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The stronger the evidence is against the null hypothesis, the higher the divergence from it.
What do you mean by null hypothesis ?
A statistical hypothesis known as a null hypothesis asserts that no statistical significance can be found in a collection of provided observations. Using sample data, hypothesis testing is performed to judge a theory' veracity. It is sometimes referred to as just "the null," and its symbol is . To determine if a theory regarding markets, investing methods, or economies is correct or wrong, quantitative analysts employ the null hypothesis,
The null hypothesis states that the percentage of the population who works full time is 0.45.
As a result, 450 persons who are randomly selected from a population of 1000 work full-time.
A different hypothesis states that the ratio is higher than 0.45.
In the options provided, the proportion for the first option is 300/1000, or 0.3.
In the second choice, 500/1000 equals 0.5
Third alternative: 700/1000 = 0.7
Therefore, the stronger the evidence is against the null hypothesis, the higher the divergence from it.
To learn more about the null hypothesis from the given link.
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