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GROUPING QUESTIONS INTO SECTIONS OF THE SURVEY

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GROUPING QUESTIONS INTO SECTIONS OF THE SURVEY. Relevance, ease, interest, answerability. Internal logic of questionnaire & smooth progression through questionnaire. ... – PowerPoint PPT presentation

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Title: GROUPING QUESTIONS INTO SECTIONS OF THE SURVEY


1
GROUPING QUESTIONS INTO SECTIONS OF THE SURVEY
  • Relevance, ease, interest, answerability.
  • Internal logic of questionnaire smooth
    progression through questionnaire.
  • Keep questions on same topic together.
  • Keep questions with same response options
    together.
  • First sections should appear fairly easy
    important (e.g., personal experiences or
    opinions, topics extensively covered in the mass
    media, local or regional issues, etc.).
  • Watch for context redundancy effects.

2
MORE ON CONTEXT AND REDUNDANCY EFFECTS
  • Context effects occur when answers to one
    question influence an answer to a subsequent
    question. (e.g., How worried are you about
    crime in your neighborhood? followed by Do you
    know of anyone who has been a victim of a crime
    in your neighborhood?)
  • Redundancy effects occur when respondents are
    influenced by detailed answers when asked to
    provide a more general answer. (e.g., a series
    of questions about course content, time tabling,
    housing, safety at Nipissing University followed
    by a general or overall evaluation of Nip. U.)

3
GROUPING OF QUESTIONS IN A HYPOTHETICAL CRIME
SURVEY
  • Perceptions on crime in general.
  • Perceptions on specific types of crime.
  • Personal experiences with crime.
  • Personal fear about crime.
  • Actions taken to protect self, friends, family.
  • Perceptions about Criminal Justice System in
    general.
  • Perceptions about specific components of the
    Criminal Justice System (courts, policing,
    corrections).
  • Demographics.

4
QUESTIONNAIRE LENGTH
  • Telephone surveys (10-20 minutes).
  • Face-to-face interviews (30 minutes - 60 minutes)
  • Mailed surveys (3 - 6 pages)
  • Internet surveys (varying lengths depending on
    how many questions per computer screen).
  • Major Determinants money resources
    information required expected interest/motivation
    of respondents strengths/limitations of mode
    of administration.

5
MORE ON QUESTIONNAIRE LENGTH
  • What motivates respondents?
  • Interesting topic questionnaire?
  • Important topic?
  • Actions resulting from study?
  • Questionnaire appears professional, easy,
    straightforward?

6
GUIDELINES FOR MAILED QUESTIONNAIRES.
  • Maximum 5-8 pages.
  • lower case questions UPPER CASE RESPONSES.
  • Number response options.
  • Space questions answers.
  • Questions horizontal responses vertical.
  • Brief, simple instructions when changing topics
    and/or response options.
  • Different typefaces for transitions (section
    headings).
  • Arrows indicate skip instructions.

7
AVOIDING OTHER FLAWS IN MAILED SURVEYS
  • Minimize open-ended questions.
  • Avoid complex words.keep them simple
  • - Is the word found in everyday usage (e.g.,
    newspapers, TV)?
  • - Is there a simpler word that conveys the same
    meaning?
  • - If you must use a specialized wordcheck its
    meaning with experts.
  • - Pretesting self-administered questionnaire
    allows feedback on ambiguous or difficult
    questions.

8
SELECTING THE SURVEY METHOD.
  • THREE MAJOR SURVEY TYPES MAIL, TELEPHONE,
    FACE-TO-FACE.
  • INTERNET SURVEYS.RAPIDLY GROWING!
  • GROUP-ADMINISTERED SURVEYS. MINOR TYPE OFTEN
    USED IN COMBINATION WITH A MAJOR TYPES.

9
EVALUATING THE PROS AND CONS OF THE 3 MAIN
METHODS
  • THREE CATEGORIES OF FACTORS
  • 1. ADMINISTRATIVE/RESOURCE FACTORS.
  • 2. QUESTIONNAIRE ISSUES.
  • 3. DATA-QUALITY ISSUES.
  • REFER TO THE HANDOUT..

