Bmp statistical software

Instead of proceeding data in its raw form, descriptive statistics allows us to present and interpret data more easily. In contrast, inferential statistics allows analysts to test a hypothesis based on a sample of data from which they can make inferences and generalizations about the greater whole. Inferential statistics tries to make conclusions about future outcomes beyond the data available. For descriptive statistics, we choose a group to study, measure all the subjects in that group and describe the group in exact numbers.

Descriptive statistics can be helpful in looking into such things as the spread and center of the data, but because descriptive statistics are stated in exact numbers, they cannot be used to make broader generalizations or conclusions. For inferential statistics, we instead start by defining the target population and then plan how to obtain a representative sample.

After analyzing the sample and testing hypotheses based on the sample data, the result will be expressed in confidence intervals and margins of errors, based on the uncertainty of using a sample that cannot perfectly represent the population. Both kinds of statistics are at the heart of the statistical analysis that powers statistical software, used hand in hand to solve business problems with intelligence.

Statistical software can help with business intelligence in many different ways. Statistical analysis can give insight into how effectively your business is operating, and help you think ahead with predictive analytics models based on historical data. So what are the benefits of using a statistical analysis tool for business intelligence?

There are many factors to consider when choosing statistics software. Using a complicated advanced tool like statistical software for simple data sets is impractical; statistical analysis tools work best with complicated sets of quantitative data.

If your analysis needs are less demanding, a business analytics tool may be more suitable for you. Products tend to offer different ranges of statistical theorems and algorithms, but some users may only need to use a small percentage of these functions. If you have a massive amount of data to analyze, you may want to invest in a tool built to handle large data sets with speed.

You should look for a tool that performs exactly the kind of data analyses you need it to. Who will use the tool? Will your analysts be experts, amateurs, or somewhere in between? Will they analyze data continuously in real-time, or will they do more statistical analysis on an ad-hoc self-service basis? Are they primarily data analysts or scientists?

Your statistical analysis software should meet the needs of the person using it, so make sure to choose a package that does exactly what your user needs it to. Statistical analysis is by no means easy, and many statistical software platforms can be confusing and downright unintelligible to the average user.

Some tools also have a higher learning curve than others, making them more difficult to master. After considering who will be using the tool, determine what their level of experience with statistics is. Expert data scientists will feel at home crunching numbers with equations and programming languages, but novice users may feel overwhelmed with a software presented in that format and prefer using a more familiar menu-based interface.

Do your engineers need a robust statistical analysis platform with powerful coding capabilities, or do your analysts need a simpler statistical tool that can display basic models, or do you need something in between? Considering the interoperability and integration capabilities of prospective statistics software is an important step in the vetting process. While statistical software helps businesses derive deeper insights from their data, they are often just a cog in the machine of their technology ecosystems.

More frequently than not, your business may need more than just one solution to address its analytical needs. Will the new solution play well with others? If your business currently uses any other programs, it can be helpful to get a statistical analysis tool that supports the databases, file formats and frameworks of your existing solutions.

Some statistical packages are feature-packed with data visualization options, while others generate graphics that are much more bare-bones, with less customization available. Do you prefer interactive or static visualizations?

Will you need your statistical analysis software to produce visually appealing graphics outright? Statistical software packages range in price from free for open-source tools like Python and R, to thousands of dollars per license for more robust offerings. Will you need just one license, or several? There are also many statistical analysis platforms that have academic versions available to students and teachers at a discounted rate.

The cost of your solution will affect which statistical analysis software is best for your business. This database application is provided solely for the purposes of private study, scholarship, or research. Therefore, the information in this database is in the public domain for these purposes but may not be available for some commercial uses.

Because the database and related material are free and provided "as is," the authors, the USGS, the FHWA, and the United States Government are not obligated to provide users with any support, consulting, training, or assistance of any kind with regard to the use, operation, and performance of this database nor to provide users with any updates, revisions, new versions, or "bug fixes".

The use of trade or product names in this database is for identification purposes only and does not constitute endorsement by the U. This software has been approved for release by the U. Although the software has been subjected to rigorous review, the USGS reserves the right to update the software as needed pursuant to further analysis and review.

Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. Government shall be held liable for any damages resulting from its authorized or unauthorized use. ScienceBase WMS. JASP offers standard analysis procedures in both their classical and Bayesian form.

Read More. Nyenrode Business University www. Utrecht University Methods and Statistics www. University of Bern Department of Psychology www. University of Leuven www. European Research Council www. Official websites use. Share sensitive information only on official, secure websites. The U. Geological Survey developed SELDM and the statistics documented in this report in cooperation with the Federal Highway Administration to indicate the risk for stormwater flows, concentrations, and loads to exceed user-selected water-quality goals and the potential effectiveness of mitigation measures to reduce such risks.

In SELDM, three treatment variables—hydrograph extension, volume reduction, and water-quality treatment—are simulated by using the trapezoidal distribution and the rank correlation with the associated runoff variables.