Questions and Answers:
Hypothesis?
A scientific hypothesis accepted if there is no way to demonstrate that the hypothesis is wrong? Can you explain, I am kinda confused...
Answer: There are some hypotheses that can be phrased in such a way that they can never be disprove. These sorts of speculative hypotheses are gen orally viewed with extreme skepticism until they are positively pr oven. One example is the existence of aliens. You can not find aliens forever and pr opponents of the theory will only claim you haven't found them yet. It such a case it falls upon the one making the claim to meet the burden of proof. Most of the time a hypothesis will be made in a way that can be either pr oven or disprove with evidence or experimentation. A hypothesis is an initial prediction on the outcome of an experiment. It is not the same as a theory which has been repeatedly tested and gen orally agree ed upon to be the best ex plantation for a particular eff etc by the majority of the scientific community.
Hypothesis?
Person is testing whet here students do better when they eat healthier before going to college. At the end of the week he gave them a test and checked the results. Give me a hypothesis please.
Answer: Two-tailed: it is hypothesised that healthy eating will have an eff etc on the quality of work in college students. One-tailed: it is hypothesised that healthy eating will improve the quality of work in college students. (it's usually better to use two-tailed, and you have to include a null hypothesis as well) null: healthy eating will have no impact on the quality of work in college students.
Explain the difference between the null hypothesis and the alternate hypothesis?
Plain the difference between the null hypothesis and the alternate hypothesis. How is the null hypothesis chosen (why is it null)? What is the importance of rejoicing the null hypothesis in relation of the sample to the population? With a failure to reject the null hypothesis, can we make a general statement about the population based on the sample findings?
Answer: I'm going to say that the guy with the untenable name is partly wrong. We initially start with a research hypothesis -- something we believe or would like to show -- e. G. , a new fuel additive will improve gas mil age. Then we figure out whet here the research hypothesis is an appropriate null hypothesis or alternate hypothesis. In the vast majority of cases, it is an alternate hypothesis because it doesn't contain an equal sign (i. E, =,>=,<=) and that's because we gen orally want to show a change or difference in something.. (in fact, that's an easier situation to deal with. ) the other hypothesis (typically the null) is then automatically the exact opposite. For example, if we believe that our new fuel additive will increase gas mil age, obviously we're going to say something like new > old. Then the null automatically becomes new <= old. I don't know exactly why it's called null. Ya' got to have a name. It's just the default. It is what we will presume (like "resumed innocent" in court) unless the evidence is overwhelmingly inconsistent with the default presumption. We never test an actual population parameter; in some cases we test a presumed parameter, or sometimes whet here there is a difference in populations, at least one of which will be represented by a sample. For example, we may know that household income in our town was some figure in the 2000 census. We might take a sample to find out if that figure (a now hypothesized parameter) has changed. In the fuel additive example, we would use a sample to represent a population of automobiles that don't use the additive. And then we apply the additive to produce a sample of cars that represent a (not even yet existent) population of additive-using cars. We reject the null hypothesis when we determine that it is improbable (to some level of significance) that the sample could have been drawn from the hypothesized population. If our additive-using cars get slightly better gas mil age, we probably can't swear that the stuff works. But if it (say) doubtless, such a larger eff etc is unlikely to be from chance (temperature, tire wear, tailwind, driver/terrain differences, etc) and we can presume that the future population of additive-using cars will get better mil age than the non-using population. Nor thing can be said when we fail to reject the null hypothesis -- it's just lack of sufficient evidence. Same as when a jury finds a person not guilty -- just means that the prosecution (whichh has the burden of proof) failed to produce sufficient evidence to overturn the presumption of innocence.
Hypothesis :can an invisible force like god that can interfere with every living things life exist?
Once people. Treat this question as a hypothesis : dint think of god of god as a man wit ha beard. Think of him as an invisible force like gravity. Now work on the hypothesis : can an invisible force that can interfere or determine our lives really exist?
Answer: Well if we are playing scientific hypothesis then I would say yeah that's for sure possible... But you have some evidence to reason this hypothesis? Right? I mean I guess if you were talking about god as electronic interactions (anorthere 'invisible' force) or quantum effects then I would say you have some evidence there but calling it god is a bit misleading. If you are saying there is some sort of intelligence like an invisible being or 'the force' in star wars I would say your hypothesis is wrong and there is no evidence to support it only evidence to disprove it.
When testing a hypothesis, describe the type of data needed to support the hypothesis. Is a certain type of da?
En testing a hypothesis, describe the type of data needed to support the hypothesis. Is a certain type of data more reliable or dependable than other types of data? Why?
Answer: Data collated using scientific methods are the most reliable. There needs to be a definite variable being tested as well as positive and negative controls. The method should be reproducible so another scientist could come along and do the exact same experiment. The data should be collated objectively, meaning personal bias should have nor thing to do with the final results.
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