Quantitative techniques aim at gathering important numerical data for statistical analysis. This analysis in turn facilitates research studies and enables the organizational leadership to make important business decisions. Businesses therefore leverage the use of different types of quantitative techniques to carry out research.
All these techniques typically fall under three broad categories, namely statistical, mathematical or programming. Many businesses and data collection companies in India use multiple techniques simultaneously to arrive at accurate research findings. Lets take a look how to complete analysis of quantitative data with the different techniques in the net segment.
1. Differentiation: A mathematical process that involves calculus, differentiation is a technique that is used to witness the process of change within a given system over a period of time. Differentiation studies the changes brought about a variable and the results affected by these variations.
2. Regression Analysis: This quantitative technique is extremely useful and is used by businesses almost on a daily basis. Researchers prefer this technique as it helps establish a causal relationship between two independent variables in a given system. Regression analysis uses predictors and independent variables as two sets of data. Comparing these two sets therefore forms an important base for regression analysis.
3. Factor Analysis: Another favoured technique of researchers, factor analysis trims down the available data to explore the similarities between different data sets. By doing this, factor analysis helps reveal hidden trends within the data without making the researchers do all the work.
4. Indexes: Indexes are considered to be an effective quantitative technique to both simplify as well as share the research data with the public. The financial sector uses this technique to represent the financial health of the industry. Indexes are highly useful to analyze how different trends within an environment are behaving.
5. Game and Probability Theory: This theory aims to discover the most appropriate strategy in the current scenario. The Game and Probablity Theory uses various quantitative methods and experiments to find the most optimal course of action. Even though this technique is less used in business environments for the purpose of analysis of quantitative data, it is still a very useful technique to gauge the complexity of a situation where one is unsure of the available options.
Alongside these techniques, quantitative data can also be gathered by using many other methods as well. Electronic surveying and sensors are used to collect numerical data from inanimate objects. Then there are surveys and questionnaires that help gather information from people. But many a times, this collected data not yield appropriate results. Hence, its important to leverage the above-mentioned techniques to arrive at statistically sound outcomes.
In conclusion, therefore, use these techniques to analyze the given data to enable ease of predictions and future forecasts.
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