Ch 10-12 (U1) Collecting Data & Experiments: Key Terms

prospective/observational study

subjects are followed to observe future outcomes.

bc no treatments are deliberately applied, a prospective study is not an experiment.

experiment

manipulates factor levels to crate treatments, randomly assigns subjects to these treatment levels, and then compares the responses of the subject groups across treatment levels.

random assignment

an experiment must assign experimental units to treatment groups at random

factor

a variable whose levels are manipulated by the experimenter. experiments attempt to discover the effects that differences in factor levels may have on the responses of the experimental units. 

response

a variable whose values are compared across different treatments.

in a randomized experiments, large response differences can be attributed to the effect of differences in treatment level.

experimental units

individuals on whom an experiment is performed. (usually called subjects or participants when they are human.)

level

the specific values that the experimenter chooses for a factor.

treatment

the process, intervention, or other controlled circumstance applied to randomly assigned experimental units. they are the different levels of a single factor or are made up of combinations of levels of two or more factors.

4 principles of experimental design

control, randomize, replicate, block

control

the process of managing or regulating variables in an experiment to isolate the effects of specific factors.

randomize

______ subjects to treatments to even out effects that we cannot control.

replicate

______ over as many subjects as possible.

if the subjects of the experiment are not a representative sample from the population of interest, replicate the entire study with a different group of subjects, preferably from a different part of the population.

block

a group of similar experimental units that share a characteristic that could affect the outcome of the experiment.

completely randomized design

all experimental units have an equal chance of receiving any treatment

statistically significant

when an observed difference is too large for us to believe that it is likely to have occurred naturally

control group

the experimental units assigned to a baseline treatment level, typically either the default treatment, which is well understood, or a null, placebo treatment. their responses provide a basis for comparison. 

blinding

any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups.

single-blind

a research design where the study participants are unaware of their assigned treatment group, but the researchers or experimenters administering the study are aware of the allocation.

double-blind

a research technique where neither the study participants nor the researchers administering the treatment know who is receiving the actual intervention and who is receiving a placebo or control treatment.

placebo

a treatment known to have no effects administered to one group so that all groups experience the same conditions.

placebo effect

the tendency of many human subjects to show a response even when administered a placebo.

blocking

when groups of experimental units are similar, it is often a good idea to gather them together into blocks. we isolate the variability attributable to the difference between the blocks so that we can see the differences caused by the treatments more clearly.

randomized block design

the subjects are randomly assigned to treatments only within blocks.

matching

subjects who are similar in ways not under study may be matched and then compared with each other on the variables of interest. reduces unwanted variation.

confounding

when the levels of one factor are associated with the levels of another factor in such a way that their effects cannot be separated.

population

the entire group of individuals or instances about whom we hope to learn

sample

a (representative) subset of a population, examined in hope of learning about the population.

sample survey

a study that asks questions of a sample drawn from some population in hopes of learning something about the entire population.

ex: polls taken to assess voter preferences

bias

any systematic failure of a sampling method to represent its population

• relying on voluntary response

• undercoverage of the population

• nonresponse bias

• response bias

randomization

the best defense against bias. each individual is given a fair, random chance of selection.

sample size

the number of individuals in a sample. determines how well the sample represents the population, not the fraction of the population sampled.

census

a sample that consists of the entire population.

population parameter

a numerically valued attribute of a model for a population.

we rarely expect to know the true value, but we do hope to estimate it from sampled data.

ex: the mean income of all employed people in the country

statistic

values calculated for sampled data.

simple random sample (SRS)

a sample in which each set of n elements in the population has an equal chance of selection.

sampling frame

a list of individuals from whom the sample is drawn.

sampling variability

the natural tendency of randomly drawn samples to differ, one from another.

stratified random sample

a sampling design in which the population is divided into several subpopulations, or strata, and random samples are then drawn from each stratum.

if the strata are homogeneous, but are different from each other, this type of sampling design may yield more consistent results than an SRS.

cluster sample

a sampling design in which entire groups, or clusters, are chosen at random. 

usually selected as a matter of convenience, practicality, or cost. 

clusters are heterogeneous, and a random sample of clusters should be representative of the population.

multistage sample

sampling schemes that combine several sampling methods.

ex: a national polling service may stratify the country by geographical regions, select a random sample of cities from each region, and then interview a cluster of residents in each city.

systematic sample

a sample drawn by selecting individuals systematically from a sampling frame.

ex: selecting every 20th customer from a store's sales list to survey, or choosing every 5th student from a school roster to participate in a study

pilot study

a small trial run of a survey to check whether questions are clear. it can reduce errors due to ambiguous questions.

voluntary response bias 

bias introduced to a sample when individuals can choose their on own whether to participate in the sample.

these samples are always invalid and cannot be recovered, no matter how large the sample size.

convenience sample

consists of the individuals who are conveniently available.

they often fail to be representative because every individual in the population is not equally convenient to sample.

undercoverage

a sampling scheme that biases the sample in a way that gives a part of the population less representation.

nonresponse bias

bias introduced when a large fraction of those sampled fails to response. those who do respond are likely to not represent the entire population.

ex: those who are at work during the day won’t respond to a telephone survey conducted only during working hours.

response bias

the tendency of respondents to provide inaccurate or misleading answers in surveys or research studies. (wording of questions)

ex: voters are more likely to express support of “the president” than support of the particular person holding that office at the moment 

data

a single, specific item of information or a single measurement, whereas statistics are numbers or summaries derived from analyzing a collection of data to reveal patterns or trends

categorical variable

a type of variable that assigns observations to distinct groups or categories based on a qualitative characteristic, rather than a numerical quantity.

ex: hair color, gender

quantitative variable

a type of numerical variable whose values represent amounts or quantities that can be measured or counted.

ex: height, weight, age, or the number of goals scored

random

an outcome is _____ if we know the possible values it can have, but not which particular value it takes.

simulation

a ______ models a real-world situation by using random-digit outcomes to mimic the uncertainty of a response variable of interest.

simulation component

a ____ ____ uses equally likely random digits to model simple random occurrences whose outcomes may not be equally likely. 

trial

the sequence of several components representing events that we are pretending will take place.

response variable

values of the ____ ____ record the results of each trial with respect to what we were interested in.

1. it is representative of the whole population

2. it reduces variation

what are the two advantages of stratifying?

strata

distinct, non-overlapping subgroups within a larger population that share common characteristics, such as age, gender, or location.

causation

what can be concluded ONLY through an experiment?

randomly assigning treatment(s)

what makes an experiment and experiment?

1. components

2. outcome

3. trial

4. response

5. assigning #s

what are the 5 parts of an experiment?