros Mumbai & Chennai, during the last 2 years.


SAMPLINGCensus vs Sample:

Census includes the entire population. Sample is a representative part of the population. Census may not be feasible all the time. Hence use sample. Advantages of sampling: speed/timelines & costs However we need to use census in cases when the population is very small. Eg: If you supply to 15 clients (the census), you can do a research on all 15 (since the population is very small). Eg: Medical research for rare disorders.


SAMPLINGSample design:

Sample frame: This is a means of representing elements of the population.Eg: telephone directory. It is not used for non-probability sampling.

Sampling unit: This is the basic unit containing elements of the population to be sampled.

Eg: Loan instrument Sampling Unit could be businessmen with over 5 yrs experience (because 5 yrs is the repayment period. So they would have gone through the entire cycle).

Sampling method: This describes the method by which sample units are to be selected for measurement. Options: - probability/non-probabilitysingle unit/cluster of units stratified/unstratified equal unit probability/unequal unit probability single stage/multi stage


SAMPLINGNon-probability sampling procedures:

(i) Convenience sampling: Based on convenience of sampling.Eg: to test new food product, add it to menu card at a restaurant. Advantages: quick, inexpensive

(ii) Judgement sampling/purposive sampling: Representative sampling is drawn up using judgement selection procedure.Eg: An organizations new products always failed. Hence sample for study was competition with compatible products (products that are not competing, but are being sold in the same way. Eg: shampoo & toothpaste)


SAMPLINGNon-probability sampling procedures:

(iii) Quota sampling: Sizes of subclasses of population estimated. Sample would contain compatible % of subclasses.Eg: in a research for fountain pens, subclasses would be students, employees, businessmen, persons, housewives. Whatever % these subclasses constitute, you should choose people from these subclasses in the same % for your sample.

(iv) Snowball sampling: Sample few based on judgment / random/convenience. Take referrals, include referrals in your sample. Called Snowball because the size of your sample keeps increasing as your research proceeds.Eg: MR for travel/tourism, Readers Digest asks for referrals.


SAMPLINGProbability sampling: Sampling unit is selected by chance. Chance of each unit being selected is known. Designs: (i) Simple random sampling (SRS): Each sample unit has a known and equal probability of selection. It is drawn by random procedures from the sample frame. (ii) Systematic sampling: Each sampling unit has a known probability of selection. Permissible samples have known & equal probability. Others have known & zero probability.Eg: Population size = N, sample required = n, arrange units (in say, ascending order). At N/n th interval, select a unit (maybe 1st or 2nd). N = 600, n = 60, Sampling interval = 10. Select random number between 1-10 (say 5). Then sample elements are 5/15/25/35.


SAMPLING(iii) Stratified sampling : Divide population into strata based on some criteria. Then do SRS within strata. Difference in: in quota sampling, you use convenience sampling, in this you use SRS. (iv) Cluster sampling: - Select primary sampling unit at random. - Sample all elements in selected PSU. - Eg: survey of sales staff of a pharma company - Select geographical area at random. - Sample all sales staff in selected area. - Advantage : Depth interviews possible at low cost. (v) Area sampling: - Select areas at random. - Within areas, select respondents at random.


SAMPLINGSample size :

Sample size determined using following approaches: Unaided judgment Affordability (all you can afford) Size indicated by similar studies (take average) Required size per cell Traditional statistical methods Bayesian statistical model

Unaided judgment: - Arbitrary approach - Precision not clear - Costing not taken into account - Used commonly, nut should be avoided



Affordability (all you can afford) - Based on budget - At times practical - Sometimes leads to unnecessary data collection Size indicated by similar studies (take average) - Can be used as initial aid - Formal judgment to be used case-to-case Required size per cell - Used for SRS/stratified random/purposive/quota - Eg: Fast food joint: Information required from 2 groups service/businessmen. Four age groups created: 2025/25-35/35-50/50+. Sample of 30 needed in each group. Hence total sample = 30 * 4 * 2 = 240



Traditional statistical methods Sampling distribution of mean: This is the relative frequency distribution of the means of all possible samples of size n, taken from a population the size N.Eg: Super Shoppe has a direct mail campaign during Diwali, which generated 1250 invoices. Suppose sample size = 50.

