Studying applied statistics? Four top tools you’ll need to excel

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Whether you are just starting your applied statistics course or are looking for a better program for your current position, it’s always a good idea to stay on top of your software game.

Ultimately, when studying how to apply data to everyday problems and develop new solutions, you’re going to need more than a simple spreadsheet and a mind for math. For example, if you choose to study a Masters in Applied Statistics with Michigan Tech, you’ll be learning to use various complex correlating tools. But, how do you necessarily know which will provide you with the most actionable results in your given field?

Studying applied statistics? Four top tools you’ll need to excel

No matter where you intend to go with your degree, it’s an excellent idea to brush up on the wider software field. With that in mind, here are four vital software tools for those studying or performing applied statistics in their everyday career.

IBM SPSS Statistics

IBM SPSS Statistics is landmark software package that helps to provide extensive data to support informed decision-making at a fast pace. It’s built as an all-in-one suite for data managers. It’ll help to support you in preparing complex data through to presenting information in a variety of formats and styles.

For those analysts working extensively with how statistics can impact decision-making, SPSS can even perform both descriptive analytics and statistical simulations. Ultimately, IBM has fine-tuned its suite over the years to remove as many manual tasks from the data analyst’s desk as possible.  

SPSS can seamlessly gather data from various sources and file types, ranging from simple spreadsheets to dense ASCII text. It’s highly versatile.

IBM SPSS even provides an automated data preparation feature, which can find and identify missing or incorrect numbers. This ensures your reports are accurate and reliable — and there’s no need for you to painstakingly verify that there is no duplicated data. On top of this, SPSS can even make predictions based on data fed into its backend and help you to confidently forecast for the future.

Thanks to SPSS’ user-friendly interface, you do not have to worry about being a complete wizard with coding. It is highly intuitive, making it a true staple for any applied statistics student or professional. You’ll likely find this software is the ‘standard’ you’ll be working with when first studying applied statistics.

SAS 

SAS is a cloud-based data suite used by business analysts, data scientists, researchers, statisticians and engineers alike. This program deploys complex statistical models in the interest of predicting future trends. None of us can effectively predict the future, but SAS is well-known within the industry for its speed, accuracy and reliability. 

SAS includes graph publishing features, and for those who are just getting started, there’s a free e-course provided to help introduce you to the inner workings of the suite.

Despite its impressive setup and handy course, this software is not built for beginners. You will always need some knowledge of coding and statistical procedures. It is not the most intuitive data analytics software for beginners, so you will need a working knowledge of how to use its various commands, and what you intend to use it for.

That being said, it is an industry-standard software solution, so you’ll likely come across it in future settings. Whether you are using it in school or in a professional environment, SAS is definitely a program worth investing in. 

GraphPad Prism 

GraphPad Prism is specifically designed for scientific research and is a statistics and data analysis program. It is used professionally in all kinds of sciences, from biotechnology and automotive technology to pharmaceuticals and healthcare. 

The most appealing aspect of GraphPad Prism is that you do not need to be a coding genius to use it. It has been designed to be one of the most intuitive analytics suites on the market.

GraphPad Prism includes a wide range of statistical analysis parameters, including non-linear regression and nonparametric comparison. It can be used collaboratively between users too, allowing your colleagues to add information, commentary, research and more to the files that you share. 

GraphPad provides live updates, ensuring you’re always kept informed of any new changes to the data you’re preparing.

However, GraphPad does have its limitations. You won’t be able to create your own equations on a graph or layout of your own build. That being said, it is a commonly used program that has proven to be time and work-efficient, and is relied on cross-industry.

Minitab 

Minitab can provide visual demonstrations of data and its complex analyses. It is an ideal program for making informed and reliable decisions, regardless of whether you are training, or building strategies in a professional environment.

Minitab appeals to many people thanks to the fact that it is completely customizable. You can be sure your data is laid out in a way that suits you, even drilling down into how you set up your menu and interface. You can save time using the one-click importing feature too — something of an edge for this software over the broader competition.

If you’re working against the clock, you can also use the Quick Start option to learn how to use the program’s basic features, including full courses and exercises to follow at your own pace.

Your visualized data, such as probability plots, histograms, time series plots and scatterplots, will update live as the data changes, so there’s no need to worry about keeping up the pace. This is software that’s well-rated for its accuracy and flexibility too!

Conclusion 

Having the right tools for your Masters in Applied Statistics or any associated role is essential. Whether you’re considering getting into computer science or learning more about how statistics play a role in society’s broader problem-solving, it’s crucial to have both a plan of action and a selection of amazing software in your arsenal.

The above programs are by no means conclusive when it comes to available tools for data analytics. However, get to know them early, as you’ll likely come across them a lot!

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