RS1 Unitt 2

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Alternative Hypothesis

what the researcher suspect or hope to be true about the parameter of interest and can take on three forms. the form is determined by the research question.

Anecdotal Evidence

results from situations that come to mind easily and is of little value in scientific research

Bias

tendency of samples to differ from the corresponding population as a result of systematic exclusion of part of the population

Blind

when the subjects are not aware which treatment they receive BUT the people ADMINISTERING treatments do know

Blocking

a technique in experimental design that filters out the effects of some extraneous factors; creates groups that are similar with respect to a factor; for example: gender, age, grade level

Cause and Effect conclusions

based on experiments where it is established that the explanatory variable is the most likely cause of the response variable.

Comparison

the process used to determine whether there is a statistically significant difference between two or more groups

Confounding Variable

a variable that may differ among the explanatory variable groups in such a way that we cannot distinguish their effects from those of the explanatory variable; they may prevent us from drawing a cause and effect conclusion between the explanatory and the response variable

Constant

a value that remains unchanged

Control

holding extraneous factors constant so that their effects do not confound experimental design conditions

Convenience Sample

samples that are easily accessible

Double Blind

when neither the person evaluating the subjects nor the subjects are aware of which treatment they actually receive

Experiment

a study in which the experimenter actively imposes the treatment on the subjects

Explanatory Variable

the variables whose effect you want to study

Factor

Each independent variable that we assume to influence the dependent variable of interest

Intervention

The treatment that is being tested, i.e imposed on the experimental group

Level (of a factor)

The logical categories or intensities of factors or treatments

Non-response

Members of the population did not have the OPPORTUNITY to respond

Null Hypothesis

states that the parameter of interest is equal to a specific value

Observational Study

When the investigator PASSIVELY observes and records information on observational units

Parameter

a number that describes a population

Placebo

a treatment with no active ingredient or benefit (such as a sugar pill)

Placebo Effect

Subjects often respond positively simply by being given a treatment

Population

The entire group of people or objects (observational unit) of interest

Precision (of a sample statistic)

How much the value varies from sample to sample

Prospective Study

A study that starts with a group and watches for outcomes (like the development of cancer or remaining cancer free) during the study period and relates this to suspected risk or protective factors that might be linked to the outcomes

Random Assignment

It creates treatment groups that are similar in all respects except for the treatment imposed so that lurking and potentially confounding variables tend to balance out between the two groups

Replication

using enough experimental units so any difference can be attributed to the treatment instead of chance differences in experimental units

Representative Sample

a sample that has similar characteristics to the population so that you can learn useful information

Response Variable

the variable that you can suspect is affected by the other variable; often considered to be the outcome of interest

Retrospective Study

A study that starts with an outcome and then looks back to examine exposures to suspected risk or protected factors that might be linked to that outcome

Sample

part of the population from which or which data are gathered to learn about the population as a whole

Sampling Bias

Systematic tendency of a sampling method to over represent some parts of the population

Sampling Frame

An actual list of every member of the population that we want to sample from

Sampling Variability

The tendency of values of a sample statistic to vary from sample to sample

Simple Random Sampling (SRS)

When every possible sample of size n has an equal chance of being the sample ultimately selected

Statistic

A number that describes a sample

SRS

Simple Random Sampling

Statistically Significant

When the difference in values of the response variable between two groups is so large that such an extreme difference would rarely occur by random assignment alone

Treatment

the explanatory variable

Trial

the single performance of an experiment

Unbiased Statistic

This occurs if values of the statistic from different random samples are centered at the actual parameter value

Voluntary Response

Samples collected in such a way that members of the population decide for themselves whether or not to participate in the study

Data

the information collected

Quantitative Variable

measures a numerical characteristic

Categorical Variable (Qualitative)

records a group designation

Binary variable

a catagorical variable with only two possible catagories (yes or no, left or right)

Homogeneous population

A population that is uniform

Under-coverage

When some parts of your populations are not adequately represented from your sample

Question Wording

A survey questions that is written so poorly as to confuse or mislead respondents to answer one way or the other

Lurking Variable

a variable that is not among the explanatory or response variables in a study but that may influence the response variable

Treat lurking variables as a _

Noun. they are anything that could affect the response in yours experiment, even of they do not directly impact the experiment, but is part of the experimental environment.

Treat confounding variables as a _

Verb. Variables confound other variables.

If your sampling method is biased and you take larger samples you will _ reduce the bias and you will produce a more __ estimate that is still not close to the population value

Not;Precise

Random Sampling eliminates _

Bias

Random Assignment eliminates _

confounding variables

One sample

collecting a single piece of information from each observational unit. ONE group

Two sample

collecting a single piece of information from each observational unit, bit splitting them into TWO groups.

Matched Pairs

Creating blocks by matching pairs or similar experimental units. One subject in the pair gets one treatment and the other subject in the pair gets the other one. It helps reduce variation among experimental units.

Can a matched pair be just one experimental unit?

Yes! It means that one experimental unit gets both treatments one after the other. It serves as its own control. However you must randomize the order for random assignment

ARE WE FAILING?????

No! if we use the power of quizlet we will defeat Ms. Nelson