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Phân tích Cronbach

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Internal consistency
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In statistics and research, internal consistency is a measure based on the
correlations between different items on the same test (or the same subscale on a
larger test). It measures whether several items that propose to measure the same
general construct produce similar scores. For example, if a respondent expressed
agreement with the statements "I like to ride bicycles" and "I've enjoyed riding
bicycles in the past", and disagreement with the statement "I hate bicycles", this
would be indicative of good internal consistency of the test.
Internal consistency is usually measured with Cronbach's alpha, a statistic calculated
from the pairwise correlations between items. Internal consistency ranges between
zero and one. A commonly-accepted rule of thumb is that an α of 0.6-0.7 indicates
acceptable reliability, and 0.8 or higher indicates good reliability. High reliabilities
(0.95 or higher) are not necessarily desirable, as this indicates that the items may be
entirely redundant. The goal in designing a reliable instrument is for scores on
similar items to be related (internally consistent), but for each to contribute some
unique information as well.
URL: 

Reliability (statistics)
From Wikipedia, the free encyclopedia
Jump to: navigation, search
In statistics, reliability is the consistency of a set of measurements or measuring
instrument, often used to describe a test. This can either be whether the
measurements of the same instrument give or are likely to give the same
measurement (test-retest), or in the case of more subjective instruments, such as
personality or trait inventories, whether two independent assessors give similar
scores (inter-rater reliability). Reliability is inversely related to random error.
Reliability does not imply validity. That is, a reliable measure is measuring something
consistently, but not necessarily what it is supposed to be measuring. For example,
while there are many reliable tests of specific abilities, not all of them would be valid
for predicting, say, job performance. In terms of accuracy and precision, reliability is
precision, while validity is accuracy.
In experimental sciences, reliability is the extent to which the measurements of a
test remain consistent over repeated tests of the same subject under identical
conditions. An experiment is reliable if it yields consistent results ...
Internal consistency
From Wikipedia, the free encyclopedia
Jump to: navigation, search
In statistics and research, internal consistency is a measure based on the
correlations between different items on the same test (or the same subscale on a
larger test). It measures whether several items that propose to measure the same
general construct produce similar scores. For example, if a respondent expressed
agreement with the statements "I like to ride bicycles" and "I've enjoyed riding
bicycles in the past", and disagreement with the statement "I hate bicycles", this
would be indicative of good internal consistency of the test.
Internal consistency is usually measured with Cronbach's alpha, a statistic calculated
from the pairwise correlations between items. Internal consistency ranges between
zero and one. A commonly-accepted rule of thumb is that an α of 0.6-0.7 indicates
acceptable reliability, and 0.8 or higher indicates good reliability. High reliabilities
(0.95 or higher) are not necessarily desirable, as this indicates that the items may be
entirely redundant. The goal in designing a reliable instrument is for scores on
similar items to be related (internally consistent), but for each to contribute some
unique information as well.
URL: http://en.wikipedia.org/wiki/Internal_consistency
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