what's the difference between quantitative and qualitative evidence.?
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quantitative evidence deals with the amount and qualitative deals with the quality of the evidence, is it realiable or not.
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Qualitative data is to do with characteristics of things eg. colours, say, something is red.  Qualitative data is descriptive words, really. \n\nQuantitative data is to do with numbers; the numerical information relating to the data. \n\nDicrete and Continuous are examples of Quantitative data.\n\nDiscrete variables are those which have a SET value like shoe sizes-- you can only have certain sizes like 5, 6 (or sometimes half-sizes as well), but no other values like 5.2534...  \n\nContinuous are like people's heights where you can have ANY value like 6 feet so-and-so inches. (or 156.98437485... inches or something like that)\n\nhope this helps :-)
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Go to yahoo and it will help you do this homework  put in define \nstatistic and a parameter and it will tell you the difference.
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A hypothesis test starts from the assumption that the null hypothesis is correct (c) and then you test whether the data is likely under this assumption.  If the data refutes the null hypothesis to the chosen significance level than you are said to have proven the alternative hypothesis to be likely.\n\n\nIs this for highschool homework?  If you need help I have a degree in statistics and can help you understand this stuff but if you just want someone to do your homework you should re-think this.  Trying to get to the end result without learning the process won't get you anywhere in life.  Even if you don't use this in your future career it is still worth learning.
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Qualitative is relating to or based on the quality or character of something, as opposed to its size or quanity.  I'm sure you know what investigation means.
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"Descriptive statistics" are typically distinguished from inferential statistics. With descriptive statistics you are simply describing what is or what the data shows. With "inferential statistics", you are trying to reach conclusions that extend beyond the immediate data alone.\n\nScience deals with the natural world. Technology is the study of the natural laws which govern the universe.
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there physical evidence and circumstantial evidence.        \n\nphysical is like a bloody glove or bones or any thing physical \n\ncircumstantial is like a map or time line of how things happen \n\ntake the oj thing for instance the glove was physical and the time line to show wat happend were was circumstantial
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Qualitative is contrasted with quantitative. Qualitative deals with words or ideas as data rather than with numbers. For example, if you ask people to tell you why we are at war with Iraq, and you record and summarize their answers, this would be qualitative. Usually it's much more open-ended than quantitative, meaning that you allow people to give their views in their own terms. This also usually makes it more difficult to interpret qualitative data, although many would argue that it more accurately reflects people's views.\nWith quantitative research, you immediately convert answers to numbers. E.g., "how much do you agree with the war" on a scale from 1 to 5. Or, Do you agree or disagree. Notice that the answers can easily be summarized as the percent who agree or disagree, or how many agree with what strength. But respondents don't have the option of explaining their views in any detail.\nGenerally, interviews and focus groups are techniques of choice for qualitative researchers; surveys or questionnaires are the techniques preferred by quantitative researchers.\nYou can find many good sources on qualitative research  at any college library or at a book site such as Amazon.
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Quantitative Research\n\nBy definition, measurement must be objective, quantitative and statistically valid. Simply put, it's about numbers, objective hard data. A scientifically calculated sample of people from a population is asked a set of questions on a survey to determine the frequency and percentage of their responses.
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I hate to tell you this, but it may depend (in part on the instructor).  Some people say that deductive reasoning goes from "general to specific" (applying a general principle to a specific example), while inductive reasoning goes from "specific to general" (trying to derive a general principle from specific examples).  THIS IS NOT ACCURATE, but this is how many non-logicians present the difference.\n\nA deductive argument seeks to prove the truth of the conclusion.  That is, if the premises (reasons) are true, then the conclusion must also be true.  An example is the sort of argument you see on standardized tests all the time:\nAll dogs are mammals.\nFido is a dog.\nTherefore, Fido is a mammal.\nThis is a deductive argument--if the first two sentences are true, then the last sentence must be true.  Deductive arguments can be evaluated for consistency, validity, and soundness--we won't worry about what all that means here (email me if you really want to know)--but a good deductive argument gives a proof of the conclusion that it offers.\n\nInductive reasoning, on the other hand, seeks to provide support for a conclusion.  Quite often you will find statistics being used in an inductive argument--perhaps because there are no hard and fast reasons that can be used to create a deductive argument.\n\nWhich is better?  Deductive arguments are preferred, because they offer a proof.  Inductive arguments cannot offer proof--they only offer support to a claim.  (And inductive arguments are used in advertising all the time--like the toothpaste commercial that reports that 4 out of 5 dentists recommend their brand--trying to give us a reason to support a claim that they cannot prove.)
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Experiments that result in Numerical Data are called Quantitative Research.\n\nExperiments that result in data based on feelings and peoples opinions/comments are called Qualitative Research
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experiment is replicated. data anaylsis has more got to do with experiments than treatments.
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In a controlled experiment, you control the variables and thus, you affect the outcome. In an observational study, you don't touch anything and you don't affect the outcome.
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Deductive.\n\nWhen you know a rule and apply it to a situation, you are DEDUCING the solution in that situation.\n\nThe other type of reasoning is inductive.\nWhen you observe many examples of a particular behavior (or relationship, or whatever), you may conclude INDUCTIVELY that it will occur in ALL situations. (But of course you can't be SURE that it will. Your degree of confidence is based on the number of situations in which you have seen it happen, and the fact that you have never seen it NOT happen.)
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Hypothesis: This is an educated guess based upon observation. It is a rational explanation of a single event or phenomenon based upon what is observed, but which has not been proved. Most hypotheses can be supported or refuted by experimentation or continued observation. \n\nTheory: A theory is an explanation of a set of related observations or events based upon proven hypotheses and verified multiple times by detached groups of researchers. One scientist cannot create a theory; he can only create a hypothesis.
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Quantitative Analysis: When you can analyze some property that can be expressed with numbers -- such as, length, weight etc.\n\nQualitative Analysis: When yoy analyse some property that doesn't "really" fall on a numeric scale -- abstract in nature -- such as smartness, beauty.\n\nOften times, abstract properties are expressed on a numeric scale to perform qualitative analysis.
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qualitive & quantitive