The Difference between Null Hypothesis and Alternative Hypothesis
When conducting a hypothesis test, it is essential to understand the difference between the null hypothesis and the alternative hypothesis. Hypothesis testing is a statistical method used to confirm or reject an assumption about a population parameter. It involves setting up a null hypothesis and an alternative hypothesis to be tested. This article will explore the difference between null hypothesis and alternative hypothesis, and why it is crucial to understand them for successful hypothesis testing.
What is a Null Hypothesis?
A null hypothesis is a statement that suggests that there is no significant difference between two sample populations or variables being measured. It is assumed to be true, and the researcher is trying to disprove this statement through statistical analysis. The null hypothesis tends to be the default hypothesis, and it is typically denoted as H0, with the ‘H’ standing for hypothesis, and the ‘0’ indicating that it is the null hypothesis.
For instance, imagine a study that aims to compare the weight of apples picked in two different orchards. The null hypothesis would state that there’s no significant difference in weight between the apples picked from Orchard A and Orchard B.
What is an Alternative Hypothesis?
An alternative hypothesis is a statement that suggests that there is a significant difference between two sample populations or variables being measured. It’s a claim that opposes the null hypothesis and is the alternate assumption. If the null hypothesis is rejected, then the alternative hypothesis is typically accepted. It is often denoted as Ha, with the ‘a’ indicating alternative.
For the apple study, the alternative hypothesis could be that the apples picked from Orchard A are heavier than those picked from Orchard B.
The Difference Between Null Hypothesis and Alternative Hypothesis
The difference between the null hypothesis and the alternative hypothesis lies in the statement that they make regarding the sample populations or variables under consideration. The null hypothesis assumes that there is no significant difference between the two samples, while the alternative hypothesis assumes that there is a significant difference between the two samples.
In statistical analysis, the researcher collects data to determine whether the null hypothesis can be rejected or not. If the data doesn’t contradict the null hypothesis, then it is supported. Otherwise, if the data significantly opposes the null hypothesis, it is rejected. If the null hypothesis is rejected, then the alternative hypothesis is accepted.
In conclusion, understanding the difference between the null hypothesis and alternative hypothesis is crucial to the successful application of hypothesis testing. The null hypothesis assumes that there is no significant difference between the two sample populations, while the alternative hypothesis assumes that there is. A researcher is expected to carry out statistical analysis to either support or reject the null hypothesis. By understanding the difference between these two hypotheses, a researcher can choose the right statistical test and effectively interpret the results obtained.
Table difference between null hypothesis and alternative hypothesis
Here is an example HTML table that compares the null hypothesis and alternative hypothesis:
| Null Hypothesis | Alternative Hypothesis |
|---|---|
| The null hypothesis is a statement that suggests there is no significant difference between two groups or variables. | The alternative hypothesis is a statement that suggests there is a significant difference between two groups or variables. |
| It represents the status quo or the default assumption. | It represents the research question or the competing assumption. |
| It is tested by calculating the probability (p-value) of observing a result as extreme as the one observed if the null hypothesis were true. | It is supported by rejecting the null hypothesis and accepting the alternative hypothesis based on the p-value and the level of significance (alpha) chosen. |
| It is denoted as H0 or Ho. | It is denoted as Ha or H1. |