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- 1Scientific PurposeTo provide evidence in favor of certain ideas that may not be always physically seen or obvious
-may clash with common sense - 2Scientific Method Steps1. Observations
2. Question
3. Hypothesis
4. Prediction
5. Test - 3Statistics with Scientific MethodModern scientific hypotheses or theories are probabilistic. This means they must be carried out in a statistical framework.
- 4Testable HypothesisExplains observed facts simply and withstands many falsifications.
- 5Untestable HypothesisA hypothesis that cannot be falsified.
Ex: The entire universe is a figment of my imagination. - 6Difference b/t Hypothesis, Theory, and LawHypothesis: Explanation based on evidence
Theory: A group of laws
Law: A well supported hypothesis - 7Data Analysis Purpose- To summarize findings
- To better understand or validate a theory
- To forecast a variable
- To evaluate performance of a variable
- To select a course of action - 8Descriptive StatisticsOrganization and summary of data.
- 9Inferential StatisticsGeneralization of results from a small sample to a larger population.
- Linked with probability theory - 10Statistical PopulationTotal set of elements under examination in a particular study
- Finite population
- Hypothetical population - 11Population characteristicAny measurable attribute of the population.
- 12SampleSubset of elements of population used to make inferences of the characteristics of the whole population.
- 13VariableA population characteristic that takes on different values for the elements that make up the population.
- 14ErrorOccurs if true population characteristics are not represented.
- Systematic error
- Random error - 15Archival Data or Secondary DataData already existing or available
- 16Internal DataExisting records or files from an institution
Ex: Weather station records - 17External DataData obtained outside the institution conducting the study
- 18Primary SourceObtained from original data collector
- 19Secondary SourceObtained from something other than the primary source.
- 20MetadataInformation about the data including processes used to create, check, and produce it.
- 21Metadata componentsData definitions
Method of Sampling
Data Quality
Data Legal Issues
Studies
Deospatial - 22Structural MatrixOne observational unit, multiple variables
- 23Interaction MatrixVariable expressed as a flow between locations.
- 24Qualitative DataNon Numerical Data
Non overlapping categories - 25Quantitative DataNumerical Values
- 26Continuous DataData that changed over time
- 27Discrete DataData that is a whole number
Ex: cannot have half of a student - 28Explicitly SpatialLocations of observations directly observed
- 29Implicitly SpatialData represents location but does not observe directly.
- 30Spatially Aggregated DataWhole data set is comprised of combined elements.
- 31Ecological FallacyFalse inference made about individuals based on what the group does.
- 32Nominal Scale- Qualitative variables with no ordering
- May contain arbitrary numerical values
- Information often summarized in a simple chart. - 33Individual LevelCollecting data personally for each individual.
- 34Ordinal ScaleQualitative variables WITH ordering
Numerical differences not meaningful
- Strongly ordered
- Weakly ordered - 35Interval ScaleMagnitude between two variables can be determined.
Ratio between two variables NOT possible.
Zero value NOT meaningful - 36Ratio ScaleQuantitative values
Zero NON arbitrary
Ex: Kelvin Scale; absolute zero - 37PrecisionLevel of exactness of a measurement
- 38AccuracyMeasurement bias from true value
Ex: hitting middle of dartboard. - 39ValidityAssesses whether variable measures the defined process properly
- 40ReliabilityAssessment of data quality
- 41Sturges' Rule1 + 3.3 log n
- 42Scott's Rule3.5(s)(n^-1/3)
- 43Equal Interval (Based on Range)Intervals equal width
Intervals based on the max and min - 44Equal Interval (NOT Based on Range)Classes interval selected arbitrarily
Equal intervals between classes - 45Quantile BreaksEqual number of observations in each class
Eliminates outliers - 46Natural BreaksUser defined number of classes
Single Linkage: Use highest break in data as class and so forth downward. - 47OgiveCumulative frequency graph
S curve
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- Beschreibung
- Karteikarten am Ohne Titel, erstellt von James Foster9258 am 28/01/2015.
- Erstellt von
- James Foster9258
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