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Title: Chapter%204:%20Gathering%20Data

Chapter 4Gathering Data
  • Section 4.1
  • Should We Experiment or Should We Merely Observe?

Learning Objectives
  1. Population versus Sample
  2. Types of Studies Experimental and Observational
  3. Comparing Experimental and Observational Studies

Learning Objective 1Population and Sample
  • Population all the subjects of interest
  • We use statistics to learn about the population,
    the entire group of interest
  • Sample subset of the population
  • Data is collected for the sample because we
    cannot typically measure all subjects in the

Learning Objective 2Type of Study
Observational Study
  • In an observational study, the researcher
    observes values of the response variable and
    explanatory variables for the sampled subjects,
    without anything being done to the subjects (such
    as imposing a treatment)

Learning Objective 2Observational Study
Sample Survey
  • A sample survey selects a sample of people from a
    population and interviews them to collect data.
  • A sample survey is a type of observational study.
  • A census is a survey that attempts to count the
    number of people in the population and to measure
    certain characteristics about them

Learning Objective 2Type of Study Experiment
  • A researcher conducts an experiment by assigning
    subjects to certain experimental conditions and
    then observing outcomes on the response variable
  • The experimental conditions, which correspond to
    assigned values of the explanatory variable, are
    called treatments

Learning Objective 2Example
  • Headline Student Drug Testing Not Effective in
    Reducing Drug Use
  • Facts about the study
  • 76,000 students nationwide
  • Schools selected for the study included schools
    that tested for drugs and schools that did not
    test for drugs
  • Each student filled out a questionnaire asking
    about his/her drug use

Learning Objective 2Example
  • Conclusion Drug use was similar in schools that
    tested for drugs and schools that did not test
    for drugs

Learning Objective 2Example
  • This study was an observational study.
  • In order for it to be an experiment, the
    researcher would had to have assigned each school
    to use or not use drug testing rather than
    leaving this decision to the school.

Experimental Design????
  • Observational Studies????
  • An observational study observes individuals and
    measures variables of interest but does not
    attempt to influence the responses.
  • Designed experiments????
  • An experiment deliberately imposes some treatment
    on individuals in order to observe their

Learning Objective 3Comparing Experiments and
Observational Studies
  • An experiment reduces the potential for lurking
    variables to affect the result. Thus, an
    experiment gives the researcher more control over
    outside influences.
  • Only an experiment can establish cause and
    effect. Observational studies can not.
  • Experiments are not always possible due to
    ethical reasons, time considerations and other

Example 3.2
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Do smaller classes benefit students?
  • ????????,????????????
  • ????????????,?????????
  • ????????
  • ???STAR program
  • 6385 ????regular class (22-25) with one
    teacher, regular class with a teacher and a
    full-time teachers aid, small class (13-17)

Where can we find observational data?
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  • Sampling??
  • GSS???????3000?
  • ????????2000?
  • Census??
  • ????
  • ????
  • ??????

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  • A sample may be more accurate than a
  • Accuracy and precision??????????????
  • Census of a large population increase the
    likelihood of nonsampling errors because of the
    increased volume of work. ???????????90??????????
  • EXgtBureau of the Census uses samples to check the
    accuracy of the U.S. Census.
  • Speed of response???????????
  • Cost
  • Destructive sampling ?????

  • ????????????????????,????????????(sampling

Chapter 4Gathering Data
  • Section 4.2
  • What are Good Ways and Poor Ways to Sample?

