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What Skills should a Statistician Have

What Skills should a Statistician Have
EXPECTED WAGE:
$72,610
Unemployment:
2.2%
Education:
Master's degree

Typically, statisticians require a master's degree in mathematics, statistics or a related quantitative field. Many use their bachelor's degree to gain entry level jobs. Most academic and research jobs require a Ph.D.

Education & Training

The majority of statisticians have degrees in the following: computer science, math, statistics, economics or some similar quantitative field. Those with a bachelor's degree in statistics commonly cover calculus, survey methodology, linear algebra, statistical theory, probability and experimental design.

Most universities and colleges advise students to take courses in physics, computer science, math and engineering. These foundation courses can prepare students to work in numerous industries. Coursework in physical science and engineering can be beneficial for statisticians working on improving productivity or in the manufacturing realm. A background in health sciences, chemistry and biology can be useful for testing agricultural items and pharmaceutical goods.

Since statisticians commonly work with data analysis software, any computer programming classes can be a huge asset.

Skills and Qualities that will Help

Analytical skills: Statisticians rely on statistical models and techniques to analyze copious amounts of data. They must comprehend computer programming languages and the right software packages to develop and design new models and techniques. It is necessary to be precise in their work.

Communication skills: Statisticians commonly propose solutions and work with individuals who do not have a broad knowledge of statistics or math. They must communicate clearly and present ideas and information in a way that others will comprehend.

Math skills: Statisticians rely on calculus, statistics and linear algebra to create analyses and models.

Problem-solving skills: Statisticians create techniques to solve issues with analysis and data collection including high non-response rates in order to draw meaningful conclusions.