Alternative Hypothesis-Definition, Types and Examples
A hypothesis is a working assertion based on scant data. As a result, there arises a requirement for additional testing. A statistical hypothesis test is a technique for determining if the available data are sufficient to support a given hypothesis. Hypothesis testing can be used to make probabilistic claims about the characteristics of the population. There are two types of hypotheses:
This Story also Contains
- Alternative hypothesis
- Types of alternative hypothesis
- Null hypothesis
- Differences and similarities between null and alternative hypothesis
- Examples
Null hypothesis
Alternative hypothesis
Alternative hypothesis
The alternative hypothesis is a hypothesis under which a statistically significant association exists between two variables. It is denoted by Ha or H1. It is also called the research hypothesis. The alternative hypothesis is typically a claim that a researcher believes to be true and that rejects the null hypothesis. An alternative hypothesis is complementary to the null hypothesis and thus, only one of them can be true at a time. Suppose, your null hypothesis is ‘Harry will get more than 20 marks in the test’ then the alternative hypothesis will be ‘Harry will get less than or equal to 20 marks in the test’.
Types of alternative hypothesis
There are three types of alternative hypotheses:
Left-tailed: In this type of hypothesis, the sample proportion (ᴨ) is less than a specific value (ᴨ0).
Ha : ᴨ < ᴨ0
Right-tailed: In this type of hypothesis the sample proportion (ᴨ) is greater than a specific value (ᴨ0).
Ha : ᴨ > ᴨ0
Two-tailed: In this type of hypothesis the sample proportion (ᴨ) is not equal to a specific value (ᴨ0).
Ha: ᴨ ≠ ᴨ0
Null hypothesis
A null hypothesis is a hypothesis in which there is no statistically significant relationship between two variables. It is denoted by the symbol H0. Researchers try to reject the null hypothesis and always write the null hypothesis in terms of ‘no effect’, ‘no difference’, or ‘no relation’. One should never prove or accept the null hypothesis.
Differences and similarities between null and alternative hypothesis
Differences between null and alternate hypothesis:
NULL HYPOTHESIS | ALTERNATIVE HYPOTHESIS |
It states there is no statistical relationship between two variables. | It states there is a statistically important relationship between two variables. |
A claim that effects on the population don’t exist. | A claim that there is an effect on the population. |
The researcher tries to reject this hypothesis. | The researcher assumes this hypothesis to be true. |
It is denoted by H0. | It is denoted by Ha. |
Similarities between null and alternative hypotheses:
They are both solutions to research problems.
Statistical tests are used to examine them.
Examples
We want to determine if the mean salary of employees in an office is different from $75,000. The null and alternative hypotheses are:
H0: ᴨ = $75,000
Ha: ᴨ ≠ $75,000
Let us take a decision in a court as a statistical hypothesis test. The null hypothesis is that the defendant is assumed to be innocent while the alternative hypothesis states that the defendant is guilty. The defendant is innocent until proven guilty likewise it is presumed that the null hypothesis is true in a hypothesis test until proven otherwise. There must be sufficient evidence to prove the alternative hypothesis true that is to prove the defendant guilty.
Only legitimate evidence may be used in a court as the basis for a trial. To determine the statistical significance of the null hypothesis in hypothesis testing, an acceptable test statistic should be used. If the null hypothesis is proven wrong at a particular level of significance, evidence would back up the alternative hypothesis.
Frequently Asked Questions (FAQs)
The alternative hypothesis is assumed to be true by the researcher.
Alternative hypothesis is denoted by Ha or H1.
Alternative hypothesis is also called the research hypothesis.
The null hypothesis states that there’s no relationship between variables while the alternative hypothesis states that there’s a statistically important relation between variables. The researcher tries to reject the null hypothesis while the alternative hypothesis is assumed to be true.
Null hypothesis and alternative hypothesis are the two types of hypothesis.