Learning Objectives
  1. Sampling Frame Sampling Design
  2. Simple Random Sample (SRS)
  3. Random number table
  4. Margin of Error
  5. Convenience Samples
  6. Types of Bias in Sample Surveys
  7. Key Parts of a Sample Survey

Learning Objective 1Sampling Frame Sampling
  • The sampling frame is the list of subjects in the
    population from which the sample is taken,
    ideally it lists the entire population of
  • The sampling design determines how the sample is
    selected. Ideally, it should give each subject
    an equal chance of being selected to be in the

Learning Objective 2Simple Random Sampling, SRS
  • Random Sampling is the best way of obtaining a
    sample that is representative of the population
  • A simple random sample of n subjects from a
    population is one in which each possible sample
    of that size has the same chance of being selected

Learning Objective 2SRS Example
  • Two club officers are to be chosen for a New
    Orleans trip
  • There are 5 officers President, Vice-President,
    Secretary, Treasurer and Activity Coordinator
  • The 10 possible samples are
  • (P,V) (P,S) (P,T) (P,A) (V,S)
  • (V,T) (V,A) (S,T) (S,A) (T,A)
  • For a SRS, each of the ten possible samples has
    an equal chance of being selected. Thus, each
    sample has a 1 in 10 chance of being selected and
    each officer has a 1 in 4 chance of being

Learning Objective 3SRS Table of Random Numbers
Table of Random Numbers
  • Table E on pg. A6 of text

Leaning Objective 3Using Random Numbers to
select a SRS
  • To select a simple random sample
  • Number the subjects in the sampling frame using
    numbers of the same length (number of digits)
  • Select numbers of that length from a table of
    random numbers or using a random number generator
  • Include in the sample those subjects having
    numbers equal to the random numbers selected

Learning Objective 3Choosing a simple random
  • We need to select a random sample of 5 from a
    class of 20 students.
  • List and number all members of the population,
    which is the class of 20.
  • The number 20 is two-digits long.
  • Parse the list of random digits into numbers that
    are two digits long. Here we chose to start with
    line 103, for no particular reason.

22 36 84 65 73 25 59 58 53 93 30 99 58 91 98 27
98 25 34 02
22 36 84 65 73 25 59 58 53 93 30 99 58 91 98 27
98 25 34 02
24 13 04 83 60 22 52 79 72 65 76 39 36 48 09 15
17 92 48 30
1 Alison 2 Amy 3 Brigitte 4 Darwin 5 Emily 6
Fernando 7 George 8 Harry 9 Henry 10 John 11
Kate 12 Max 13 Moe 14 Nancy 15 Ned 16 Paul 17
Ramon 18 Rupert 19 Tom 20 Victoria
  1. Choose a random sample of size 5 by reading
    through the list of two-digit random numbers,
    starting with line 2 and on.
  2. The first five random numbers matching numbers
    assigned to people make the SRS.

The first individual selected is Amy, number 02.
Thats it from line 2. Move to line 3 Then Moe
(13), Darwin, (04), Henry (09), and Net (15)
  • Remember that 1 is 01, 2 is 02, etc.
  • If you were to hit 09 again before getting five
    people, dont sample Ramon twiceyou just keep

Learning Objective 4Margin of Error
  • Sample surveys are commonly used to estimate
    population percentages
  • These estimates include a margin of error which
    tells us how well the sample estimate predicts
    the population percentage
  • When a SRS of n subjects is used, the margin of
    error is approximately

Learning Objective 4Example Margin of Error
  • A survey result states The margin of error is
    plus or minus 3 percentage points
  • This means It is very likely that the reported
    sample percentage is no more than 3 lower or 3
    higher than the population percentage

Sampling Design
Sample designs
  • Nonprobability samples
  • Voluntary Response Sample
  • Convenience
  • Judgment
  • Quota
  • Snowball
  • Probability samples
  • Simple random
  • Systematic
  • Stratified
  • Proportionate
  • Disproportionate
  • Cluster
  • Multistage

There are no appropriate statistical techniques
for measuring random sampling error from a
non-probability sample. Thus projecting the data
beyond the sample is statistical inappropriate.
Comparisons of sampling techniques
Learning Objective 5Convenience Samples Poor
Ways to Sample
  • Convenience Sample a type of survey sample that
    is easy to obtain
  • Unlikely to be representative of the population
  • Often severe biases result from such a sample
  • Results apply ONLY to the observed subjects

Convenience Sampling
  • ???? (haphazard or accidental sampling), relying
    on available subjects
  • EXgt man-on-the-street interviews, talk to friend
    about their political sentiment
  • EXgt professor uses students as sample
  • EXgt every tenth student entering the university
  • EXgt Survey over sea Chinese for international

Convenience Sampling
  • Advantages Very low cost, extensively used, No
    need for list of population.
  • It is justified only if the researcher wants to
    study the characteristics of people passing the
    sampling point at specified times or if less
    risky sampling methods are not feasible.

