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T distribution

When we use T distribution?

When we know, population is normal distribution and what we have is only sample.

What is the question to which T distribution answers?

Given a small sample out of population with an assumed/declared
population mean, what is the cumulative probability that another trail that I conduct by taking same sample size of previous sample trail, results in same as earlier sample mean?

Example: I say my population mean is 10 defective bulbs out of 1000.
Let us conduct a test on 30 random samples. Let us say trail shows 12
defective bulbs out of 30 sample size. If I do What is the probability that in next trial we can again have 12 defective bulbs?



--
HP

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ORE-OBIEE Integration

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1. I have ORE in 12c pdb configured with a user, say RUSER2 with RQROLE and RQADMIN roles.
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3. Table PRED_TBL is created with height, weight and ID columns.
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#olm is a ORE script which returns predicted table.
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raw<-dat
library(ORE)
lmdl<-lm(WEIGHT~.,raw)
lpred<-predict(lmdl,raw)
pred_tbl<-cbind(raw,lpred)
pred_tbl
}');
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#Creating view which calls olm script with PRED_TBL as input
create or replace view R_PREDICT as
select HEIGHT, WEIGHT, ID,LPRED from table( rqTableEval(
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