Definition Hypothesis test - What is a hypothesis test and how do we relate it to work

A

Andy_80

#1
Hello,
My name is Anand and working for a BPO as a quality analyst. I'm getting trained on six sigma Green belt.
I would like to know what is hypothesis test and how do we relate it to work. I'm confused by the examples the tutor is giving......like !..the common justice one!. Please help
 
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Jim Wynne

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#2
Andy_80 said:
Hello,
My name is Anand and working for a BPO as a quality analyst. I'm getting trained on six sigma Green belt.
I would like to know what is hypothesis test and how do we relate it to work. I'm confused by the examples the tutor is giving......like !..the common justice one!. Please help
Have a look at Hypothesis Testing, which gives a good overview except for the author's conflation of the terms "theory" and "hypothesis," which are not synonymous in this context. (In science, proven hypotheses might result in theories.)
 

Miner

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#3
Andy_80 said:
Hello,
My name is Anand and working for a BPO as a quality analyst. I'm getting trained on six sigma Green belt.
I would like to know what is hypothesis test and how do we relate it to work. I'm confused by the examples the tutor is giving......like !..the common justice one!. Please help
A hypothesis test is a simple test to compare two samples and make a determination whether the samples come from the same parent population.

No two samples will have the exact same mean and standard deviation, so it is important to determine whether the samples are the same or different, especially if you need to assess the impact of a change.

The test uses the difference between the two means and the size of the standard deviation as well as the sample sizes to determine the probability that the difference between the two is zero.

The greater the difference in mean, the smaller the standard deviation and the greater the sample size decrease the probability that the difference in means is zero.

One caution: Extremely large sample sizes will tend to show statistical significance that is of no practical value. When designing such a test, you should decide in advance how big a difference in means is of practical importance. Using this information and the process standard deviation will allow you to calculate the appropriate sample size to use.
 

Marc

Hunkered Down for the Duration with a Mask on...
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#4
Extra Information:

A hypothesis (= assumption in ancient Greek) is a proposed explanation for a phenomenon.

1. a proposal intended to explain certain facts or observations
2. a tentative theory about the natural world; a concept that is not yet verified but that if true would explain certain facts or phenomena; "a scientific hypothesis that survives experimental testing becomes a scientific theory"; "he proposed a fresh theory of alkalis that later was accepted in chemical practices"
3. guess: a message expressing an opinion based on incomplete evidence

From JSW05's link:

Hypothesis Test

Setting up and testing hypotheses is an essential part of statistical inference. In order to formulate such a test, usually some theory has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved, for example, claiming that a new drug is better than the current drug for treatment of the same symptoms.

*********************

In each problem considered, the question of interest is simplified into two competing claims / hypotheses between which we have a choice; the null hypothesis, denoted H0, against the alternative hypothesis, denoted H1. These two competing claims / hypotheses are not however treated on an equal basis, special consideration is given to the null hypothesis. We have two common situations:

1. The experiment has been carried out in an attempt to disprove or reject a particular hypothesis, the null hypothesis, thus we give that one priority so it cannot be rejected unless the evidence against it is sufficiently strong. For example, H0: there is no difference in taste between coke and diet coke against H1: there is a difference.

2. If one of the two hypotheses is 'simpler' we give it priority so that a more 'complicated' theory is not adopted unless there is sufficient evidence against the simpler one. For example, it is 'simpler' to claim that there is no difference in flavour between coke and diet coke than it is to say that there is a difference.

The hypotheses are often statements about population parameters like expected value and variance, for example H0 might be that the expected value of the height of ten year old boys in the Scottish population is not different from that of ten year old girls? A hypothesis might also be a statement about the distributional form of a characteristic of interest, for example that the height of ten year old boys is normally distributed within the Scottish population?

The outcome of a hypothesis test test is 'reject H0' or 'do not reject H0'.
 
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