Convenience Sampling
  • Problems
  • (1) no way of knowing if those included are
  • (2) Variability and bias of estimates cannot be
    measured or controlled.
  • (3) Projecting the results beyond the specific
    sample is inappropriate.
  • Should be use only for exploratory design to
    generate ideas and insights.
  • you should alert readers to the risks associated
    with this method.

Learning Objective 5Convenience Samples Poor
Ways to Sample
  • Volunteer Sample most common form of
    convenience sample
  • Subjects volunteer for the sample
  • Volunteers do not tend to be representative of
    the entire population

  • ???call in??????????????????,?????????

Judgment Samples (Purposive Samples)????
  • hand-picked sample elements, believed to be
    representative of the population of interest
  • EXgt a fashion manufacturer regularly selects a
    sample of key accounts that it believes are
    capable of providing the information to predict
    what will sell in the fall.
  • EXgt Dow Jones industrial average select 30
    blue-chip stocks out of 1,800 stocks. Highly
    correlated with other NYSE indicators on the
    daily percentages of price changes
  • EXgtRepresentative communities in U.S.
    presidential election.
  • EXgt CPI????????

Snowball sample????
  • Locate an initial set of respondents. These
    individual are then used as informants to
    identify others with the desired characteristics.
  • Appropriate when the members of a special
    population are difficult to locate.

Snowball sample????
  • EXgt survey users of an unusual product a study
    among deaf for product that would allow deaf
    people to communicate over telephone.
  • EXgt ??????(????),homeless, gangsters, migrant
    workers, undocumented immigrants.
  • EXgt network study,????(HIV)
  • Bias a person who is known to someone has a
    higher probability of being similar to the first

Quota samples????
  • by selecting sample elements in such a way that
    the proportion of the sample elements possessing
    a certain characteristics is approximately the
    same as the proportion with the characteristics
    in the population.
  • Establishing a characteristics matrix What
    proportion of the target population is male and
    female? what proportions of each gender fall
    various age categories, educational level, ethnic
  • Once such a matrix has been created and a
    relative proportion assigned to each cell in the
    matrix, you collect data from people having all
    the characteristics of a given cell.
  • All the persons in a given cell are then assigned
    a weight appropriate to their portion of the
    total population.

Quota samples????
  • Problems
  • The sample could be far off with respect to other
    important characteristics.
  • The quota frame must be accurate, and it is often
    difficult to get up-to-date information for this

Quota samples????
  • Biases may exist in the selection of sample
    elements within a given cell. The interviewer has
    a quota to achieve. The actual choice of elements
    left to the discretion of the individual field
    worker. Interviewers are prone to follow certain

Quota samples????
  • those who are similar to the interviewers are
    more likely to be interviewed,
  • toward the accessible (first floor, airline
    terminals, business district, college campus),
  • toward household with children, exclude working
  • against workers in manufacturing (service and
  • against extreme of income (EXgt "mansions" were
    skipped because the interviewer did not feel
    comfortable knocking on doors that were answered
    by servants. ),
  • against the less educated, against low-status

Learning Objective 6Types of Bias in Sample
  • Bias Tendency to systematically favor certain
    parts of the population over others
  • Sampling Bias bias resulting from the sampling
    method such as using nonrandom samples or having
  • Nonresponse bias occurs when some sampled
    subjects cannot be reached or refuse to
    participate or fail to answer some questions
  • Response bias occurs when the subject gives an
    incorrect response or the question is misleading
  • A Large Sample Does Not Guarantee An Unbiased

Error in survey research
Systematic (nonsampling) error
Random sampling error
Respondent error
Administrative error
Data processing error
Response bias
Nonresponse error
Sample selection error
Deliberate falsification Unconscious
Self-selection bias
Interviewer cheating
Interviewer error
Acquiescence bias
Extremity bias
Interviewer bias
Auspices bias
Social desirability bias
Contamination by others
Learning Objective 7Key Parts of a Sample Survey
  • Identify the population of all subjects of
  • Construct a sampling frame which attempts to list
    all subjects in the population
  • Use a random sampling design to select n subjects
    from the sampling frame
  • Be cautious of sampling bias due to nonrandom
  • We can make inferences about the population of
    interest when sample surveys that use random
    sampling are employed.

