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By having a control (which is subjected to the same conditions as the test subject[s] except for the condition or substance you are testing) you can eliminate other influences, by comparing the control to your test. In testing medication, for example, this is VERY important - if only to account for the PLACEBO EFFECT that occurs.
By having a variable, you can compare the results of a series of applications of the specific condition or substance you are testing, which should show at what level(s) the experiment works and possibly what side effects occur.
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The variable provides the data that are to be interpreted and compared.
The control provides a reference, or standard, for comparison. Without this reference, no valid comparison is possible so, the data is moot, and the hypothesis can't be tested.
What else can I help you with?
Why is it important to have controls in an investigation?
Without controls it is not possible to make a hypothesis
Why is it important to have a control in an investigation?
Without controls it is not possible to make a hypothesis
What is the purpose of controlling the environment when testing a hypothesis?
The purpose of controlling the environment when testing a hypothesis is ultimately to get a reliable result to the study.
How important is testing in the process of validating a hypothesis?
Testing is crucial in validating a hypothesis as it provides empirical evidence to either support or refute the proposed explanation. Through systematic experimentation and data collection, researchers can assess the reliability and validity of their hypothesis. Without testing, hypotheses remain speculative and lack the necessary grounding in observable reality. Ultimately, robust testing leads to more credible conclusions and advancements in knowledge.
How is a scientific hypothesis evaluated?
By testing.
Why is it important to have controls in an investigation?
Without controls it is not possible to make a hypothesis
Why is it important to have a control in an investigation?
Without controls it is not possible to make a hypothesis
Why is important that a sample be random and representative when conducting hypothesis testing?
It helps you nawser
What are the most important controls needed in this experiment?
It is a conclusion,variable,a hypothesis,procedure,and data.
What is the difference between forming a hypothesis and testing a hypothesis?
forming a hypothesis is when you come up with an educated guess.. what you think it may be . testing a hypothesis is when you're testing to see if someone else's guess is right.
What following statement is not part of testing a hypothesis?
Concluding that the hypothesis is correct based on personal beliefs or opinions is not part of testing a hypothesis. Testing a hypothesis involves designing experiments, collecting data, and analyzing results to determine if the hypothesis is supported or not.
What is the act of testing a hypothesis?
examining/ experimenting/ testing/ verifying... it depends on the type of hypothesis to an extent I think.
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 purpose of controlling the environment when testing a hypothesis?
The purpose of controlling the environment when testing a hypothesis is ultimately to get a reliable result to the study.
What is Hypothesis Testing of Type I Error?
Rejecting a true null hypothesis.
How important is testing in the process of validating a hypothesis?
Testing is crucial in validating a hypothesis as it provides empirical evidence to either support or refute the proposed explanation. Through systematic experimentation and data collection, researchers can assess the reliability and validity of their hypothesis. Without testing, hypotheses remain speculative and lack the necessary grounding in observable reality. Ultimately, robust testing leads to more credible conclusions and advancements in knowledge.
How do you decide whether to use a z test or a t test when testing a hypothesis about a population mean?
You use a z test when you are testing a hypothesis that is using proportions You use a t test when you are testing a hypothesis that is using means
