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When setting the selling price of a product, businesses use quantitative data of the annual income of a person or household to determine their purchasing power. Large government research departments uses census data to predict which sector of the economy needs money and how much they need, how many seats a state will have in the U.S. The Government carry out census to acquire and record information about the members of a given population. For instance, a company who is about to launch a new product into the market will analyse quantitative data from previous research to predict an increase or decrease in sales. Researchers project future data using algorithms and mathematical analysis tools. Quantitative Data Examples in Research
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These examples vary and will therefore be separately highlighted below. There are various Quantitative data examples which are applied in both research and statistics. The above characteristics of ratio data allows for the application of a wide range of inferential and descriptive statistical methods. It is the ultimate when we talk about data measurement because it tells us about the order, exact distance between units on the scale, and has an absolute zero. Ratio data on the other hand, is an extension of interval data. It is an extension of ordinal data, with a standardised scale as opposed to the former.
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Interval data is defined as type of data which is measured along a scale, in which each point is placed at equal distance from one another. In this case, the data has neither an upper nor a lower bound.Ĭontinuous data can also be divided into two types, namely ratio data and interval data. An example of a countably finite data is an arbitrary set A =. When trying to identify discrete data, we ask the following questions Can it be counted? Can it be divided into smaller parts?ĭiscrete data can be said to be either countably finite or countably infinite. Measurements like weight, length, height are not classified under discrete data.Įxamples of discrete data include the number of students in a class, the number of days in a year, the age of an individual, etc. Quantitative Data can be divided into two types, namely Discrete & Continuous Data.ĭiscrete data is a type of data that consists of counting numbers only, and as such cannot be measured. For example, a manufacturing company will need an answer to the question, “How much is the production cost?”.Ī quantitative data of the company's cost of production will be collected through this question and will inform the company's selling cost (where selling cost = production cost + profit). This data type can also be defined as a group of quantifiable information that can be used for mathematical computations and statistical analysis which informs real-life decisions. Also known as numerical data, quantitative data further describes numeric variables (e.g. Quantitative data is the type of data whose value is measured in the form of numbers or counts, with a unique numerical value associated with each data set.