Then total possible samples =

1250! (1250 50!) 50!

This is a very high number. Hence (take for eg) 500 samples. Determine mean of each sample.


SAMPLINGValue of mean 38 39.99 40 41.99 42 43.99 44 45.99 46 47.99 48 49.99 50 51.99 52 53.99 54 55.99 56 57.99 58 59.99 60 61.99 62 63.99 TOTAL Frequency of occurrence 1 2 17 39 52 85 110 77 64 37 10 4 2 500 Rel Freq of sample mean .002 .004 .034 .078 .104 .170 .220 .154 .128 .074 .020 .008 .004 1.00


SAMPLING These means would be distributed normally in terms of their relative frequency of occurrences. Relative frequency then can be a measure of probability. If all possible samples were taken, we would have obtained mean which would also be distributed normally with a mean value very close to mean value calculated from 500 samples. Hence sample characteristics can be said to represent the population


SAMPLING

We can infer that a sampling distribution of the mean for SRS samples has: - Normal distribution - Mean equal to population mean - SD called standard error of mean . That is equal to population standard deviation divided by square root of sample size


SAMPLING

Basically we are trying to find would want the sample size mean as possible. The larger to the mean & thus the error N = 1250 N = 50 N = s2z2 /E2

out the ideal sampling size. We to be as close to the population the sampling size, the closer it is is smaller.


SAMPLINGQ1. A soft drink company desires to determine the annual per capita consumption of soft drinks in Pune. For this purpose they would like to carry out a research for which a max error is 0.5lt per capita per year. With a confidence level of 95%. A pilot sample taken to estimate population dispersion (SD) indicates a value of 8 liters of per capita per year. Determine the minimum sample size if the response rate is 25%. S=8 Now the 0.95 Form the table, the value is read as 1.96.

0.95 / 2 = 0.475.

Therefore, z = 1.96 E = 0.5 N = s2z2 /E2 = 984.


SAMPLINGMultiply by 4 for the 25% response rate. Therefore answer = 984 * 4 = 3936 If the error is 1, and the confidence level is 60% E=1 Z = 0.84


DATA REDUCTIONThis is the process of getting data ready for analysis. It is intermediate to data processing. Steps involved: (i) Field controls (ii) Editing (iii) Coding (iv) Transcribing (v) Generating new variables (vi) Summary statistical calculation


DATA REDUCTION(i) Field controlsThese are procedures designed to minimize errors during actual data collection, thru monitoring and validation. Monitoring happens when data is being collected. Validation is checking it after data collection.

(ii) EditingData considered should be current, present , readable & accurate. This is the editors responsibility. Missing data could be filled in through imputation, trend analysis and plug-in values. For ambiguous data, the editor has to set standards for evaluation.

(iii) CodingCoding involves establishing categories and assigning data to them. Categories established as per QD procedures. Categories shown by numbers as much as possible. Data assignment is relatively simple for close-ended questions. For open-ended, create a code-book to indicate system of coding used. That ensures uniformity.


DATA REDUCTION(iv) TranscribingThis is the process of physically transferring data from measurement instrument to computer storage. At times may be time consuming, hence it needs to be planned for.

(v) Generating new variablesThis may be required as a pre-cursor to analysis. New variables may be generated from combinations of other variables in data. Eg: persons age/marital status/number and age of children indicates stage in family life cycle. Data may be collected thru interval scale and later assigned to classes. Eg: Family income in Rupees/year may then be put into groups. New variables may be added thru secondary data Eg: median income/education in a geographic area. Data may need to be transformed into another functional form (inverting the 50% where you have used splitballot technique).


DATA REDUCTION(vi) Summary statistical calculation Create basic data array. Tabulate frequency distributions. - One way tabulation (with one variable) - Cross tabulation (two variable) - Banners ( more than 2 variables) Calculate central tendency and dispersion (SD, variance, range) Estimation (either point or interval estimation). Both are in terms of means & proportions. If the sample size < 30, use t statistic If the sample size < 30, use z statistic

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RM (Research Methodology)