7 Types of Statistical Analysis Techniques

Prescriptive analysis
Prescriptive analysis helps organizations use data to guide their decision-making process. Companies can use tools such as graph analysis, algorithms, machine learning and simulation for this type of analysis. Prescriptive analysis helps businesses make the best choice from several alternative courses of action.
Related: How Analyzing Data Can Improve Decision-Making
Exploratory data analysis
Exploratory data analysis is a technique data scientists use to identify patterns and trends in a data set. They can also use it to determine relationships among samples in a population, validate assumptions, test hypotheses and find missing data points. Companies can use exploratory data analysis to make insights based on data and validate data for errors.
Causal analysis
Causal analysis uses data to determine causation or why things happen the way they do. It is an integral part of quality assurance, accident investigation and other activities that aim to find the underlying factors that led to an event. Companies can use causal analysis to understand the reasons for an event and use this understanding to guide future decisions.
Statistical analysis process
There are five major steps involved in the statistical analysis process:
1. Data collection
The first step in statistical analysis is data collection. You can collect data through primary or secondary sources such as surveys, customer relationship management software, online quizzes, financial reports and marketing automation tools. To ensure the data is viable, you can choose data from a sample that's representative of a population. For example, a company might collect data from previous customers to understand buyer behaviors.
2. Data organization
The next step after data collection is data organization. Also known as data cleaning, this stage involves identifying and removing duplicate data and inconsistencies that may prevent you from getting an accurate analysis. This step is important because it can help companies ensure their data and the conclusions they draw from the analysis are correct.