10
  • ADMINISTRATIVE/RESOURCE ISSUES ( HOW MUCH
    TIME MONEY?)
  • QUESTIONNAIRE ISSUES (HOW MANY WHAT KIND OF
    QUESTIONS).
  • DATA QUALITY ISSUES (RESPONSE RATE, ACCURACY
    COMPLETE ANSWERS).

11
  • THE FIRST 3 QUESTIONS WE NEED TO ASK OURSELVES
    ARE
  • 1. WHO ARE SURVEY RESPONDENTS?
  • 2. IS RESEARCH QUESTION MORE AMENABLE TO ONE
    METHOD?
  • 3. HOW MUCH TIME MONEY DO I HAVE?

12
MAIL SURVEYS
  • COVER LETTER QUESTIONNAIRE.
  • COVER LETTER INCLUDES PURPOSE, SPONSOR,
    INSTRUCTIONS, CONFIDENTIALITY, CONTACT
    INFORMATION.
  • THE QUESTIONNAIRE IS TOTALLY SELF-EXPLANATORY.IT
    MUST BE CLEAR SIMPLE!.
  • OPTIMUM RESPONSE RATES REQUIRE REMINDER LETTERS
    AND A SECOND QUESTIONNAIRE.

13
ADVANTAGES OF MAIL SURVEYS
  • ONE OF THE CHEAPER METHODS.
  • MOST COSTS ARE FIXED AND PREDICTABLE.
  • CAN CONSULT HOUSEHOLD RECORDS OR VISUAL AIDS.
  • GOOD METHOD FOR SENSITIVE TOPICS.
  • TIME TO COMPLETION IS PREDICTABLE.
  • RESPONSE RATES CAN BE GOOD.

14
DISADVANTAGES OF MAIL SURVEYS
  • RESPONSE BIAS.
  • QUESTIONNARIE LENGTH APPEARANCE.
  • QUESTIONNAIRE MUST BE SELF-EXPLANATORY.
  • NO CONTROL OVER ORDER OF ANSWERS.
  • NO CONTROL OVER WHO ANSWERS.
  • POOR FOR OPEN-ENDED QUESTIONS.

15
ADVANTAGES OF TELEPHONE SURVEYS
  • TELEPHONES RANDOM DIGIT DIALING TECHNOLOGY
    PROVIDES EXCELLENT POPULATION COVERAGE.
  • DATA QUALITY IS GOOD.ESPECIALLY FOR SURVEYS
    THAT TAKE LESS THAN 30 MINUTES FOCUS ON RECENT
    ATTITUDES OR BEHAVIORS.
  • USUALLY INTERMEDIATE IN COST BETWEEN MAIL
    FACE-TO-FACE INTERVIEWS.

16
  • INTERVIEWERS, WORK CENTER, COMMUNICATIONS
    MONITORING EQUIPMENT, SAMPLE, SUPERVISERS.
  • INTERVIEWERS ARE A MIXED BLESSING.THEY SPEED UP
    SURVEY BUT MUST BE SELECTED, HIRED, TRAINED,
    SUPERVISED.
  • LOW SAMPLING FRAME BIAS (WITH RDD).
  • GENERAL WILLINGNESS TO BE INTERVIEWED.
  • RESPONSE RATES HIGHER THAN MAIL SURVEYS.

17
  • USUALLY THE FASTEST SUVEY METHOD.
  • INEXPENSIVE SAMPLING FRAMES.
  • GOOD INTERVIEWERS ADD VALUE TO RESPONSES.
  • CAN USE COMPLEX QUESTIONNAIRE FORMATS.
  • GOOD INTERVIEWERS CAN CLARIFY QUESTIONS.
  • CONTROL ORDER OF QUESTIONS.
  • RAPPORT CAN REDUCE NONRESPONSES AND HELP WITH
    SENSITIVE QUESTIONS.

18
DISADVANTAGES OF TELEPHONE SURVEYS
  • MUST USE SHORT, SIMPLE QUESTIONS.
  • MUST USE FEW, SHORT, SIMPLE ANSWER CHOICES.
  • NO VISUAL AIDS.
  • LIMITED CONTROL OF INTERVIEW SITUATION.
  • OPEN-ENDED QUESTIONS.

