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Hypothesis Testing

Hypothesis refers means an educated guess or an assumption that can be tested.

Forms of hypothesis:
1.       HA- Research hypothesis
2.       HO- Null hypothesis

HA: Research hypothesis:

The research hypothesis is also known as an alternate hypothesis. HA is a statement on which a statistical hypothesis test is set up.

HO- Null hypothesis:

Null hypothesis is also known as no difference or no relationship, this is used to facilitate testing of research hypothesis

Types of hypothesis:

·         One-tailed- Directional
HA: p>0
HO: p<0

·         Two-tailed- non-directional

HA: p not equal to zero




Types of Error:

Type 1 Error – Rejection of a true Null hypothesis.
Type 2 Error – It may have a false negative finding.

Type 1 error is donated by Alpha.
Level of significant can reduce the type 1 error.

For most of the hypothesis analysis, level of significance value is considered to 95%. If the level of significance is taken as 0.01, means there are fewer chances and we can strongly say about the null hypothesis statement we have assumed.

Type 2 Error is donated by Beta.

More is the sample size, less are the chances of Type 2 Error.

Power calculated to take a correct decision in rejecting the NULL hypothesis
Effective size is to calculate the one variable effect on the other variable

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