How To Choose Statistical Tests

How To Choose Statistical Tests To Use in your Dissertation or Capstone Project

Are you a nursing student worried how you will analyze data for your DNP capstone project or dissertation paper? We would like to present to you a comprehensive tutorial on how to choose statistical tests for your dissertation project. In case you get stuck feel free to consult our SPSS data analysis help service

Most people can handle descriptive statistics without issues. But when it comes to inferential statistics, few people exude total confidence. But with the right statistical tests , inferential statistics does get a little easier. This post explains how to choose statistical tests that deliver high-quality findings.

Statistical analysis and testing are somewhat complex but very useful processes. They help researchers and analysts convert tons of raw data into useful information. If you don’t have a grasp of these procedures, you likely won’t see great results.

Before you dive into how to choose statistical tests for your study, study the distribution of your data. You also should spend some time extracting descriptive statistics from the data. In other words, you should calculate the mode, median, and mean. Doing that does make drawing inferences from your data somewhat easier.

What Factors Determine Which Tests You Should Select?

There are a plethora of statistical tests out there. Unsurprisingly, choosing the most fitting statistical test (s) for your research is a daunting task.

Three factors determine the kind of statistical test(s) you should select. These are the nature and distribution of your data, the research design, and the number and type of variables.

Here’s a little general advice on picking statistical tests. If your data is “normally distributed,” it’s best to use parametric tests. But if your data isn’t normally distributed (“non-normal” data), you should go with non-parametric tests.

9 Common Statistical Tests and How to Pick the Right One

Before you pick any particular statistical test, ask yourself: what do I want to do with my data? What do I want to know? After that, pick the statistical test that’s designed specifically to support the execution of that action.

Here’s a list of common statistical tests and what they’re best for so you can pick the best bet for your analysis.

Sign tests

Use the sign statistical test to study the difference between two related variables. This statistical test pays little attention to the magnitude of change in the difference (if any). However, the test factors in the direction of the difference between the variables in question.

Wilcoxon rank sum test

The test focuses on the difference between two variables that are independent of each other. It takes into consideration both the direction and magnitude of the difference between the variables.

Wilcoxon sign rank test

The Wilcoxon sign rank test is used to test the difference between two related variables.


This statistical test helps data analysts to test the difference between group means. Note: You shouldn’t run ANOVA before you’ve accounted for all variances in the outcome variable.

Paired T-test

The Paired T-test helps analyze the difference between the means of two related variables.

Independent T-test

The Independent T-test is the exact opposite of the Paired T-test. This test deepens the analyst’s understanding of the difference between the means of two independent variables.

Pearson correlation test

The Pearson test is a correlational statistical test. It enables you to accurately determine if any statistical association exists between two continuous variables.

Spearman correlation Test

The test is similar to the Pearson correlation test in that it’s a correlational statistical test. The test helps you to describe the association existing between two ordinal variables.

Chi-Square test

The Chi-Square test measures the strength of the association that exists between two categorical variables.

Multiple regression test

The test tracks how change in multiple predictor variables (2 or more) predicts change in the outcome variable.

Single regression test

The test tracks how change in one variable (predictor variable) predicts change in another variable (outcome variable).

You now know what each of 11 common statistical tests measure. At this point, picking the right test for your study should be pretty easy.

Statistical Tests For Inferential Analysis

You’ve learned what various statistical tests do. Which means you can easily know how to choose statistical tests that are suitable for your research. But you probably haven’t mastered any of the tests, have you? Obviously, you can’t leverage the power of any of the statistical tests if you don’t know how they work. Also, you should learn how to use statistical analysis software packages such as SPSS and MATLAB work. That’s because statistical tests and statistical software work hand in hand.

Infographic on how to choose statistical tests

how to choose statistical tests


Video on how to choose statistical tests


Statistics Major Job Opportunities

Why Study A Major In Statistics?

Hot Careers and Future Job Outlook for Statisticians

statistics major job opportunitiesIf you’re a data geek, you’re assured of job security, at least for the next one decade. For the last 15 years, there has been an increasing demand for statisticians. According to BLS (The Bureau of Labor Statistics), this growth is not about to relent.

BLS projects that from 2016 to 2026, employment for statisticians will grow by 34%. This is huge compared to the 28% growth in mathematical science occupations and 7% in all occupations. Statistician’s rank 9Th on the list prepared by Labor department of 20 fastest growing occupations.

Out of the 10 jobs BLS forecasts to grow fastest in the next decade, it’s only app developer and statistician that are not in the healthcare field.

