Difference between revisions of "AP Statistics Curriculum 2007 IntroVar"

From SOCR
Jump to: navigation, search
(Model Validation)
(The Nature of Data & Variation)
Line 2: Line 2:
  
 
==The Nature of Data & Variation==
 
==The Nature of Data & Variation==
No mater how controlled the environment, the protocol or the design, virtually any repeated measurement, observation, experiment, trial, study or survey is bound to generate data that varies because of intrinsic (internal to the system) or extrinsic (due to the ambient environment) effects.
+
No matter how controlled the environment, the protocol or the design, virtually any repeated measurement, observation, experiment, trial, study or survey is bound to generate data that varies because of intrinsic (internal to the system) or extrinsic (due to the ambient environment) effects.
  
 
For example, the UCLA's [[AP_Statistics_Curriculum_2007_IntroVar#References | study of Alzheimer’s disease*]] analyzed the data of 31 MCI and 34 probable Alzheimer’s disease patients. The investigators made every attempt to control as many variables as possible, yet, the demographic information they collected from the outcomes of the subjects contained unavoidable variation. The same study found variation in the MMSE cognitive scores even in the same subjects.
 
For example, the UCLA's [[AP_Statistics_Curriculum_2007_IntroVar#References | study of Alzheimer’s disease*]] analyzed the data of 31 MCI and 34 probable Alzheimer’s disease patients. The investigators made every attempt to control as many variables as possible, yet, the demographic information they collected from the outcomes of the subjects contained unavoidable variation. The same study found variation in the MMSE cognitive scores even in the same subjects.

Revision as of 17:06, 1 March 2008

General Advance-Placement (AP) Statistics Curriculum - Introduction to Statistics

The Nature of Data & Variation

No matter how controlled the environment, the protocol or the design, virtually any repeated measurement, observation, experiment, trial, study or survey is bound to generate data that varies because of intrinsic (internal to the system) or extrinsic (due to the ambient environment) effects.

For example, the UCLA's study of Alzheimer’s disease* analyzed the data of 31 MCI and 34 probable Alzheimer’s disease patients. The investigators made every attempt to control as many variables as possible, yet, the demographic information they collected from the outcomes of the subjects contained unavoidable variation. The same study found variation in the MMSE cognitive scores even in the same subjects.

AP Statistics Curriculum 2007 IntroVar Dinov 061407 Fig1.png

Approach

Models & strategies for solving the problem and understanding the data and inference.

  • Once we accept that all natural phenomena are inherently variant and there are no completely deterministic processes, we need to look for models and techniques that allow us to study such acquired data in the presence of variation, uncertainty and chance.
  • Statistics is the data science that investigates natural processes and allows us to quantify variation to make population inference based on limited observations.

Model Validation

Checking/affirming underlying assumptions.

  • Each model or technique for data exploration, analysis and understanding relies on a set of assumptions, which always need to be validated before the model or analysis tool is employed to study real data (observations or measurements that are perceived or detected by the investigator).
  • Such prior model conjectures or presumptions could take the form of mathematical constraints about the properties of the underlying process, restrictions on the study design or demands on the data acquisition protocol.
  • Common assumptions include (statistical) independence of the measurements, specific limitations on the shape of the observed distribution, restrictions on the parameters of the processes being studied , etc.

Computational Resources: Internet-based SOCR Tools

Examples

Computer simulations and real observed data.

Hands-on activities

Step-by-step practice problems.


References




Translate this page:

(default)
Uk flag.gif

Deutsch
De flag.gif

Español
Es flag.gif

Français
Fr flag.gif

Italiano
It flag.gif

Português
Pt flag.gif

日本語
Jp flag.gif

България
Bg flag.gif

الامارات العربية المتحدة
Ae flag.gif

Suomi
Fi flag.gif

इस भाषा में
In flag.gif

Norge
No flag.png

한국어
Kr flag.gif

中文
Cn flag.gif

繁体中文
Cn flag.gif

Русский
Ru flag.gif

Nederlands
Nl flag.gif

Ελληνικά
Gr flag.gif

Hrvatska
Hr flag.gif

Česká republika
Cz flag.gif

Danmark
Dk flag.gif

Polska
Pl flag.png

România
Ro flag.png

Sverige
Se flag.gif