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The conditions of what is called his control group.
What else can I help you with?
What is meaning by saying that a hypothesis must be testable?
In Karl Popper's terminology there must be a way to prove a hypothesis false. That is what it means when scientists say that a specific hypothesis is a "testable hypothesis".
Why should hypothesis should be testable?
Hypothesis testing is how science progresses. Scientists come up with hypotheses (pl. for hypothesis) based on their observations and what is Known to be true (i.e. Laws of Physics...like gravity). Hypotheses are designed to answer a question and, by definition, MUST be DISprovable. If a hypothesis cannot be disproven, it has no value. For example, if I look outside and then say "I see the sky is blue"...that is not a hypothesis, it is an observation (or maybe a fact...albeit an optical illusion). However, if I look out the window and say "the sky ALWAYS appears blue"....That is a hypothesis, because it is testable and can be disproven, since tomorrow it might be gray.
What must a hypothesis always be?
a best educated guess
What must be true for a hypothesis to become widely accepted by scientist?
For a hypothesis to become widely accepted by scientists, it must be supported by robust and repeatable experimental evidence. Additionally, it should withstand rigorous peer review and be consistent with existing scientific knowledge. The hypothesis should also demonstrate predictive power and be able to explain a range of phenomena within its domain. Finally, it should be open to further testing and refinement as new data emerges.
What happens if a hypothesis is tested and shown to be false?
We do not make a clear separation between "proven true" and "proven false" in hypothesis testing. Hypothesis testing in statistical analysis is used to help to make conclusions based on collected data. We always have two hypothesis and must chose between them. The first step is to decide on the null and alternative hypothesis. We also must provide an alpha value, also called a level of significance. Our null hypothesis, or status quo hypothesis is what we might conclude without any data. For example, we believe that Coke and Pepsi tastes the same. Then we do a survey, and many more people prefer Pepsi. So our alternative hypothesis is people prefer Pepsi over Coke. But our sample size is very small, so we are concerned about being wrong. From our data and level of significance, we find that we can not reject the null hypothesis, so we must conclude that Coke and Pepsi taste the same. The options in hypothesis testing are: Null hypothesis rejected, so we accept the alternative or Null hypothesis not rejected, so we accept the null hypothesis. In the taste test, we could always do a larger survey to see if the results change. Please see related links.
Why do scientists repeat?
Scientists repeat experiments for reliability. The experiment must be repeated for the scientist to develop a theory. One experiment does not prove your hypothesis correct; therefore, it must be done a several times.
How can one formulate a hypothesis effectively using the method of hypothesis testing?
To formulate a hypothesis effectively using hypothesis testing, one must first identify a research question and make a clear statement about the relationship between variables. Then, the hypothesis should be specific, testable, and based on existing knowledge or theory. Finally, the hypothesis should be framed in a way that allows for statistical analysis to determine its validity.
What must always happen before a hypothesis can be formed?
a reveiw of what is known about the subject must occur
Why is a hypothesis not just a guess?
Unlike a wild guess, a hypothesis is based on observations and it must be testable......:-) answer by hismejohn
Why do scientists repeat experiments?
Scientists repeat experiments for reliability. The experiment must be repeated for the scientist to develop a theory. One experiment does not prove your hypothesis correct; therefore, it must be done a several times.
In the hypothesis phase of the scientist process the scientist gives one or more falsifiable explanations for the observation?
In the hypothesis phase of the scientific process, scientists propose one or more testable and falsifiable explanations for their observations. These hypotheses serve as a foundation for further experimentation and investigation, allowing researchers to design experiments that can confirm or refute their proposed explanations. Importantly, a good hypothesis must be specific enough to allow for clear predictions and outcomes. By testing these hypotheses, scientists can refine their understanding of the phenomena being studied.
Why must a scientific hypothesis be stable?
A stable scientific hypothesis allows for consistency and reliability in testing and results. It enables the hypothesis to be accurately evaluated and potentially confirmed or refuted through experimentation. Stability ensures that the hypothesis accurately reflects the phenomena being studied.