What is fueling the growth?

There is a growing appreciation of statistics – The science of gleaning insights from data, and measuring, understanding, and controlling uncertainty – by governments, nonprofit organizations and businesses.

With the web and the ever-growing computing power, the world is producing more and more data that can be used to generate scientific and business insights. This increased availability of data is fueling the need for more data geeks – numbers won’t crunch themselves.

By 2025, IDC, a research firm, expects the amount of data created yearly to be 10 times more than the data created in 2016. That makes ‘statistical analysis and data analysis’ one of the hottest skills to have. And according to Linkedin, it’s the second most important skill that employers are looking for in 2018.

Increasing wages

The huge demand for data experts has led to a surge in wages for statisticians. Based on BLS data, between 2000 and 2014, statisticians’ mean wage grew by 12%. For most workers, wages in this period either dropped or stagnated.

By 2016, the median annual income for statisticians was $80,000, and it’s growing. Students are noticing. Between 2015 and 2016, the number of undergraduates in the US majoring in statistics rose by 19%. But according to American Statistical Association, the rise is hardly enough to meet employer’s demand.

Expanding university statistics programs

Universities are also responding to the increasing demand for data experts by expanding their statistics programs. Between 2003 and 2014, the number of universities offering degrees in statistics went up by 50% for undergraduate programs, and 20% percent for masters programs. There was an even bigger growth in master’s and doctorate programs, between 2000 and 2014, the number of programs increased by 160% and 130% respectively.

Also, several universities, for instance, the University of Washington, Kennesaw State University, the University of Michigan, the University of California, and the University of Washington, have now established Data Science programs.

Hot Career Opportunities For Statisticians

The job growth for statisticians is impressive, but still, it under reports the number of opportunities available to data experts. Jobs such as market research analyst, data scientist, and actuary, demand proficiency in statistics. Hundreds of thousands of statisticians work in this jobs.

Here is a list of career opportunities in statistics

Market Research Analyst

Market research analysts use specialized software to analyze ‘market data’. They gather and break down complex data on consumers, competitors, and market conditions. Their role is to take difficult data sets and translate them into easily understandable graphs, tables, and reports that can be used by people with little expertise in statistics.

Data comes from a myriad of areas, including interviews, web analytics, surveys, and literature reviews. To become an analyst, you need a bachelor’s degree, but some positions require a master degree.


A statistician’s job is to prevent inaccuracy in the interpretation of data. Statisticians design surveys, experiments, and questions. They then gather data through various methods for analysis and observation. After careful analysis, they present findings in an easily understandable form. Statisticians also explore new ways of collecting data.

Thanks to the massive amount of data that’s now available to organizations, there is an ever-growing need for statisticians.

Brand Optimization Analysts

Like all statistics-driven careers, brand optimization analysts study data and examine trends. Once they’ve noted trends, analysts suggest changes to business goals and develop strategies to maximize the reach of their brands.

To get into this career, you need a bachelor’s in finance, mathematics, marketing, economics, statistics or computer science.

Operations research analyst

list of careers in statisticsOperation research analysis taps into information from every aspect a business: sales data, customer feedback, web analytics, and computer databases. The analysts then use statistical tools to analyze this information and craft solutions for key decision makers.

A collaboration between the management team and operation research analysts is key to keeping a business profitable and functional. At the entry level, you can get in with a bachelor’s, but senior positions require a master’s degree.

Data Scientist

Data scientists dig through data looking for trends that point to the ‘next big thing.’ To become a data scientist, you need data gathering and analysis skills. Businesses use data science to develop and launch new offerings.

To get into this career, you need a bachelor’s degree, in math, statistics, physics, engineering, or computer science.

Financial analyst

Financial analysts focus on evaluating of past and present financial data. They look into business and economic trends and work with company officials to project the company’s financial future. Analysts typically specialize in industries, types of products or world regions.

To get into an advanced position, you need a master’s degree, but there are opportunities even you have a bachelor’s degree.


data analysis helpA biometrician’s job is to study trends that point to the probability of phenomena or specific conditions occurring. Their findings bolster quality control in field projects as they allow colleagues to anticipate and plan for various scenarios.

To become a biometrician, you need a master’s degree in zoology, wildlife biology, ecology or statistics.

Data scientist or statisticians combine math skills and excellent computer skills to gather and analyze data, with which they craft accurate and insightful reports that businesses use to develop plans and achieve goals. Employment opportunities are plentiful in multiple industries, providing data experts with lucrative, challenging and rewarding careers.

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