what does qualitative , quantitative data ,discrete and continuous mean?
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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 :-)
822199
I hope I understand your question there is qualitative reseach and quantitative.
242624
http://en.wikipedia.org/wiki/Mean_%28statistics%29\n\nThis is a link from Wikipedia. It shows lots of examples along with explanations.
591179
What kind of data?  You mean anything or pictures, words, or ??
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Qualitative refers to not measureing exact quantities, but rather how things relate. As opposed to Quantitative.\n\nFor example qualitativly it will require higher interest rates to borrow money for a riskier venture. Quantitatively it will cost you 1% increase in interest rates to purchase a rental house versus your residence.\n\nOne should be able to apply this tidbit of knowledge to forecasting methods too, although I might not know exactly what the ones are you are refering too. \n\nRather than saying how much something will be affect by an action you can say in what direction its affect will be. e.g. the city paying less to have the parks kept up will bring fewer people in to the open air market right next to the park whcih will tend to decrease the amount of business transactions. Even though more advertising by the market will increase it by a larger amount and it will go up overall. All of this as opposed to saying by how much business will be done because of these things.
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How about:\noptical activity\npolarisation\nrheology\nelectrochemistry\ndiffusion\nsurface activity
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If numerical data is not available, sometimes one collects qualitative, or descriptive data.  Instead of a list of numbers, you end up with descriptions of what occurs.
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a continuous function is defined in terms of limits across its entire domain.  this can be formally shown to be equivalent to this statement:  a function is continuous if it is *differentiable* across its entire domain.\n\nthis means, if a derivative exists for every point on the function where the function is defined, then it is continuous.  so, for example, the function:\n\nf(x) = { 0 when x < 1;\n         2 when x >= 1 }\n\nhas a step change at x = 1.  so the domain of this function is (-oo, oo) (that is, negative infinity to plus infinity) but it is not differentiable at x=1.  this is because the limit of the function when approaching x=1 is different when you're coming from the right or the left.\n\nbasically, continuous just means that you can graph the function without lifting your pencil off the paper.  there are no jumps or places where you have to pick up and go to another spot on the page.  another example of a discontinuous function is f(x) = 1/x, because as you approach zero from the negative side, you have to lift up your pencil when you cross zero and go to the top of the paper.\n\nthe formal definition of continuous functions is in terms of delta and epsilon, and you can read about it on this mathworld page:\nhttp://mathworld.wolfram.com/ContinuousFunction.html\n\ncheers!
841311
This info is a part of an introductory phase of a basic statistics course. The four scales of measurement are nominal, ordinal, interval, and ratio.\nNominal: Categorical data and numbers that are simply used as identifiers or names represent a nominal scale of measurement. Numbers on the back of a baseball jersey (St. Louis Cardinals 1 = Ozzie Smith) and your social security number are examples of nominal data. If I conduct a study and I'm including gender as a variable, I will code Female as 1 and Male as 2 or visa versa when I enter my data into the computer. Thus, I am using the numbers 1 and 2 to represent categories of data.\n\nOrdinal: An ordinal scale of measurement represents an ordered series of relationships or rank order. Individuals competing in a contest may be fortunate to achieve first, second, or third place. First, second, and third place represent ordinal data. If Roscoe takes first and Wilbur takes second, we do not know if the competition was close; we only know that Roscoe outperformed Wilbur. Likert-type scales (such as "On a scale of 1 to 10 with one being no pain and ten being high pain, how much pain are you in today?") also represent ordinal data. Fundamentally, these scales do not represent a measurable quantity. An individual may respond 8 to this question and be in less pain than someone else who responded 5. A person may not be in half as much pain if they responded 4 than if they responded 8. All we know from this data is that an individual who responds 6 is in less pain than if they responded 8 and in more pain than if they responded 4. Therefore, Likert-type scales only represent a rank ordering.\n\nInterval: A scale which represents quantity and has equal units but for which zero represents simply an additional point of measurement is an interval scale. The Fahrenheit scale is a clear example of the interval scale of measurement. Thus, 60 degree Fahrenheit or -10 degrees Fahrenheit are interval data. Measurement of Sea Level is another example of an interval scale. With each of these scales there is direct, measurable quantity with equality of units. In addition, zero does not represent the absolute lowest value. Rather, it is point on the scale with numbers both above and below it (for example, -10 degrees Fahrenheit).\n\nRatio: The ratio scale of measurement is similar to the interval scale in that it also represents quantity and has equality of units. However, this scale also has an absolute zero (no numbers exist below the zero). Very often, physical measures will represent ratio data (for example, height and weight). If one is measuring the length of a piece of wood in centimeters, there is quantity, equal units, and that measure can not go below zero centimeters. A negative length is not possible.\n\nThe table below will help clarify the fundamental differences between the four scales of measurement\n\n 1)Indications Difference 2)Indicates Direction of Difference  3)Indicates Amount of Difference 4)Absolute Zero \n\nNominal X           1\nOrdinal  X X        1-2\nInterval  X X X     1-3\nRatio X X X X      1-4\n\n\nYou will notice in the above table that only the ratio scale meets the criteria for all four properties of scales of measurement.
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A discrete variable typically fits into a category and is a yes or no answer.  They are tabulated into single events, i.e. broken = yes or no?.\n\nA continuous variable is something measured on a continuum, and can have an infinite number of values.\n\nA good test for this is to ask if it can be divided in half.  For example, Can something be half broken?  If is doesn't make sense to be, it is discrete.
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Try here (the content is very techinical).  http://scienceworld.wolfram.com/physics/ContinuityEquation.html\nhttp://www.efm.leeds.ac.uk/CIVE/CIVE1400/Section3/continuity.htm
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Bandwidth is a measure of data volume over time.  Do you mean how much cumulative data is transferred over the course of a day?  I'd say that number is probably close to a petabyte (a million gigabytes).
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Happiness is qualitative. It can not be quantified. But the Utilitarians wanted to quantify it in the 19th century.
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Anytime you have a problem that is continuous, as opposed to discrete, you will need to use either integration or differentiation to characterize the solution.  That means to say that every problem that involves time in one way or another will necessitate the use of calculus to find an answer at some instant in time.  If the problem is such that you can approximate the answer, then you can discretize the parameters as small slices of time and come up with an approximate answer - without using calculus.
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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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The study of organizing data.  It implies Computers.
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It refers to the practice of recording financial transactions into various journals or ledgers.  Just the raw financial data, no analysis on it yet.