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Permalink Reply by Anandraj K C on February 23, 2010 at 3:28

A null hypothesis is a statistical hypothesis that is tested for possible rejection under the assumption that it is true (usually that observations are the result of chance).

type of hypothesis used in statistics that proposes that no statistical significance exists in a set of given observations. The null hypothesis attempts to show that no variation exists between variables, or that a single variable is no different than zero. It is presumed to be true until statistical evidence nullifies it for an alternative hypothesis.

It should be stressed that researchers very frequently put forward a null hypothesis in the hope that they can discredit it. For a second example, consider an educational researcher who designed a new way to teach a particular concept in science, and wanted to test experimentally whether this new method worked better than the existing method. The researcher would design an experiment comparing the two methods. Since the null hypothesis would be that there is no difference between the two methods, the researcher would be hoping to reject the null hypothesis and conclude that the method he or she developed is the better of the two.

The symbol H0 is used to indicate the null hypothesis. For the example just given, the null hypothesis would be designated by the following symbols:

H0: µ1 - µ2 = 0

or by

H0: μ1 = μ2.

The null hypothesis is typically a hypothesis of no difference as in this example where it is the hypothesis of no difference between population means. That is why the word "null" in "null hypothesis" is used -- it is the hypothesis of no difference

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Permalink Reply by Anandraj K C on February 23, 2010 at 3:54

A (general) hypothesis is a statement about the relationship between two or more variables. The stated rela-tionship must be testable; i.e., there must be, at least in principal, some way of checking the hypothesis gainst reality to determine whether the hypothesis is true (scil., appears consistent with reality) or is false

A statistical hypothes s is either (1) a statement about the value of a population parameter or (2) a statement bout the probability distribution that a random variable obeys.
You have just been appointed Head of Technical Services in a large academic library in a state university.
In appointing you, the library's director stressed the general expectation that, in its next session, the state's legislature
was likely to go crazy with the excitement of making budget cuts--rational or not. Therefore, she told you, you must
be constantly on the lookout for any and all possible ways of reducing expenses without affecting your library's
services to its users.
You decide that one of the first things you need to do is to establish some benchline data for what your current op-
erations are costing you. One of the more costly services your library provides is its OPAC, i.e., its Online Public
Access Catalog. Among the benchline data that you would like are data on the numbers of OPAC users and the fre-
quency of uses of (i.e., queries of or accesses to) the OPAC.
The operating system on the mainframe computer that supports your OPAC is capable of reporting the number of
current users of the OPAC (i.e., the number of persons currently logged into the OPAC) at any particular time that
you ask the system for that datum. How could you use this system capability to provide you with an idea of the
typical number of simultaneous OPAC users?
The essence of the problem is that you need to determine the mean number of users logged in at any one time.
A pertinent technique is that of constructing confidence intervals for the mean of a population. (Alterna-
tively, you could use the t-test procedure to test the null hypothesis that the population mean has a certain
value, i.e., a hypothesis of the form H 0 :µ = µ 0 , for some arbitrary value of µ 0 . In this case, the null hy-
pothesis states that the mean number of simultaneous OPAC users has some specified value.)
To construct a confidence interval for the population mean, you would take a random sample of the numbers
of OPAC users at various times during the OPAC's hours of operation. Using the observed sample mean
1
number of users, x , the observed sample standard deviation in the number of users, s, and the sample size, n,
you would construct the confidence interval for whatever level of confidence you wished to use, e.g., 95% or99

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Permalink Reply by Jashvant Patel on February 23, 2010 at 12:45

For all about Null hypothesis you may refer the following links which can help you to clear your concepts

http://www.null-hypothesis.co.uk/science//item/what_is_a_null_hypot...
http://en.wikipedia.org/wiki/Null_hypothesis
www.null-hypothesis.co.uk/.../what_is_a_null_hypothesis

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Permalink Reply by Ratnesh Kumar Sharma on February 24, 2010 at 18:49

Null Hypothesis: Null means Zero. The null hypothesis is a statistical preposition which states, essentially that, there is no relation between the variable (of the problem). When a hypothesis is stated negatively, then it is called as a null hypothesis. A null hypothesis is used to collect additional support for the known hypothesis. The null hypothesis says, “You are wrong, there is no relation, disprove me if you can”. The objective of the null hypothesis is to avoid personal bias of the investigator in the matter of data collection.

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Permalink Reply by Keerti Purwar on May 7, 2012 at 20:20

thank u

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