19
FACE-TO FACE SURVEYS
  • INTERVIEWS DONE IN PLACE TIME CONVENIENT FOR
    RESPONDENT.
  • INTERVIEWS ACCOUNT FOR MUCH OF THE EXPENSE
    ASSOCIATED WITH THIS METHOD.
  • PREFERRED METHOD FOR CERTAIN GOALS.

20
FACE-TO FACE SURVEYS ADVANTAGES
  • HIGHEST RESPONSE RATE OF ANY METHOD (80 ).
  • MORE CONTROL OF INTERVIEW SITUATION.
  • RAPPORT PRODUCES TOP-QUALITY DATA.
  • COMPLEX, LONG QUESTIONS.
  • VISUAL AIDS.
  • CONTROL QUESTION ORDER.

21
FACE-TO FACE SURVEYS ADVANTAGES
  • BEST FOR OPEN-ENDED QUESTIONS.
  • PROBE FOR ANCILLARY INFORMATION.
  • MORE TIME IS POSSIBLE.
  • CONSULT RECORDS/FILES.

22
FACE-TO FACE SURVEYS DISADVANTAGES
  • MOST EXPENSIVE METHOD.
  • LONGEST METHOD.
  • NEED GOOD INTERVIEWERS TO HANDLE SENSITIVE
    QUESTIONS.
  • SOCIALLY DESIREABLE POLITICALLY CORRECT
    RESPONSES.

23
ADVANTAGES ON ONLINE SURVEYS
  • LOW COST (Can be costly to collect data with some
    web survey hosts).
  • SPEED (can add time deadlines to qualify for
    incentives).
  • VARIETY OF QUESTION TYPES CONTENT OPTIONS
  • POTENTIALLY HUGE AUDIENCE
  • GOOD FOR OPEN-ENDED QUESTIONS
  • GOOD FOR SENSITIVE QUESTIONS (if e-mail addresses
    are not recorded).

24
COMBINING SURVEY METHODS
  • COMBINATIONS CAN BE USED TO OFFSET DISADVANTAGES.
  • COMMON COMBINATIONS ARE MAIL TELEPHONE OR
    INTERNET FACE-TO-FACE SELF-ADMINISTERED
    QUESTIONNAIRE.
  • COMBINING SURVEY METHODS DEPENDS ON YOUR RESEARCH
    PROBLEM AND YOUR AVAILABLE RESOURCES.

25
Basic Concepts in Samples and Sampling
  • POPULATION
  • SAMPLE
  • SAMPLING UNIT
  • CENSUS
  • SAMPLING EFFOR
  • SAMPLING FRAME
  • SAMPLING FRAME ERROR

26
SAMPLING.
  • 1. PROBABILITY NONPROBABILITY SAMPLING.
  • 2. WITH PROBABILITY SAMPLING WE KNOW THE
    PROBABILITY OF SELECTION FOR ANY ELEMENT
  • IN OUR POPULATION.
  • 3. PROBABILITY SAMPLING ALWAYS INVOLVES SOME
    KIND OF RANDOM SELECTION PROCEDURE.

27
  • PROBABILITY OF SELECTION (P.O.S.) IS THE
    LIKELIHOOD THAT AN ELEMENT WILL BE SELECTED FROM
    THE POPULATION FOR INCLUSION IN THE SAMPLE.
  • WITH A POPULATION CENSUS THE P.O.S. IS 1.0
    AS SAMPLE SIZE DECREASES, SO DOES THE P.O.S.
    INTO THE SAMPLE (YOUR P.O.S INTO A SAMPLE OF
    25,000 CANADIANS IS GREATER THAN YOUR P.O.S INTO
    A SAMPLE OF 100 CANADIANS).
  • WITH RANDOM SAMPLING, CASES ARE SELECTED INTO THE
    SAMPLE ONLY ON THE BASIS OF CHANCE.PARADOXICALLY,
    THIS REQUIRES CAREFUL CONTROL OF THE SAMPLING
    PROCESS.