Chapter 4Gathering Data
  • Section 4.3
  • What Are Good Ways and Poor Ways to Experiment?

Learning Objectives
  1. Identify the elements of an experiment
  2. Experiments
  3. 3 Components of a good experiment
  4. Blinding the Study
  5. Define Statistical Significance
  6. Generalizing Results of the Study

Experimental Design????
  • A Designed Experiment
  • Folic Acid (??) and Birth Defects
  • Folic Acid (??) ???????????????????,??????????????

Experimental Design????
  • ?????????,?4753?????????????????0.8mg????????,????
  • ???13/1000
  • ????23/1000

Principles of Experimental Design
  • Treatment group ????????
  • Control group ???(???)????????
  • Experimental units subjects ???,?????
  • Response variable ????(????)???????????,????????
  • Factor ????????????????????,???????
  • Level ?? ?????????,?0.8mg ?0mg

Learning Objective 1Elements of an Experiment
  • Experimental units the subjects of an
    experiment the entities that we measure in an
  • Treatment A specific experimental condition
    imposed on the subjects of the study the
    treatments correspond to assigned values of the
    explanatory variable
  • Explanatory variable Defines the groups to be
    compared with respect to values on the response
  • Response variable The outcome measured on the
    subjects to reveal the effect of the

Learning Objective 2Experiments
  • An experiment deliberately imposes treatments on
    the experimental units in order to observe their
  • The goal of an experiment is to compare the
    effect ofthe treatment on the response.
  • Experiments that are randomized occur when the
    subjects are randomly assigned to the treatments
    randomization helps to eliminate the effects of
    lurking variables

Learning Objective 33 Components of a Good
  • Control/Comparison group allows the researcher
    to analyze the effectiveness of the primary
  • Randomization eliminates possible researcher
    bias, balances the comparison groups on known as
    well as on lurking variables
  • Replication allows us to attribute observed
    effects to the treatments rather than ordinary

Learning Objective 3Principle 1 Control or
Comparison Group
  • A placebo is a dummy treatment, i.e. sugar pill.
    Many subjects respond favorable to any treatment,
    even a placebo.
  • A control group typically receives a placebo. A
    control group allows us the analyze the
    effectiveness of the primary treatment.
  • A control group need not receive a placebo.
    Clinical trials often compare a new treatment for
    a medical condition, not with a placebo, but with
    a treatment that is already on the market.

Learning Objective 3Principle 1 Control or
Comparison Group
  • Experiments should compare treatments rather than
    attempt to assess the effect of a single
    treatment in isolation
  • Is the treatment group better, worse, or no
    different than the control group?
  • Example 400 volunteers are asked to quit
    smoking and each start taking an antidepressant.
    In 1 year, how many have relapsed? Without a
    control group (individuals who are not on the
    antidepressant), it is not possible to gauge the
    effectiveness of the antidepressant.

Learning Objective 3Placebo effect
  • Placebo effect (power of suggestion) The placebo
    effect is an improvement in health due not to
    any treatment but only to the patients belief
    that he or she will improve.

