PERBANDINGAN UJI T STATISTIK RATA-RATA TERBOBOT DENGAN RATA-RATA TIDAK TERBOBOT PADA DATA KEUANGAN: (Studi Kasus Yield Obligasi Muncipal dan Korporasi Amerika Serikat dengan Rating AAA
Means is technic to explanation the group or size in center set of data. Usually, a common statistical question arises when two random samples are taken from two different normal populations, possibly with different variances, and wish to know whether or not the means of the two populations are equa...
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| Main Authors: | , |
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| Format: | Theses and Dissertations NonPeerReviewed |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/131972/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=72486 |
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| Summary: | Means is technic to explanation the group or size in center set of data.
Usually, a common statistical question arises when two random samples are taken
from two different normal populations, possibly with different variances, and wish
to know whether or not the means of the two populations are equal. To examine
the similarity of the average, typically use t-test mean two samples. In this
minithesis will describe about expansion of t-test mean two samples using tstatistic
weighted means.
This methode present a generalization of the two-sample t-test for equality
of the means to the case where the sample values are to be given unequal weights.
This is a natural situation in financial return modelling where some samples are
considered more reliable than others in predicting a common mean. In this case
show with an example of yield data that using the standard unweighted t-test can
lead to the wrong statistical conclusion. |
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