In both examples, the null hypothesis states that there is no significant difference between the measure and the hypothesized value, while the alternative hypothesis states that there is a significant difference. 'The mean decrease in blood pressure for patients taking the new medication is not 10 mmHg' 'The mean decrease in blood pressure for patients taking the new medication is 10 mmHg' 'The mean weight of apples picked from the orchard is not equal to 6 ounces.'Ī drug manufacturer claims that their new medication will lower blood pressure by 10 mmHg on average.

The alternative hypothesis would then be: 'The mean weight of apples picked from a certain orchard is equal to 6 ounces.' Example 1:Īn example of a null hypothesis could be: The goal of hypothesis testing is to determine which of these hypotheses is more likely to be true based on a sample of data. The alternative hypothesis is the statement that there is a significant difference. In statistical hypothesis testing, a null hypothesis is a statement or assumption that there is no significant difference between a particular measure (such as a population mean) and a hypothesized value (such as a theoretical or experimental value). This process helps researchers to determine whether their findings are statistically significant or simply due to chance. Based on this likelihood, a decision is made to accept or reject the null hypothesis. It involves formulating a null hypothesis and an alternative hypothesis, and then using statistical methods to determine the likelihood of obtaining the observed sample results if the null hypothesis were true. Statistical hypothesis testing is a method used in statistics to make inferences about a population based on a sample.

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