Competitive analysis: Statistical analysis illuminates your objective value as a company.Here are a few areas of statistical data analysis that keep your business practices sharp:
If your organization sells products or services, you should use statistical analysis often to check in on sales performance as well as to predict future outcomes and areas of weakness. Statistically analyzing your team is important, not only because it helps you to hold them accountable, but also because it ensures their performance is measured by unbiased numerical standards rather than opinions. It’s easy to collect this data, but to make meaning of it, you’ll want to statistically analyze the data to assess the performance of individuals, teams, and the company. For internal, or team metrics, you’ll want to measure data like associated deals and revenue, hours worked, trainings completed, and other meaningful numerical values. From this sample and the results of your experiment, you can use inferential statistics to infer conclusions about the rest of the data set.Įvery company has several key performance indicators (KPIs) to judge overall performance, and statistical data analysis is the primary strategy for finding those accurate metrics. In this type of statistical analysis, you are less focused on the entire collection of raw data and instead take a sample and test your hypothesis or first estimation. Statistical inference: Inferential statistics practices involve more upfront hypothesis and follow-up explanation than descriptive statistics.It is only the practice of digesting and summarizing raw data, so it can be better understood. Descriptive analysis isn’t about explaining or drawing conclusions, though. Descriptive statistical analysis focuses on creating a basic visual description of the data, or turning information into graphs, charts, and other visuals that help people understand the meaning of the values in the data set. Raw datadoesn’t mean much on its own, and the sheer quantity can be overwhelming to digest. Descriptive statistics: This type of statistical analysis is all about visuals.See more: What is Data Analysis? Types of statistical data analysisīefore you get started with statistical data analysis, you need two pieces in place: 1) a collection of raw data that you want to statistically analyze and 2) a predetermined method of analysis.ĭepending on the data you’re working with, the results you want, and how it is being presented, you may want to choose either of these two types of analysis: Use cases for statistical data analysis.See below to learn more about statistical data analysis and the tools that help you to get the most out of your data: Statistical Data Analysis Statistical data analysis is often applied to survey responses and observational data, but it can be applied to many other business metrics as well. Statistical data analysis does more work for your business intelligence (BI) than most other types of data analysis.Īlso known as descriptive analysis, statistical data analysis is a wide range of quantitative research practices in which you collect and analyze categorical data to find meaningful patterns and trends.