HYPOTHESIS A hypothesis is an idea or explanation that you then test through study and experimentation. Outside of science, theory or guess can also be called a hypothesis. A hypothesis is something more than a wild guess but less than a well-established theory. . . . Types 1)one-tailed 2)Two-tailed . . One-tailed test alludes to the significance test in which the region of rejection appears on one end of the sampling distribution. It represents that the estimated test parameter is greater or less than the critical value. When the sample tested falls in the region of rejection, i.e. either left or right side, as the case may be, it leads to the acceptance of the alternative hypothesis rather than the null hypothesis. .. . . examples...

3. Sampling of attributes

4. HYPOTHESIS
Hypothesis is an idea or explanation
that you then test through study and
experimentation. Outside science, a theory or
guess can also be called a hypothesis.
A hypothesis is something more than a wild
guess but less than a well-established theory.

5. Testing of HYPOTHESIS
It deals with the verification of validity of
presumptions regarding the parameters
of the population using samples drawn
from population.

6. Types
1)one tailed
2)Two tailed

7. Definition of One-tailed Test
One-tailed test alludes to the significance test
in which the region of rejection appears on
one end of the sampling distribution. It
represents that the estimated test parameter
is greater or less than the critical value. When
the sample tested falls in the region of
rejection, i.e. either left or right side, as the
case may be, it leads to the acceptance of
alternative hypothesis rather than the null
hypothesis.

8. • In this statistical hypothesis test, all the critical
region, related to α, is placed in any one of the
two tails. One-tailed test can be:
• Left-tailed test: When the population
parameter is believed to be lower than the
assumed one, the hypothesis test carried out
is the left-tailed test.
• Right-tailed test: When the population
parameter is supposed to be greater than the
assumed one, the statistical test conducted is
a right-tailed test.

10. Definition of Two-tailed Test
The two-tailed test is described as a
hypothesis test, in which the critical area is on
both the ends. It determines whether the
sample tested falls within or outside a certain
range of values. Therefore, an alternative
hypothesis is accepted in place of the null
hypothesis, if the calculated value falls in
either of the two tails of the probability
distribution.

11. In this test, α is bi-furcated into two
equal parts, placing half on each side, i.e.
it considers the possibility of both
positive and negative effects. It is
performed to see, whether the estimated
parameter is either above or below the
assumed parameter, so the extreme
values, work as evidence against the null
hypothesis.

13. ERROR
• Type1 error
• Type2 error

14. Actual fact Decision based on the
samples
Decision Error
1 Ho is true Accept Ho Correct decision ----
2 Ho is true Reject Ho wrong decision Type 1
3 Ho is not true Accept Ho wrong decision Type 2
4 Ho is not true Reject Ho Correct decision ----

15. Type 1
Error of the first kind is taking a wrong
decision to reject the null hypothesis
when it is actually true.
Type I error is a false positive

16. Type 2
Error of the second kind is taking a wrong
decision to accept the null hypothesis
when it is actually not true.
Type II error is a false negative.