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Experimental data in science and engineering is data produced by a measurement, test method, experimental design or quasi-experimental design. In clinical research any data produced are the result of a clinical trial. Experimental data may be qualitative or quantitative, each being appropriate for different investigations.
The ease of quantification is one of the features used to distinguish hard and soft sciences from each other. Scientists often consider hard sciences to be more scientific or rigorous, but this is disputed by social scientists who maintain that appropriate rigor includes the qualitative evaluation of the broader contexts of qualitative data.
Quantitative research is a research strategy that focuses on quantifying the collection and analysis of data. [1] It is formed from a deductive approach where emphasis is placed on the testing of theory, shaped by empiricist and positivist philosophies.
This example of design experiments is attributed to Harold Hotelling, building on examples from Frank Yates. [22] [23] [15] The experiments designed in this example involve combinatorial designs. [24] Weights of eight objects are measured using a pan balance and set of standard weights. Each weighing measures the weight difference between ...
While the tools of data analysis work best on data from randomized studies, they are also applied to other kinds of data—like natural experiments and observational studies [19] —for which a statistician would use a modified, more structured estimation method (e.g., difference in differences estimation and instrumental variables, among many ...
In science, quantitative structure is the subject of empirical investigation and cannot be assumed to exist a priori for any given property. The linear continuum represents the prototype of continuous quantitative structure as characterized by Hölder (1901) (translated in Michell & Ernst, 1996). A fundamental feature of any type of quantity is ...
Test the hypothesis' predictions by an experiment, observational study, field study, or simulation; Draw a conclusion from data gathered in the experiment, or revise the hypothesis or form a new one and repeat the process; Write a descriptive method of observation and the results or conclusions reached
For quantitative data, collection is done by measuring numerical information using instruments. In agriculture and biology studies, yield data and its components can be obtained by metric measures. However, pest and disease injuries in plats are obtained by observation, considering score scales for levels of damage.