[PDF] Null Hypothesis Testing: Problems, Prevalence, and an Alternative | Semantic Scholar (2025)

FAQs

What is an example of a null hypothesis and an alternative hypothesis? ›

Examples: Null Hypothesis: H₀: There is no difference in the salary of factory workers based on gender. Alternative Hypothesis: H_a: Male factory workers have a higher salary than female factory workers. Null Hypothesis: H₀: There is no relationship between height and shoe size.

A null hypothesis is a statistical hypothesis in which there is no significant difference exist between the. set of variables. It is the original or default statement, with no effect, often represented by H0 (H-zero).

The statement being tested in a test of statistical significance is called the null hypothesis. The test of significance is designed to assess the strength of the evidence against the null hypothesis, or a statement of 'no effect' or 'no difference'. It is often symbolized as H₀.

The null hypothesis is often stated as the assumption that there is no change, no difference between two groups, or no relationship between two variables. The alternative hypothesis, on the other hand, is the statement that there is a change, difference, or relationship.

The null hypothesis is the statement or claim being made (which we are trying to disprove) and the alternative hypothesis is the hypothesis that we are trying to prove and which is accepted if we have sufficient evidence to reject the null hypothesis.

The null statement must always contain some form of equality (=, ≤ or ≥) Always write the alternative hypothesis, typically denoted with H _a or H ₁, using less than, greater than, or not equals symbols, i.e., (≠, >, or <).

The null hypothesis assumes that any kind of difference between the chosen characteristics that you see in a set of data is due to chance. For example, if the expected earnings for the gambling game are truly equal to zero, then any difference between the average earnings in the data and zero is due to chance.

The conclusion is made up of two parts: 1) Reject or fail to reject the null hypothesis, and 2) there is or is not enough evidence to support the alternative claim. Option 1) Reject the null hypothesis (H0). This means that you have enough statistical evidence to support the alternative claim (H1).

A null hypothesis is a hypothesis that says there is no statistical significance between the two variables. It is usually the hypothesis a researcher or experimenter will try to disprove or discredit. An alternative hypothesis is one that states there is a statistically significant relationship between two variables.

What is the null hypothesis in a nutshell? ›

The null hypothesis states that there's no statistical significance in the observed effect, while the alternative hypothesis states that there's a significant effect. 2. Choose the significance level (alpha): Usually set at 0.05, this represents the probability of rejecting the null hypothesis when it's true. 3.

A study is statistically significant if the P value is less than the pre-specified alpha. Stated succinctly: A P value less than a predetermined alpha is considered a statistically significant result. A P value greater than or equal to alpha is not a statistically significant result.

The significance of distributions within parts of a large-area prevalence study can be evaluated by an adaptation of the chi-square contingency test: χ² = Σ (O-E) 2 E where O = observed number of cases in each part , E = the expected number of cases in the same part .

For a representative sample, prevalence is the number of people in the sample with the characteristic of interest, divided by the total number of people in the sample.

The number of cases of a disease, number of infected people, or number of people with some other attribute present during a particular interval of time. It is often expressed as a rate (for example, the prevalence of diabetes per 1,000 people during a year).

For example, perhaps you are interested in comparing the mean body size of two species of lizards, an anole and a gecko. Our null hypothesis would be that the two species do not differ in body size. The alternative, which one can conclude by rejecting that null hypothesis, is that one species is larger than the other.

If it uses words such as “less, decreased, smaller and so on”, apply “<” for H1. If words such as “the same, change, different/difference and so on” appear in the claim, use “≠” for H1. The opposite symbol will be used for H0. (Note: For MATH 1257, always use “=” for H0.)

A simple hypothesis suggests only the relationship between two variables: one independent and one dependent. Examples: If you stay up late, then you feel tired the next day. Turning off your phone makes it charge faster.

For example, let's say you think that a certain drug might be responsible for a spate of recent heart attacks. The drug company thinks the drug is safe. The null hypothesis is always the accepted hypothesis; in this example, the drug is on the market, people are using it, and it's generally accepted to be safe.