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A sampling error could occur from?
a poorly designed hypothesis
When do we reject a hypothesis?
When we've proven that the hypothesis is false !
What is the difference between a hypothesis and a working hypothesis?
The difference is that working hypothesis is that your still working on it but the hypothesis that your not working on it.
What is difference between a hypothesis and a scientific hypothesis?
A scientific hypothesis has to be testable.
What does it mean if a scientist fails to rejects a hypothesis?
the hypothesis has not been proven wrong.
What is 2 types of hypothesis?
A hypothesis can be framed in either a positive or negative manner. The results will show that this WILL occur. The results will show that this WILL NOT occur.
What is the meaning of hypothesis in statistics?
A hypothesis is the first step in running a statistical test (t-test, chi-square test, etc.) A NULL HYPOTHESIS is the probability that what you are testing does NOT occur. An ALTERNATIVE HYPOTHESIS is the probability that what you are testing DOES occur.
What do you do have to do on a hypothesis question?
You have to write what you expect is going to occur.
What is A logical explation for events that occur in the natural world?
hypothesis
A sampling error could occur from?
a poorly designed hypothesis
What is an educated guess made by scientist about what they think will occur?
Hypothesis
What is a hopothesis?
A hypothesis is an educated guess about what will occur due to a certain set of circumstances.
The hypothesis that the evolution of different species occur at a slow constant rate is called?
Gradualism.
What makes a hypothesis in a science experiment testable?
Prediction of Observation. An Hypothesis is testable when it predicts what observations will occur under some circumstance that can be experimentally created.Either it does so accurately, or it does not.
What must always happen before a hypothesis can be formed?
a reveiw of what is known about the subject must occur
Differences between null and alternative hypothesis?
The difference between the null hypothesis and the alternative hypothesis are on the sense of the tests. In statistical inference, the null hypothesis should be in a positive sense such in a sense, you are testing a hypothesis you are probably sure of. In other words, the null hypothesis must be the hypothesis you are almost sure of. Just an important note, that when you are doing a tests, you are testing if a certain event probably occurs at certain level of significance. The alternative hypothesis is the opposite one.
If experiments support a hypothesis why is the hypothesis still not considered?
A better explanation might exist.
