Null Hypothesis: H0: There is no difference in the salary of factory workers based on gender.

3 weeks ago - Fisher's original (lady tasting tea) example was a one-tailed test. The null hypothesis was asymmetric. The probability of guessing all cups correctly was the same as guessing all cups incorrectly, but Fisher noted that only guessing correctly was compatible with the lady's claim.

January 24, 2025 - Although “fail to reject” may sound awkward, it’s the only wording that statisticians accept. Be careful not to say you “prove” or “accept” the null hypothesis. Example: Population on trialThink of a statistical test as being like a legal trial.

May 7, 2024 - In addition to the null hypothesis, the alternative hypothesis is also a staple in traditional significance tests. It's essentially the opposite of the null hypothesis because it assumes the claim in question is true. For the first item in the table above, for example, an alternative hypothesis might be "Age does have an effect on mathematical ability."

Test if the percentage of U.S. students who take advanced placement exams is more than 6.6%. State the null and alternative hypotheses. ... On a state driver’s test, about 40% pass the test on the first try. We want to test if more than 40% pass on the first try. Fill in the correct symbol (=, ≠, ≥, <, ≤, >) for the null and alternative hypotheses. H0: p __ 0.40 Ha: p __ 0.40 ... In a hypothesis test, sample data is evaluated in order to arrive at a decision about some type of claim.

May 8, 2025 - We can then compare the (calculated) sample mean to the (hypothesized) population mean of 7.0 and attempt to reject the null hypothesis. (The null hypothesis here—that the population mean is not 7.0—cannot be proved using the sample data. It can only be rejected.) Take another example: The annual return of a particular mutual fund is claimed to be 8%. Assume that the mutual fund has been in existence for 20 years.

March 10, 2021 - Here is how to write the null and alternative hypotheses for this scenario: H0: p ≥ .30 (the true proportion of citizens who support the law is greater than or equal to 30%) HA: μ < 0.30 (the true proportion of citizens who support the law is less than 30%) Introduction to Hypothesis Testing Introduction to Confidence Intervals An Explanation of P-Values and Statistical Significance

November 21, 2023 - For example, a null hypothesis statement can be “the rate of plant growth is not affected by sunlight.” It can be tested by measuring the growth of plants in the presence of sunlight and comparing this with the growth of plants in the absence ...

In that example, the null hypothesis is: the probability that a light bulb is defective does not decrease after introducing a new production method. Let's make the alternative hypothesis that the probability of being defective is 1% smaller after changing the production process (assume that a 1% decrease is considered a meaningful improvement by engineers).

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August 6, 2025 - The null hypothesis implies that any observed alterations in blood pressure subsequent to the medication's administration are a result of random fluctuations rather than a consequence of the medication itself. Conversely, the alternative hypothesis contends that the medication does indeed generate a meaningful alteration in blood pressure levels, distinct from what might naturally occur or by random chance. ... Example 1: A researcher claims that the average time students spend on homework is 2 hours per night.

November 7, 2022 - For these tests, the null hypothesis states that there is no difference between group proportions. Again, the experimental conditions did not affect the proportion of events in the groups. P is the population proportion parameter that you’ll need to include. For example, a vaccine experiment compares the infection rate in the treatment group to the control group.

This can happen, for example, when biological activity/presence in measured. That is, a protein might be "dormant" and the stimulus you are using can only possibly "wake it up" (i.e., it cannot possibly reduce the activity of a "dormant" protein). In addition, for some statistical tests, one-tailed tests are not possible. Let's return finally to the question of whether we reject or fail to reject the null hypothesis.

For example, if you were investigating the effect that short bursts of exercise have on heart rate, your null hypothesis would state ‘Short bursts of exercise will have no effect on heart rate’.

The null hypothesis (H0) is a statement of “no difference,” “no association,” or “no treatment effect.” ... The alternative hypothesis, Ha is a statement of “difference,” “association,” or “treatment effect.” · H0 is assumed to be true until proven otherwise. However, Ha is the hypothesis the researcher hopes to ... Take as an example a treatment that is said to be 25% effective.

July 31, 2023 - We reject the null hypothesis when the data provide strong enough evidence to conclude that it is likely incorrect. This often occurs when the p-value (probability of observing the data given the null hypothesis is true) is below a predetermined significance level.

The null hypothesis, or H0, represents the hypothesis of no change or no effect. In other words, the response being measured is unaffected by the experimental manipulation being tested. For example, if the effect of a proposed anti-cholesterol drug on blood pressure is being tested, then the null hypothesis could be that the drug treatment has no effect on the measured blood pressure:

Research Question: Does the data suggest that, on the average, people are able to lose more weight on a low carbohydrate diet than on a low fat diet? ... Null Hypothesis: There is no difference in the mean amount of weight loss when comparing a low carbohydrate diet with a low fat diet (population ...

June 10, 2025 - In marketing, you might test whether "changing the color of the 'Subscribe' button from red to green does not affect conversion rates." Here the null hypothesis assumes both colors have identical conversion rates. While educators could test "there is no difference in average test scores between students using the new teaching method versus the traditional method." These examples highlight why the null hypothesis framework is essential for data-driven decision-making.