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17 Cards in this Set

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  • Back
Data
Collectionsofobservations,such as measurements, genders, or survey responses
Statistics
Thescience of planning studies and experiments, obtaining data, and thenorganizing, summarizing, presenting, analyzing, interpreting, and drawingconclusions based on the data
Population
Thecomplete collection of all measurements or data that arebeing considered
Census
Collectionof data from everymember of a population
Sample
Subcollectionof members selected from a population
Prepare - Context
vWhatdo the data mean? vWhatis the goal of the study?

Prepare - Source of the Data

* Isthe source objective?

* Isthe source biased?


* Bevigilant and skeptical of studies from sources that may be biased.

Prepare - Sampling Method
* Doesthe method chosen greatly influence the validity of the conclusion?

* Voluntaryresponse (or self-selected) samples often have bias (those with specialinterest are more likely to participate).


* Othermethods are more likely to produce good results.

Conclude – Statistical Significance
* Statisticalsignificance isachieved in a study when we get a result that is very unlikely to occur bychance.
PotentialPitfalls – Misleading Conclusions
* Concluding that one variable causes the other variable when in factthe variables are only correlated or associated together.

* Twovariables that may seemed linked, are smoking and pulse rate.


* Wecannot conclude the one causes the other. Correlationdoes not imply causality

PotentialPitfalls - Small Samples
Conclusions should not be based onsamples that are far too small.



Example: Basing a school suspension rate on a sample of only threestudents

PotentialPitfalls - Loaded Questions
If survey questions are not wordedcarefully, the results of a study can be misleading.
PotentialPitfalls - Order of Questions
Questions are unintentionally loaded bysuch factors as the order of the items being considered.
PotentialPitfalls - Nonresponse
Occurs when someone either refuses torespond to a survey question or is unavailable.
PotentialPitfalls - Missing Data
Can dramatically affect results.Subjects may drop out for reasonsunrelated to the study.Example- People with low incomes are less likely to report their incomes
PotentialPitfalls - Precise Numbers
Because as a figure is precise, manypeople incorrectly assume that it is also accurate.
PotentialPitfalls - Percentages
Misleadingor unclear percentages are sometimes used