Hypothesis

-Hareesh M2014600120

What is Hypothesis…?

• Hypothesis is considered as the principal instrument in research.

• Its main function is to suggest new experiments and observations

Definition: • A hypothesis is a conjectural statement of the relation

between two or more variables. (Kerlinger, 1956)• Hypothesis is a formal statement that presents the

expected relationship between an independent and dependent variable.(Creswell, 1994)

Hypothesis

• Hypothesis needs to be structured before the data-gathering and interpretation phase of the research

• The hypothesis gives direction to the collection and interpretation of data

Characteristics of hypothesis

• Hypothesis should be clear and precise.• Hypothesis should be capable of being tested• Hypothesis should be limited in scope and must

be specific• Hypothesis should state relationship between

variables• Hypothesis should be consistent with most

known facts, amenable to testing within a reasonable time

Null and Alternative Hypothesis

• The Null hypothesis (H0) is a claim of “no Significance difference between 2 variables”

• The Alternative hypothesis (Ha) claims “H0 is false”. Opp to Null Hypothesis

Type-1 and type-2 errors

Type I error:•Rejection of a true null hypothesis is called the type I error.•Type error I occurs when we reject a hypothesis that should be

accepted.

Type II error:•Acceptance of false null hypothesis is called the type II error.•Type error II occurs when we accept a hypothesis that should be rejected.

Confidence interval• It is expressed as a percentage and represents

how often the true percentage of the population who would pick an answer lies within the confidence interval.

• The 95% confidence level means you can be 95% certain;

• the 99% confidence level means you can be 99% certain.

• Most researchers use the 95% confidence level.

Level of Confidence

• A confidence level refers to the percentage of all possible samples that can be expected to include the true population parameter. For example, suppose all possible samples were selected from the same population, and a confidence interval were computed for each sample. A 95% confidence level implies that 95% of the confidence intervals would include the true population parameter.

Hypothesis testing of means

Mean of the population can be tested presumingdifferent situations such as the population may beNormal or other than normal, its sample size may be large

or small, variance of the population may be known or unknown and the alternative hypothesis may be two-sided or one sided. our testing technique will differ in different situations.

We may consider some of the importantSituations.

Hypothesis testing of means

Hypothesis testing of means

Hypothesis testing for differences between means

The null hypothesis for testing of difference between means is generally stated as H0 : m1 = m2 ,

• where m1 is population mean of one population and m2 is population mean of the second population, assuming both the populations to be normal populations.

• Alternative hypothesis may be of not equal to or less than or greater than type as stated earlier and accordingly we shall determine the acceptance or rejection regions for testing the hypotheses.

• There may be different situations when we are examining the significance of difference between two means, but the following may be taken as the usual situations:

Hypothesis testing for differences between means

Hypothesis testing for differences between means

Hypothesis testing for differences between means

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