A hypothesis is a testable statement. To check the accuracy of your statement, you need to design an experiment to test it and collect data. Then you analyze your data to see how well it supported your hypothesis.
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
1)Ask a question 2)Make a hypothesis (predict what will happen with your experiment) 3)Research your hypothesis 4)Test your hypothesis 5)Collect/organized your data 6)Results 7)Draw a conclusion
The question is very poorly specified so this answer is simply a wild guess at what the questioner might want. Three possible outcomes of any research, designed to test some hypothesis, are: (a) evidence in support of the hypothesis; (b) evidence disproving the hypothesis; or (c) evidence that can neither prove (support) nor disprove the hypothesis.
Any decision based on the test statistic is marginal in such a case. It is important to remember that the test statistic is derived on the basis of the null hypothesis and does not make use of the distribution under the alternative hypothesis.
An experiment
how will you ensure safety while performing experiment
when there s proof to back it up with evidence or an experiment to test the hypothesis
Data
Through observation, survey, or secondary data
You obtain objective evidence to support it by undertaking experiments designed to test the veracity of the hypothesis.
when there s proof to back it up with evidence or an experiment to test the hypothesis
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
It is the hypothesis that is presumed true until statistical evidence in the form of a hypothesis test proves it is not true.
It is important to be able to test the hypothesis because testing your hypothesis is how you prove or disprove your theories. If it is disproved then you can change your hypothesis.
Ask a question. Form a hypothesis. Prodedure. Data. Evidence. Conclusion. Reasons for error.There are many other forms of the scientific method. If this is not useful... One word for ya... GOOGLE!
To start with you select your hypothesis and its opposite: the null and alternative hypotheses. You select a confidence level (alpha %), which is the probability that your testing procedure rejects the null hypothesis when, if fact, it is true.Next you select a test statistic and calculate its probability distribution under the two hypotheses. You then find the possible values of the test statistic which, if the null hypothesis were true, would only occur alpha % of the times. This is called the critical region.Carry out the trial and collect data. Calculate the value of the test statistic. If it lies in the critical region then you reject the null hypothesis and go with the alternative hypothesis. If the test statistic does not lie in the critical region then you have no evidence to reject the null hypothesis.
evidence that supports it.