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One-tailed null hypotheses are directional. A null hypothesis should be the opposite of what you hope to show. The terms "one-tailed" and "directional" can be considered synonymous. They basically mean the hypothesis has a single way of being disproved.
1. Drug "A" will not cause an increase in height. (can only be disproved if there is an increases in height)
2. There are a greater number of bicycles than there are cars used for transportation in the city. (only disproved if cars are more numerous)
3. More people eat Pizza than Hot Dogs. (only disproved if more people eat hot dogs)
4. More people wear raincoats instead of using umbrellas (only disproved if more people use umbrella)
5. Person "A" has siblings. (disproved only if person does not have siblings)
Two tailed null hypotheses are non-directional. These hypotheses basically have more than one possible outcome that will disprove them.
1. Drug "A" will not cause a change in height. (increase or decrease in height disproves hypothesis)
2. Bicycles are the most common form of transportation in the city. (disproved more people use cars, walk, subway, buses, etc.)
3. More people eat pizza than any other food. (disproved if hot dogs, burgers, pasta, steaks are more popular)
4. Most people wear raincoats to keep dry from the rain (disproved if more people use umbrellas, ponchos, etc.)
5. Person "A" has 5 siblings. (disproved if person has 0-4 siblings or 6-infinity siblings)
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What causes hypothesis to be rejected?
We have two types of hypothesis i.e., Null Hypothesis and Alternative Hypothesis. we take null hypothesis as the same statement given in the problem. Alternative hypothesis is the statement that is complementary to null hypothesis. When our calculated value is less than the tabulated value, we accept null hypothesis otherwise we reject null hypothesis.
when the null hypothesis is greater than 0.005?
Then the null hypothesis is greater than 0.005! So what?Then the null hypothesis is greater than 0.005! So what?Then the null hypothesis is greater than 0.005! So what?Then the null hypothesis is greater than 0.005! So what?
Explain what is meant by null hypothesis?
The null hypothesis is an hypothesis about some population parameter. The goal of hypothesis testing is to check the viability of the null hypothesis in the light of experimental data. Based on the data, the null hypothesis either will or will not be rejected as a viable possibility.
If we reject the null hypothesis what can we conclude about the alpha risk?
If we reject the null hypothesis, we conclude that the alternative hypothesis which is the alpha risk is true. The null hypothesis is used in statistics.
What does the researcher hope to do with null hypothesis the opposite of the research hypothesis?
Be able to reject the null hypothesis and accept the research hypothesis
What does the researcher hope to do with the null hypothesis (the opposite of the research hypothesis)?
Be able to reject the null hypothesis and accept the research hypothesis
What does the researcher hope to do with the null hypothesis (the opposite of the research hypothesis)?
Be able to reject the null hypothesis and accept the research hypothesis
When you accept the Null Hypothesis you are certain that the Null Hypothesis is correct?
No, you are never certain.
What is a null hypothesis?
The null hypothesis is the statement that there is no relationship between two observations.
Why is a two-tailed test preferred over a one-tailed test?
In general, it is not. A one-tailed test is more powerful but it does require the alternative hypothesis to be one sided and, in therefore requires some expectation about the observations if the null hypothesis is not true.The question, therefore, is appropriate only when the experimenter has extremely limited information about the experiment - not a very common occurrence.In general, it is not. A one-tailed test is more powerful but it does require the alternative hypothesis to be one sided and, in therefore requires some expectation about the observations if the null hypothesis is not true.The question, therefore, is appropriate only when the experimenter has extremely limited information about the experiment - not a very common occurrence.In general, it is not. A one-tailed test is more powerful but it does require the alternative hypothesis to be one sided and, in therefore requires some expectation about the observations if the null hypothesis is not true.The question, therefore, is appropriate only when the experimenter has extremely limited information about the experiment - not a very common occurrence.In general, it is not. A one-tailed test is more powerful but it does require the alternative hypothesis to be one sided and, in therefore requires some expectation about the observations if the null hypothesis is not true.The question, therefore, is appropriate only when the experimenter has extremely limited information about the experiment - not a very common occurrence.
What is another name for the probability of observing a sample value at least as extreme as a given on under a null hypothesis?
The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis. The significance level of the observation - under the null hypothesis.
Difference between acceptance and rejection region?
Some researchers say that a hypothesis test can have one of two outcomes: you accept the null hypothesis or you reject the null hypothesis. Many statisticians, however, take issue with the notion of "accepting the null hypothesis." Instead, they say: you reject the null hypothesis or you fail to reject the null hypothesis. Why the distinction between "acceptance" and "failure to reject?" Acceptance implies that the null hypothesis is true. Failure to reject implies that the data are not sufficiently persuasive for us to prefer the alternative hypothesis over the null hypothesis.
