null hypothesis statistics

null hypothesis symbol

null vs alternative hypothesis

hypothesis in research

hypothesis-testing

nebular hypothesis

Making a certain class or laboratory experiment would require a good null hypothesis. You will be given variables to be used in your experiment and then you would be able to identify the relationship between the two. Every beginning of the experiment report would indicate your hypotheses. It is proven useful for it can be tested to prove if the result is considered false.

A null hypothesis is used during experiments to prove that there is no difference in the relationship between the two variables. Every type of experiment would require you to make a null hypothesis. From the word itself “null” means zero or no value. If you want to practice making a good experiment report, consider providing a good null hypothesis. Null hypothesis is designed to be rejected if the alternative hypothesis is proven to be exact.

You have to start by generating a question. For example, “do teens use online shopping applications more than adults?” You may state your hypothesis like this: “the age of a person does not tell you of the effects of online shopping.”

The hypothesis can usually be found in the given problem itself. In writing a null hypothesis, you have to indicate what might happen possibly if the hypothesis doesn’t come out in a way you expected. How about if you do not have any idea of what will going to happen? You are going to indicate what could possibly happen if the experiment will not make any difference. This is already the process of what we refer to as a null hypothesis where you expect that nothing will eventually happen. Then, you are going to provide for an alternative hypothesis. An alternative hypothesis will be the one stating that something is really going to happen. It is the complete opposite of the null hypothesis.

Consider the examples of null hypothesis below:

*The annual return of ABC Limited bonds is assumed to be 7.5%. To test if the scenario is true or false, we take the null hypothesis to be “the mean annual return for ABC limited bond is not 7.5%.” To test the hypothesis, we first accept the null hypothesis. Any information that is against the stated null hypothesis is taken to be the alternative hypothesis for the purpose of testing the hypotheses. In such a case, the alternative hypothesis is “the mean annual return of ABC Limited is 7.5%.” We take samples of the annual returns of the bond for the last five years to calculate the sample mean for the previous five years. The result is then compared to the assumed annual return average of 7.5% to test the null hypothesis. The average of the annual returns for the five years is 7.5%; the null hypothesis is rejected. Consequently, the alternative hypothesis is accepted.*

*“Hyperactivity is unrelated to eating sugar” is an example of a null hypothesis. If the hypothesis is tested and found to be false, using statistics, then a connection between hyperactivity and sugar ingestion may be indicated. A significance test is the most common statistical test used to establish confidence in a null hypothesis. Another example of a null hypothesis is “Plant growth rate is unaffected by the presence of cadmium in the soil.” A researcher could test the hypothesis by measuring the growth rate of plants grown in a medium lacking cadmium, compared with the growth rate of plants grown in mediums containing different amounts of cadmium. Disproving the null hypothesis would set the groundwork for further research into the effects of different concentrations of the element in soil.*

Null hypothesis is meant to be rejected when an alternative hypothesis is proven true.

You reject the null hypothesis to favor the alternative hypothesis. This is to remain the positive relationship between the variables.

Not necessarily.

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