Learning Objective 3Principle 2 Randomization
  • To have confidence in our results we should
    randomly assign subjects to the treatments. In
    doing so, we
  • Eliminate bias that may result from the
    researcher assigning the subjects
  • Balance the groups on variables known to affect
    the response
  • Balance the groups on lurking variables that may
    be unknown to the researcher

Learning Objective 3Principle 3 Replication
  • Replication is the process of assigning several
    experimental units to each treatment
  • The difference due to ordinary variation is
    smaller with larger samples
  • We have more confidence that the sample results
    reflect a true difference due to treatments when
    the sample size is large
  • Since it is always possible that the observed
    effects were due to chance alone, replicating the
    experiment also builds confidence in our

Learning Objective 4Blinding the Experiment
  • Ideally, subjects are unaware, or blind, to the
    treatment they are receiving
  • If an experiment is conducted in such a way that
    neither the subjects nor the investigators
    working with them know which treatment each
    subject is receiving, then the experiment is
  • A double-blinded experiment controls response
    bias from the respondent and experimenter

  • ???? (double blindness)
  • ????????????????? (treatment)
  • ??????(?????)????
  • ????????? (hidden bias)
  • ????????????????????

Learning Objective 5Define Statistical
  • If an experiment (or other study) finds a
    difference in two (or more) groups, is this
    difference really important?
  • If the observed difference is larger than what
    would be expected just by chance, then it is
    labeled statistically significant.
  • Rather than relying solely on the label of
    statistical significance, also look at the actual
    results to determine if they are practically

Learning Objective 6Generalizing Results
  • Recall that the goal of experimentation is to
    analyze the association between the treatment and
    the response for the population, not just the
  • However, care should be taken to generalize the
    results of a study only to the population that is
    represented by the study.

Stanley Milgram ???????
  • ?????????????????????????????????????????????
  • ??????,??????????????,????????
  • ?????????????????????????????????????????????????

Milgram ???????
  • ???????????????????,??????,??????,???????,????????
  • ?????????????,??????????
  • ??????????,?????????????

Milgram ???????
  • ????15V,?15-450V,??????????????XXX??
  • ????????45V???,???????????,??15V?????,???????
  • ?????????,??????,???????????????????

Milgram ???????
Milgram ???????
  • ??????????450V(MAX)?
  • ?????????? 1 ?
  • ???????360V,Ultimately 65 of all of the
    "teachers" punished the "learners" to the maximum
    450 volts. No subject stopped before reaching 300

  • ????????????????????
  • 40????,????50V

??(?)?obedience ???to authority ?
  • ???????????????,??????????,??????,????????????????
  • ????????(???)??????????
  • 65MAX--gt 20

  • ????,?????,?????????(??)?????????????

  • ?150V?,???????????????????
  • ?210V?,???????????
  • ????10?????MAX
  • ??????????????,????????????????

  • ???????,??????????????????
  • ??-- ??????????
  • ??? -- ?????
  • ????????
  • 50 MAX , average 305 V
  • ?????????
  • ???????????????

  • ??Milgram???
  • Experimental units subjects???
  • Response variable ????????
  • Factor ?????
  • Level ???
  • Control ???

Chapter 4Gathering Data
  • Section 4.4
  • What are Other Ways to Conduct Experimental and
    Observational Studies

Learning Objectives
  • Sample Surveys Other Random Sampling Designs
  • Types of Observational Studies Prospective and
  • Multifactor Experiment
  • Matched pairs design
  • Randomized block design

Learning Objective 1Sample Surveys Random
Sampling Designs
  • It is not always possible to conduct an
    experiment so it is necessary to have well
    designed, informative studies that are not
    experimental, e.g., sample surveys that use
  • Simple Random Sampling
  • Cluster Sampling
  • Stratified Random Sampling

Learning Objective 1Sample Surveys Cluster
Random Sample
  • Cluster Random Sample
  • Steps
  • Divide the population into a large number of
    clusters, such as city blocks
  • Select a simple random sample of the clusters
  • Use the subjects in those clusters as the sample

Learning Objective 1Sample Surveys Cluster
Random Sample
  • Cluster Random Sample
  • Preferable when
  • A reliable sampling frame is unavailable
  • The cost of selecting a SRS is excessive
  • Disadvantage
  • Usually need a larger sample size than with a SRS
    in order to achieve a particular margin of error

Learning Objective 1Sample Surveys Stratified
Random Sample
  • Stratified Random Sample
  • Steps
  • Divide the population into separate groups,
    called strata
  • Select a simple random sample from each strata
  • Combine the samples from all strata to form
    complete sample

