Quantitative Research Healthcare relies on quantitative research for evidence-based practice in nursing, for organizational structure, design, and marketing, for public health and value-based purchasing issues, safety, and a practically unlimited array of other uses. Using quantitative research methods generates numerical data: data that can be used to generate statistics, to track patterns reliably using metrics, and to make fairly accurate predictions based on quantitative modeling. The research methods used in quantitative

Some specific examples of this include the following: Quantitative methods are used to construct the sample of participants to the drug test or clinical trial Quantitative methods are used to describe the features of the participants, such as their age, their medical history, the gravity of their conditions, the projections of success of the trial / drug test for the various patient categories and so on Quantitative methods are used to

The high stakes testing proponents believes that the use of testing will motivate students, their families and teachers to take education more seriously. (Nathan, 2002, p.595) Many opponents on the other hand believe that "teaching to the test" will likely prove disastrous for the schools and curriculums involved and this is especially true if the test is the only gauge of success or if there is any question as

Forecasting Methods There are three basic forecasting methods namely the time series methods, the regression methods, and qualitative methods. Qualitative methods use management judgment, expertise, and opinion to make forecasts. These methods are most commonly used in long-term strategic planning process bearing in mind there are individuals within an organization whose judgment and opinion are very integral in the running of search organizations (Brown, 1959). In fact their opinions count more

Companies frequently fall in love with the data-rich results and think that the results are projectable. This supposition is wrong. Projectabilty is not possible, as the analysis is slanted and deals with a small size. Another general misapprehension is the belief that qualitative research will always give perfect deductions. Actually, the results will not give companies with perfect deductions, but only with adequate information to set up a firm

." Where the data consists of numerical things like number of cows that give birth to bulls in a region, the answer may be straightforward. But where there is interaction between the chosen variables, especially where the humans are involved as a variable unlike inanimate objects like gases or salt will not produce the same linear results that could be expected from a scientific experiment as in physics for example. In