What Are the Different Types of Data Analysis?
1. Descriptive Analysis
Descriptive analysis is the process of using statistical techniques to describe or summarize a set of data. It is popular for its ability to generate accessible insights from otherwise uninterpreted data with simple discrete numerical answers. They are frequency, mean, median, mode, percentiles, and quartiles.
2. Diagnostic Analysis
Diagnostic analysis is a form of advanced analytics that examines data or content to answer the question "why." It is performed by using human-driven techniques such as drill-down, data discovery,and data mining. It also includes making calculations using statistical software or functions for such things as correlations and trend lines.
3. Exploratory Analysis
Exploratory analysis is the critical process of performing initial investigations into data to discover patterns, groupings, correlations, spot anomalies, identify outliers, develop hypotheses and test assumptions. It is entirely a human-driven visual approach..
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4. Inferential Analysis
Inferential analysis is the process of quantitatively summarizing data, determining which data patterns are significant, and making inferential statements about performance. Inferential statistics provide the tools necessary to identify critical factors and to what degree specific test results can be generalized. There are two main types of inferential statistics - hypothesis testing and regression analysis. The samples chosen in inferential statistics need to be representative of the entire population. In this article, we will learn more about inferential statistics, its types, examples, and see the important formulas.
5. Predictive Analysis
Predictive analysis is a type of data analysis which focuses on making predictions about the future based on data. It uses mathematical modeling tools to generate predictions about an unknown fact, characteristic, or event. Four common predictive models are linear regression. The linear regression model plots the data onto a 2-axis graph and calculates a line through the center of the plot that depicts the smallest distance between all plotted data points in a single dimension. Text mining is another model used by search engines to bring up relevant links or answers to a question. Optimal estimation is a modeling technique that is used to make predictions based on observed factors such as height, altitude, speed, and angle. Clustering models are focused on finding different groups with similar qualities or elements within the data. Neural networks are complex algorithms inspired by the structure of the human brain. They process historical and current data and identify complex relationships within the data to predict the future, similar to how the human brain can spot trends and patterns.
6. Prescriptive Analysis
Prescriptive analysis specifically factors information about possible situations or scenarios, available resources, past performance, and current performance, and suggests a course of action or strategy. It can be used to make decisions on any time horizon, from immediate to long-term. It is the opposite of descriptive analytics, which examines decisions and outcomes after the fact.
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