Learning Objective 1Sample Surveys Stratified
Random Sample
  • Stratified Random Sample
  • Advantage is that you can include in your sample
    enough subjects in each stratum you want to
  • Disadvantage is that you must have a sampling
    frame and know the stratum into which each
    subject belongs

Learning Objective 1Stratified Random Sample -
  • Suppose a university has the following student
  • Undergraduate Graduate First Professional
  • 55 20
    5 20

In order to insure proper coverage of each
demographic, a stratified random sample of 100
students could be chosen as follows select a
SRS of 55 undergraduates, a SRS of 20 graduates,
a SRS of 5 first professional students, and a SRS
of 20 special students combine these 100
Learning Objective 1Comparing Random Sampling
Learning Objective 2Types of Observational
  • An observational study can yield useful
    information when an experiment is not practical.
  • Types of observational studies
  • Sample Survey attempts to take a cross section
    of a population at the current time
  • Retrospective study looks into the past
  • Prospective study follows its subjects into the
  • Causation can never be definitively established
    with an observational study, but well designed
    studies can provide supporting evidence for the
    researchers beliefs

Learning Objective 2Retrospective Case-Control
  • A case-control study is a retrospective
    observational study in which subjects who have a
    response outcome of interest (the cases) and
    subjects who have the other response outcome (the
    controls) are compared on an explanatory variable

Learning Objective 2Example Case-Control Study
  • Response outcome of interest Lung cancer
  • The cases have lung cancer
  • The controls did not have lung cancer
  • The two groups were compared on the explanatory
    variable smoker/nonsmoker

Learning Objective 2Example Prospective Study
  • Nurses Health Study
  • Began in 1976 with 121,700 female nurses aged 30
    to 55 questionnaires are filled out every two
  • Purpose was to explore the relationships among
    diet, hormonal factors, smoking habits and
    exercise habits and the risk of coronary heart
    disease, pulmonary disease and stroke
  • Nurses are followed into the future to determine
    whether they eventually develop an outcome such
    as lung cancer and whether certain explanatory
    variables are associated with it

Learning Objective 3Multifactor Experiments
  • A Multifactor experiment uses a single experiment
    to analyze the effects of two or more explanatory
    variables on the response
  • Categorical explanatory variables in an
    experiment are often called factors
  • We are often able to learn more from a
    multifactor experiment than from separate
    one-factor experiments since the response may
    vary for different factor combinations

Learning Objective 3Example Multifactor
  • Examine the effectiveness of both Zyban and
    nicotine patches on quitting smoking
  • Two factor experiment
  • 4 treatments

Learning Objective 3Example Multifactor
  • subjects a certain number of undergraduate
  • all subjects viewed a 40-minute television
    program that included ads for a digital camera
  • some subjects saw a 30-second commercial others
    saw a 90-second version
  • same commercial was shown either 1, 3, or 5 times
    during the program
  • there were two factors length of the commercial
    (2 values), and number of repetitions (3 values)

Learning Objective 3Example Multifactor
  • the 6 combinations of one value of each factor
    form six treatments

Factor B Repetitions Factor B Repetitions Factor B Repetitions
1 time 3 times 5 times
Factor A Length 30 seconds 1 2 3
Factor A Length 90 seconds 4 5 6
  • after viewing, all subjects answered questions
    about recall of the ad, their attitude toward
    the commercial, and their intention to purchase
    the product these were the response variables.

