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Does null hypothesis determine whether p value for non directional or directional testing on hypothesis should be used?
A null hypothesis is simply a postulate or, put another way, a possible statement of fact. It is a claim about something that might be accepted as true that is to be tested.
It does not determine in any way what decision method should be used to test whether it should be accepted. Therefore, it does not determine any aspect of the decision method that is used such as p value.
In general there are many rational ways of testing one hypothesis against another. Some of these ways will have better statistical properties than others; some might be cheaper or more convenient to perform. But none would be determined by the pair of hypotheses.
What else can I help you with?
What is the directional and non-directional hypothesis testing?
In statistical hypothesis testing you have a null hypothesis against which you are testing an alternative. The hypothesis concerns one or more characteristics of the distribution. It is easier to illustrate the idea of directional and non-directional hypothesis. In studying the academic abilities of boys and girls the null hypothesis would be that boys and girls are equally able. One directional hypothesis would be that boys are more able. The non-directional alternative would be that there is a gender difference. You have no idea whether boys are more able or girls - only that they are not the same.
How do you determine directional or non-directional alternate hypotheses?
Whether you frame your alternative hypothesis, Ha, as one-sided (directional) or two-sided (non-directional) is really up to you, but should be decided before you look at the data. It will affect the calculation of your p-value and ultimately your conclusions from the test. In most cases there will be a sound, obvious reason for choosing one or the other.For example, if you were testing the effectiveness of a new anti-cholesterol drug you'd probably only be interested in testing whether the average of the experimental group was lower than the control group. So Ha is directional, or one sided. If on the other hand you were testing, for example, whether a Group A performed better on a test than Group B, your Ha would be that the average of Group A does not equal Group B. That is, you're not sure, before you run the test, whether Group A should perform better or worse than Group B. So your test is non-directional, or two-sided.
What is directional hypothesis?
A non-directional hypothesis only proposes a relationship. In contrast, a directional hypothesis also proposes a direction in the relationship. For example, when one variable increases, the other will decrease.
How do you decide whether to use a z test or a t test when testing a hypothesis about a population mean?
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
Is the null hypothesis considered correct until proven otherwise?
No. The null hypothesis is not considered correct. It is an assumption, and hypothesis testing is a consistent meand of determining whether the data is sufficiently strong to say that it may be untrue. The data either supports the alternative hypothesis or it fails to reject it. See examples in links. Also note this quote from Wikipedia: "Statistical hypothesis testing is used to make a decision about whether the data contradicts the null hypothesis: this is called significance testing. A null hypothesis is never proven by such methods, as the absence of evidence against the null hypothesis does not establish it."
What is the directional and non-directional hypothesis testing?
In statistical hypothesis testing you have a null hypothesis against which you are testing an alternative. The hypothesis concerns one or more characteristics of the distribution. It is easier to illustrate the idea of directional and non-directional hypothesis. In studying the academic abilities of boys and girls the null hypothesis would be that boys and girls are equally able. One directional hypothesis would be that boys are more able. The non-directional alternative would be that there is a gender difference. You have no idea whether boys are more able or girls - only that they are not the same.
How do you determine directional or non-directional alternate hypotheses?
Whether you frame your alternative hypothesis, Ha, as one-sided (directional) or two-sided (non-directional) is really up to you, but should be decided before you look at the data. It will affect the calculation of your p-value and ultimately your conclusions from the test. In most cases there will be a sound, obvious reason for choosing one or the other.For example, if you were testing the effectiveness of a new anti-cholesterol drug you'd probably only be interested in testing whether the average of the experimental group was lower than the control group. So Ha is directional, or one sided. If on the other hand you were testing, for example, whether a Group A performed better on a test than Group B, your Ha would be that the average of Group A does not equal Group B. That is, you're not sure, before you run the test, whether Group A should perform better or worse than Group B. So your test is non-directional, or two-sided.
What is directional hypothesis?
A non-directional hypothesis only proposes a relationship. In contrast, a directional hypothesis also proposes a direction in the relationship. For example, when one variable increases, the other will decrease.
If group a has a higher mean than group b the research hypothesis is directional or non directional?
Whether your alternate hypothesis is directional (one-sided) or non-directional (two-sided) is largely up to you but must be determined before you conduct your experiment, not after. It's not defined by the outcome.
How do you decide whether to use a z test or a t test when testing a hypothesis about a population mean?
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
It Comes after a hypothesis and is used to determine whether the hypothesis is correct?
Test your hypothesis by Doing an Experiment
Which step of the scientific inquiry involves testing the hypothesis which step of the scientific inquiry involves testing the hypothesis and collecting data?
The step of scientific inquiry that involves testing the hypothesis and collecting data is the experimentation phase. During this stage, researchers design and conduct experiments to gather evidence related to their hypothesis. The data collected is then analyzed to determine whether it supports or refutes the hypothesis, forming the basis for further conclusions. This step is crucial for validating scientific claims.
Made before scientists can test a hypothesis?
A hypothesis is a proposed explanation for a phenomenon. It is made before scientists conduct experiments or gather data to test whether it is accurate or not. The purpose of testing a hypothesis is to determine if it is supported by evidence and can be considered a valid explanation for the observed phenomenon.
What are the steps of testing your hypothesis?
Testing a hypothesis typically involves several key steps: first, clearly define your hypothesis and establish the variables involved. Next, design an experiment or study to collect data, ensuring you include control and experimental groups as needed. After conducting the experiment, analyze the data to determine whether it supports or refutes your hypothesis. Finally, draw conclusions based on the results and consider any necessary revisions or further testing.
What is the meaning of trial?
In terms of science, a trial is when a scientist begins testing whatever hypothesis he or she is investigating. The scientist will then study the data obtained, and determine whether or not the original hypothesis needs to be changed.
What is it called when scientists state whether their data confirmedor rejected the hypothesis?
When scientists evaluate whether their data confirmed or rejected the hypothesis, it is referred to as hypothesis testing. This process involves analyzing the results of experiments or observations to determine if they support or contradict the initial hypothesis formulated before the research. If the data supports the hypothesis, it may lead to further investigation; if it rejects the hypothesis, researchers may revise their understanding or formulate new hypotheses.
When you decide whether or not the data supports the original hypothesis you are?
When you decide whether or not the data supports the original hypothesis, you are engaging in hypothesis testing. This process involves analyzing the collected data to determine if it aligns with your predictions or expectations. If the data shows significant evidence in favor of the hypothesis, it can be accepted; if not, the hypothesis may need to be rejected or revised. Ultimately, this decision helps validate or challenge your initial assumptions based on empirical evidence.
