0
Can Bayesian testing come to the same conclusion as null hypothesis significance testing?
Still curious? Ask our experts.
Chat with our AI personalities
Jordan
Lao
RafaAdd your answer:
Earn +20 pts
When should you accept a null hypothesis?
The null hypothesis cannot be accepted. Statistical tests only check whether differences in means are probably due to chance differences in sampling (the reason variance is so important). So if the p-value obtained by the data is larger than the significance level against which you are testing, we only fail to reject the null. If the p-value is lower than the significance level, the null hypothesis is rejected in favor of the alternative hypothesis.
What is the null hypothesis of a one way ANOVA What is the alternate hypothesis?
When writing hypotheses the null hypothesis is generally the hypothesis stating that there will be no significant difference between the variables you are testing. An alternate hypothesis would be a hypothesis suggesting that the results will be anything other than not significant. For example if you were testing three concentrations (low, medium, and high) of a type of medication on cancer cells, then one example of an alternate hypothesis would be that the medium concentration would decrease the number of viable cancer cells.
What is the difference between testing a single mean and testing the difference between two means?
A single mean is used in testing to compare a single variable to a population mean in order to determineÊif there is aÊdifference. Two means are used in testing to compare two populations to see if there are variances between the two variables.Ê
The Central Limit Theorem is important in statistics because?
According to the central limit theorem, as the sample size gets larger, the sampling distribution becomes closer to the Gaussian (Normal) regardless of the distribution of the original population. Equivalently, the sampling distribution of the means of a number of samples also becomes closer to the Gaussian distribution. This is the justification for using the Gaussian distribution for statistical procedures such as estimation and hypothesis testing.
When do i have to have sra on to test for ssgt?
you must have SrA on 6 months prior to the end of the testing cycle. so u must have SrA already sewed on before 1 feb of the testing year.
What is the difference between a hypothesis a theory and a conclusion drawn from hypothesis testing?
A hypothesis is a suggestion of a way to explain something. If the hypothesis is tested and confirmed, it can advance to the status of theory. The conclusion of testing a hypothesis will be either that the hypothesis is confirmed, or it is not confirmed.
What is the process of testing a hypothesis called?
a conclusion
What kind of mathematical tools do biologist use?
Hypothesis and significance testing
What kind of mathematical tools do usually use?
Hypothesis and significance testing
What kind of mathematical tools do biologists usually use?
Hypothesis and significance testing
What has the author Kurt Stange written?
Kurt Stange has written: 'Bayes-Verfahren' -- subject(s): Bayesian statistical decision theory, Estimation theory, Statistical hypothesis testing
What role does Random Sampling Distribution in hypothesis testing?
It is an assumption to hypothesis testing. I can not comment on the significance of a violation of these assumptions without knowing how the non-random sample was taken.
What is non-directional research hypothesis?
A non-directional research hypothesis is a kind of hypothesis that is used in testing statistical significance. It states that there is no difference between variables.
In a hypothesis testing the alternative hypothesis is assumed?
No. The null hypothesis is assumed to be correct unless there is sufficient evidence from the sample and the given criteria (significance level) to reject it.
What is scientific investigation?
A scientific observation is data , a hypothesis , and well a conclusion. Your observing or testing something that can lead you to your conclusion
How would you design an experiment to prove or disprove the hypothesis?
By testing your results, and explain in your conclusion what went wrong
What are the steps in investigating?
1. Identify the problem. 2. Formulate a hypothesis. 3. Conduct experiments testing the hypothesis. 4. Analyze data. 5. Make a conclusion.
