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Null Hypothesis
Null Hypothesis
The null hypothesis is a statement that there is no difference or no relationship between two variables or groups. It is a statement of no effect or no difference, which is assumed to be true unless proven otherwise.
Symbolic Notation:
H0: p = 0
where:
- H0 is the null hypothesis
- p is the population parameter being tested
- 0 represents the hypothesized value of p (usually zero)
Types of Null Hypotheses:
- Directional: Specifies the direction of the expected effect (e.g., H0: ฮผ > 50).
- Non-directional: Does not specify the direction of the expected effect (e.g., H0: ฮผ = 50).
- Two-tailed: Tests for difference in either direction from the hypothesized value (e.g., H0: ฮผ = 50).
- One-tailed: Tests for difference in only one direction from the hypothesized value (e.g., H0: ฮผ > 50).
Examples:
- The average height of women is equal to 160 cm. (H0: ฮผ = 160)
- There is no relationship between exercise and blood pressure. (H0: ฯ = 0)
- The probability of winning a lottery is 0.05. (H0: p = 0.05)
Importance:
- Null hypotheses are essential for statistical testing.
- They provide a clear statement of the hypothesis to be tested.
- Null hypotheses are used to guide the selection of appropriate statistical tests.
- They help interpret the results of statistical tests and draw conclusions.
Note:
- Null hypotheses are not necessarily true. They are assumptions that need to be tested against evidence.
- If the null hypothesis is rejected, it does not necessarily mean that the alternative hypothesis is true.