28
  • EVEN WITH RANDOM SAMPLING WE MAY END UP
    WITH AN UNREPRESENTATIVE SAMPLE IF WE
    HAVE.
  • (1) AN MATERIALLY INADEQUATE OR INCOMPLETE
    SAMPLING FRAME (E.G., A TELEPHONE DIRECTORY
    FROM ANY LARGE CITYUNLISTED PHONE NUMBERS CAN
    RANGE FROM 10 - 30 OF THE POPULATION).
  • (2) AN INADEQUATE RESPONSE RATE (E.G., BE
    CAUTIOUS IF YOUR NONRESPONSE RATE EXCEEDS 30 OF
    THE SAMPLE).

29
PROBABILITY SAMPLING
  • KNOWN, NON-ZERO CHANCE OF SELECTING EACH
    POPULATION ELEMENT INTO THE SAMPLE.
  • NO MAJOR SYSTEMATIC BIAS.ONLY CHANCE
    DETERMINES WHICH ELEMENTS ARE INCLUDED.
  • USE WHENEVER A MAJOR RESEARCH GOAL IS TO
    GENERALIZE SURVEY FINDINGS TO A LARGER
    POPULATION.
  • IS STILL SUBJECT TO RANDOM SAMPLING ERROR.

30
MORE ON RANDOM SAMPLING ERROR...
  • SAMPLE SIZE AND POPULATION HOMOGENEITY
    (POPULATION SAMENESS) AFFECT THE AMOUNT OF
    RANDOM SAMPLING ERROR.THE PROPORTION OF THE
    POPULATION THAT THE SAMPLE REPRESENTS DOES
    NOT!

31
.
  • THE LARGER THE SIZE OF THE SAMPLE, THE MORE
    CONFIDENCE WE CAN HAVE IN THE SAMPLES
    REPRESENTATIVENESS ( lt RANDOM SAMPLING ERROR).
  • THE MORE HOMOGENOUS OUR POPULATION, THE
    MORE CONFIDENCE WE CAN HAVE IN THE SAMPLES
    REPRESENTATIVENESS (LESS RANDOM SAMPLING
    ERROR).
  • SAMPLING FRACTIONS HAVE LITTLE IMPACT ON OUR
    SAMPLES REPRESENTATIVENESS ( OR ON RANDOM
    SAMPLING ERROR).

32
  • DIFFERENT TYPES OF PROBABILITY SAMPLES VARY
    IN THEIR RANDOM SAMPLING ERROR.
  • 4 MAJOR TYPES
  • SIMPLE RANDOM.
  • SYSTEMATIC.
  • STRATIFIED.
  • CLUSTER.

33
SIMPLE RANDOM SAMPLING.
  • REQUIRES A PROCEDURE FOR ASSIGNING UNIQUE
    NUMBERS TO ALL ELEMENTS IN THE SAMPLING
    FRAME, AND THEN IDENTIFYING CASES STRICTLY
    ON THE BASIS OF CHANCE
  • .BY USING A RANDOM NUMBERS TABLE,
  • .OR A COMPUTER PROGRAM THAT GENERATES
    RANDOM NUMBERS.
  • OR RANDOM DIGIT DIALING (FOR TELEPHONE
    INTERVIEWS OR WHENEVER AN ADEQUATE SAMPLING
    FRAME IS UNAVAILABLE).

34
  • PROBABILITY OF SELECTION IS EQUAL FOR EACH
    ELEMENT.
  • IF n 500 and N 17,000, than
    p n/N 500/17,000 .03
  • IF n 2000 and N 30,000,000, than
    p n/N 2000/30000000 .00006
  • SIMPLE RANDOM SAMPLING IS AN EPSEM METHOD
    (Equal probability of being selected method).

35
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36
SYSTEMATIC RANDOM SAMPLING
  • VARIANT OF SIMPLE RANDOM SAMPLING.THE FIRST
    ELEMENT IS SELECTED RANDOMLY FROM A LIST
    AND THEN EVERY nth ELEMENT IS SELECTED.
  • CONVENIENT WHEN ELEMENTS ARE ARRANGED
    SEQUENTIALLY.

