Quantitative data is any kind of data that can be measured numerically. For example, quantitative data is used to measure things precisely, such as the temperature, the amount of people in a crowd or the height of a structure. Although quantitative data usually involves numbers and equations, some data records actions, such as the frequency of human behavior.Know More
Quantitative research methods are most often used science, psychology and economics. Although quantitative data involves exact measurements, the data is still subject to variables. For example, a researcher gathering quantitative data on the financial earnings of a group of people may not have access to all financial documents, or some earnings may not be reported. However, quantitative data relies less on interpretation, so it is generally considered to be very accurate.
Quantitative data is often analyzed using statistics to record the frequency of occurrences. This kind of data rarely results in a new theory. Instead, most quantitative data builds on existing academic theories.
Quantitative data is often contrasted to qualitative data. Qualitative data is commonly used in the social sciences to record and analyze observations that cannot be measured or quantified, such as the behavior of people. However, qualitative and quantitative data can both be used to investigate the same research question and reach the same conclusion.Learn more about Statistics
One of the greatest disadvantages of using range as a method of dispersion is that range is sensitive to outliers in the data. Range only considers the smallest and largest data elements in the set.Full Answer >
R-squared is used for linear regression analysis by transforming the dependent variable in a regression model that is fitted to a particular set of data. In order to use R-squared on a specific regression model, a statistician may have to start with other transformations such as logging and deflating so as to eliminate unnecessary variability caused by factors such as inflation. These transformations explain a significant amount of variance.Full Answer >
The box-and-whisker plot is a technique in statistics that graphically shows the distribution of a set of data involving the minimum and maximum values, as well as the first, second and third quartiles. The plot is typically drawn using a number line.Full Answer >
According to an article from the Wharton School at the University of Pennsylvania, one way statistics are misused is when businesses infer false information from data gained during the course of their business, creating errors that cost time and money. Errors like this arise when an entity performs statistical research but fails to address all the components involved in the subject they are researching.Full Answer >