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What is a Simple vs complex hypothesis?
A simple hypothesis is one in which all parameters of the distribution are specified. For example, if the heights of college students are normally distributed with, the hypothesis that its mean is, say,, that is , we have stated a simple hypothesis, as the mean and variance together specify a normal distribution completely. A simple hypothesis, in general, states that where is the specified value of a parameter, ( may represent etc). A hypothesis which is not simple (i.e. in which not all of the parameters are specified) is called a composite hypothesis.For instance, if we hypothesize that (and) or and, the hypothesis becomes a composite hypothesis because we cannot know the exact distribution of the population in either case. Obviously, the parameters and have more than one value and no specified values are being assigned. The general form of a composite hypothesis is or, that is the parameter does not exceed or does not fall short of a specified value. The concept of simple and composite hypotheses applies to both null hypothesis and alternative hypothesis.
Can a hypothesis that has been rejected be of any value to scientists?
Yes. But usually a hypothesis (if, then, because statement) is changed overtime to establish a conclusion on the investigation. The point of the collection of the data is to show whether or not the hypothesis was supported, and if not needs to be corrected/modified. Certain parts may still be helpful/kept but in most cases it is changed
Is it true that for a hypothesis to have value it must be testable?
What do you mean by "value"?Certainly, if a theory is supposed to have scientific value (if it tells us something new about the world around us), there must be evidence to support it, or else it were a bad theory (or actually not a real theory at all).However, every scientific theory starts off as a hypothesis, which is basically just a "quaint idea". By testing that hypothesis (and obtaining positive results), it might actually be developed into a real theory. If the evidence speaks against the hypothesis, the idea just dies right there (or at least it should).So, a hypothesis has to be testable to have value (so it can "grow" into a theory).
A possible explanation or answer to a question is a?
A hypothesis
What is a testable explanation of a situation?
A hypothesis.
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.
What is the outcome of hypothesis testing?
a. the hypothesis ispartly true but needs to be revised. b. the hypothesis wrong. c. the hypothesis is supported. d. the hypothesis is of no value.
What is Hypothesis Testing of Beta Value?
Probability of failing to reject a false null hypothesis.
What is Hypothesis Testing of Alpha Value?
Probability of rejecting a true null hypothesis; that is, the alpha value or risk you are willing to take probabilistically speaking.
What is the meaning of declare value?
When forming a hypothesis for quantitative research, a declarative hypothesis states the expected relation between variables, whereas a null hypothesis states that there is no significant relation.
What is the Probabilities of Beta Value?
In hypothesis testing, this is the probability of failing to reject a false null hypothesis.
What happens when probability value is greater than alpha value?
When probability value (p-value) is greater than alpha value, we fail to reject the null hypothesis.Probablity value is the probability of obtaining an answer equal to or more extreme than the observed value.Alpha value is the level of significance. It's the value set that determines if a result is statistically significant, or in other words, if it's not likely to have occurred simply due to chance. Alpha value is usually 5%.There are two hypotheses when we conduct a hypothesis test: the null hypothesis and the alternative hypothesis.The null hypothesis acts as a default position. It's usually an assumption that there is no relationship between two events or that a treatment has no effect. In most legal systems, the null hypothesis would be that the defendant is innocent.The alternative hypothesis is what we would assume if we reject the null hypothesis. We reject the null hypothesis when the probability value is less than the alpha value.
When do you accept a hypothesis?
You accept an alternative hypothesis when the p-value is greater than the sample a for a confidence level of 95%. The null hypothesis cannot be accepted.
P-value if the null hypothesis is true?
0.5
What is the q-value formula used in statistical hypothesis testing to determine the false discovery rate of a given set of hypothesis tests?
The q-value formula in statistical hypothesis testing is used to calculate the false discovery rate of a set of hypothesis tests. It helps determine the likelihood of falsely rejecting a true null hypothesis.
Does hypothesis and estimate mean the same?
No, an 'hypothesis' is a proposed explanation for something, while an 'estimate' is a guess at a value of something.
What is the p-value if 0.01 is the level of significance and the mean is 18688 and the standard deviation is 15500?
In order to solve this you need the null hypothesis value also level of significance only helps you decide whether or not to reject the null hypothesis, is the p-value is above this then you do not reject the null hypothesis, if it is below you reject the null hypothesis Level of significance has nothing to do with the math