37
THREE STAGES IN SYSTEMATIC RANDOM SAMPLING
  • TOTAL NUMBER OF CASES DIVIDED BY THE
    DESIRED SAMPLE SIZE PROVIDES YOU WITH YOUR
    SAMPLING INTERVAL ( I N / n)where I is
    your sampling interval N is the population
    size and n is the sample size.
  • A NUMBER FROM 1 TO I (YOUR SAMPLING
    INTERVAL) IS SELECTED RANDOMLY.
  • AFTER THE FIRST CASE IS SELECTED, EVERY
    Ith CASE IS SELECTED FOR YOUR SAMPLE.

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  • SYSTEMATIC RANDOM SAMPLING TYPICALLY PROVIDES
    SAMPLES THAT ARE AS GOOD (REPRESENTATIVE)
    AS SIMPLE RANDOM SAMPLES.
  • AVOID USING SYSTEMATIC RANDOM SAMPLING IF
    THERE IS SOME UNDERLYING PATTERN OR
    PERIODICITY IN YOUR SAMPLING FRAME.SEE THE
    HANDOUT.
  • PERIODICITY IS RARE SO DONT BE PARANOID
    ABOUT IT!

40
STRATIFIED RANDOM SAMPLING
  • STRATIFIED RANDOM SAMPLING USES POPULATION
    INFORMATION (E.G., CENSUS DATA) TO MAKE
    SAMPLING MORE EFFICIENT EASY.
  • SAMPLING IS EFFICIENT WHEN YOU CAN OBTAIN
    GOOD STATISTICAL ESTIMATES EASIER SAMPLING
    IS EASIER WHEN IT REQUIRES LESS TIME, ,
    OR PRIOR INFORMATION.

41
  • ALL ELEMENTS IN THE SAMPLING FRAME ARE
    IDENTIFIED BY STRATA (E.G., GENDER, ETHNICITY,
    RELIGION, ETC.).
  • ELEMENTS ARE SELECTED (WITH SIMPLE OR
    SYSTEMATIC RANDOM SAMPLING) FROM WITHIN EACH
    STRATA.

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  • WHY IS STRATIFIED RANDOM SAMPLING MORE
    EFFICIENT?
  • SIMPLE OR SYSTEMATIC RANDOM SAMPLING CAN
    PRODUCE DISPROPORTIONATE SUB-GROUPS IN YOUR
    SAMPLE (SEE THE HANDOUT).
  • PROPORTIONATE STRATIFIED SAMPLING CAN
    ELIMINATE THIS SOURCE OF RANDOM SAMPLING
    ERROR.
  • DISPROPORTIONATE STRATIFIED SAMPLING ENABLES
    YOU TO DO STATISTICAL ANALYSES WITH
    UNWEIGHTED DATA AND STATISTICAL ESTIMATION
    WITH WEIGHTED DATA.

44
  • WHY WOULD YOU WANT TO USE DISPROPORTIONATE
    STRATIFIED SAMPLING?
  • TO ENSURE THAT ENOUGH CASES ARE INCLUDED
    IN SMALL STRATA SO THAT MEANINGFUL ANALYSES
    AND COMPARISONS CAN BE PERFORMED.

45
CLUSTER SAMPLING
  • REQUIRES LESS PRIOR INFORMATION THAN
    STRATIFIED SAMPLING.
  • USEFUL FOR SURVEYS INVOLVING A LARGE,
    DISPERSED POPULATION AND DEVELOPING
    SOCIETIES..WHERE ADEQUATE SAMPLING FRAMES ARE
    HARD TO CONSTRUCT.

46
CLUSTER SAMPLING
  • A CLUSTER IS A NATURALLY OCCURRING GROUP OF
    ELEMENTS IN A POPULATION (E.G.,
    UNIVERSITIES, CITY BLOCKS, ETC.)
  • EACH ELEMENT APPEARS IN ONE AND ONLY ONE
    CLUSTER.
  • DRAWING A CLUSTER SAMPLE IS AT LEAST A 2
    STAGE PROCESS.CAN INVOLVE SEVERAL STAGES
    DEPENDING ON NUMBER OF CLUSTERS USED.

47
CLUSTER SAMPLING
  • FOR EXAMPLE.
  • FIRST STAGE CLUSTER COULD BE A RANDOM
    SELECTION OF CITY BLOCKS.
  • SECOND STAGE A RANDOM SELECTION OF
    HOUSEHOLDS FROM THOSE CITY BLOCKS.
  • THIRD STAGE A RANDOMLY SELECTED PERSON FROM
    EACH HOUSEHOLD.