Learning Objective 4Matched Pairs Design
  • In a matched pairs design, the subjects receiving
    the two treatments are somehow matched (same
    person, husband/wife, two plots in the same
    field, etc.)
  • In a crossover design, the same individual is
    used for the two treatments
  • Randomly
  • assign the two treatments to the two matched
    subjects, or
  • randomize the order of applying the treatments in
    a crossover design
  • The number of replicates equals the number of
  • Helps to reduce effects of lurking variables

Learning Objective 5Randomized Block Design
  • A block is a set of experimental units that are
    matched with respect to one or more
  • A Randomized Block Design, RBD, is when the
    random assignment of experimental units to
    treatments is carried out separately within each

Learning Objective 5Example Randomized Block
  • Block gender 3 treatments 3 types of
  • The men (as well as the women) are randomly
    assigned to the
  • 3 treatments differences can be compared with
    respect to
  • gender as well as therapy type

Learning Objective 5Randomized Block Design
  • RBD eliminates variability in the response due to
    the blocking variable allows for better
    comparisons to be made among the treatments of
  • A matched pairs design is a special case of a RBD
    with two observations in each block

Statistical Designs
  • Completely Randomized Design All the
    experimental units are assigned randomly among
    all the treatments.
  • Randomized Block Design the experimental units
    are assigned randomly among all the treatments
    separately within each block. blocks are
    another form of control.

Completely Randomized Design
Randomized Block Design
Page 28, Figure 1.5
Completely Randomized Design
Page 28, Figure 1.6
Randomized Block Design
O1 O2??,?X?,??????????O2
  • O1 X1 O2
  • History -- Specific events in the external
    environment occurring between the first and
    second measurements that are beyond the control
    of the experimenter and that affect the validity
    of an experiment.
  • EX) Changes (departmental reorganization, a
    strike or large layoff, change in the economic
    climate) during the course of an OB field
  • EX) Cohort effect --a change in the dependent
    variable because members of one experimental
    condition experienced historical situations
    different from those of members of other
    experimental conditions.

  • O1 ? O2
  • An effect on the results of a research experiment
    caused by changes in the experimental subjects
    over time.
  • ??????????? -- Fatigue, bored, sleepy, ageetc.
  • EXgt ?????????????????? ??????

Pretesting and Postesting
Experimental Group
Control Group
Measure dependent variable
Compare same?
Measure dependent variable
  • Differences noted between the first and last
    measurements on the dependent variable are then
    attributed to the independent variable.

Administer experimental stimulus
Remeasure dependent variable
Compare Different?
Remeasure dependent variable
  • The effect of pretesting in a before-and-after
    study may sensitize the subjects when taking a
    test for the second time, thus affecting the
    validity of an experiment.
  • EX) students taking achievement and intelligence
    tests for the second time.
  • Pretesting may increase awareness of socially
    approved answers, it may increase attention to
    experimental conditions, or it may make the
    subject more conscious of the dimensions of a
  • EXgt drug intervention , attitude changes

Pretesting and Postesting
  • the subjects might respond differently to the
    questionnaires the second time even if their
    attitudes remained unchanged.
  • The very act of studying something may change it.

  • An effect on the results of an experiment caused
    by a change in the wording of questions, a change
    in interviewers, or other changes in procedures
    to measure the dependent variable.
  • Problem of reliability
  • EXgt ???????????????(????????)

Selection bias????
  • Inappropriate randomization--A sample bias
    resulting in differential selection of
    respondents for the comparison groups.
  • ????????????
  • EX). ?????????? ,????

Experimental mortality????
  • Sample attrition that occurs when some subjects
    withdraw from an experiment before it is
    completed, thus affecting the validity of the
  • ????????? Problem of drop-out
  • EXgt drug-intervention, who drop out from the
  • EXgt a short film teach people how to reduce their
    attitudes toward homosexual.
  • EXgt???????????????????

Diffusion or imitation of treatment????"??"
  • Without exposure to the treatment, control group
    were accidentally "contaminated". Experimental
    group might diffuse the information to the
    control group???????
  • EXgt?????????

Compensation???? Compensatory rivalry???? Demorali
  • EXgt???????????
  • EXgt??????????
  • EXgt??????????

Time Series Experiment-the observation windows
Positive impact -- raised the firms market share
Market Share
Positive impact -- it halted a decline in market
No long-run impact
No impact -- the market share growth remained
No impact -- fluctuation after X was introduced.
O1 O2 O3 O4 O5 O6 O7 O8 Time
  • The impact of a package change, X, on the firms
    market share.