48
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49
CLUSTER SAMPLING
  • AS A RULE, RANDOM SAMPLING ERROR WILL BE
    MINIMIZED, AND PRECISION OF STATISTICS
    MAXIMIZED, IF....
  • THE NUMBER OF CLUSTERS SAMPLES IS
    MAXIMIZED.
  • THE NUMBER OF ELEMENTS WITHIN EACH CLUSTER
    IS MINIMIZED.
  • UNFORTUNATELY, THIS STRATEGY ADDS TO THE
    COST OF CLUSTER SAMPLING.

50
CLUSTER SAMPLING
  • SAMPLING ERROR IS USUALLY HIGHEST IN
    CLUSTER SAMPLING COMPARED TO THE OTHER THREE
    PROBABILITY METHODS.
  • ERROR INCREASES AS THE NUMBER OF CLUSTERS
    DECREASE.
  • ERROR DECREASES AS THE HOMOGENEITY OF CASES
    WITHIN CLUSTERS INCREASES.

51
ONLINE PROBABILTY SAMPLING TECHNIQUES
  • SIMPLE, SYSTEMATIC, STRATIFIED, CLUSTER (FOR
    CLOSED POPULATIONS).
  • SATURATION (ONLINE CENSUS)
  • RANDOM ONLINE INTERCEPT SAMPLING
  • INVITATION ONLINE SAMPLING
  • ONLINE PANELS SAMPLING (PRE-RECRUITED)

52
ONLINE NONPROBABILTY SAMPLING TECHNIQUES
  • CONVENIENCE
  • VOLUNTEER
  • SNOWBALL OR REFERRAL
  • JUDGEMENT

53
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56
DEVELOPING THE SAMPLING PLAN
  • Define the Population
  • Define the Sampling Frame
  • Define the Sampling Method and Size
  • Draw the Sample
  • Validate the Sample
  • Resample if necessary.

57
SAMPLING DISTRIBUTIONS
  • ARE HYPOTHETICAL DISTRIBUTIONS OF A
    STATISTIC (E.G., THE MEAN) ACROSS ALL
    POSSIBLE RANDOM SAMPLES THAT COULD BE DRAWN
    FROM A POPULATION.
  • ANY SINGLE RANDOM SAMPLE CAN BE THOUGHT OF
    AS ONE OF AN INFINITE NUMBER OF RANDOM
    SAMPLES THAT THEORETICALLY COULD HAVE BEEN
    SELECTEDIF WE HAD THE MONEY OF BILL GATES
    AND THE PATIENCE OF JOB!

58
  • WHAT DOES A SAMPLING DISTRIBUTION LOOK
    LIKE?
  • CHECK OUT THE HANDOUT I GAVE YOU!
  • SAMPLING DISTRIBUTIONS FOR MOST STATISTICS
    ARE NORMAL OR BELL-SHAPED.
  • BECAUSE RANDOM SAMPLING ERROR PRODUCES THE
    BELL-SHAPE, WE CAN ESTIMATE SAMPLING ERROR
    STATISTICALLY!

59
DETERMINING SAMPLE SIZE
  • TIME AND MONEY CONSTRAINTS INFLUENCE SAMPLE
    SIZE.
  • THE LOWER YOUR SAMPLING ERROR MUST BE, THE
    LARGER YOUR SAMPLE MUST BE.
  • THE MORE DIVERSE YOUR POPULATION IS, THE
    LARGER YOUR SAMPLE MUST BE.
  • THE MORE COMPLEX YOUR ANALYSIS, THE LARGER
    YOUR SAMPLE MUST BE.
  • THE STRONGER YOUR EXPECTED RELATIONSHIPS,
    THE SMALLER YOUR SAMPLE CAN BE.

60
SAMPLE SIZERULES OF THUMB
  • LOCAL OR REGIONAL STUDIES.250 - 750.
  • PROVINCIAL OR NATIONAL STUDIES1000 - 2500.
  • NATIONAL STUDIES WITH MULTIPLE AND COMPLEX
    RESEARCH GOALS..10,000 - 15,000.
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