This section provides an overview for multivariate analysis software as well as their applications and principles. Also, please take a look at the list of 5 multivariate analysis software manufacturers and their company rankings. Here are the top-ranked multivariate analysis software companies as of February, 2024: 1.Minitab, LLC, 2.OriginLab Corporation, 3.NCSS, LLC.
1993~2019: Engaged in pharmaceutical research and development and analysis of various biological samples at the Pharmaceutical Research Institute of Japan Kayaku Co., Ltd. He is also in charge of facility management as a dangerous goods handler and radiation handling chief.
2019: Moved to another company in the same industry and has been in charge of similar work until now.
He also writes, translates, and edits specialized books.
Multivariate analysis software is software that is equipped with algorithms and tools capable of performing multivariate analysis. In general, it refers to software that allows users to obtain analysis results easily by allowing the computer to handle the complex process of difficult mathematical formulas by selecting analysis methods on the software, without having to program the software themselves.
Multivariate analysis software is equipped with algorithms for various multivariate analysis methods, such as principal component analysis, multiple regression analysis, and logistic regression analysis. Multivariate analysis software is used in fields ranging from research and development to manufacturing, where it handles vast amounts of data and can identify important factors from many factors, infer causal relationships, and make predictions based on background information.
It can handle time series data, quantitative data, and categorical data, and can perform these analyses. The fields in which it is used are diverse, ranging from medicine, pharmacy, and chemistry to manufacturing and marketing.
Multivariate analysis software is used in fields that deal with data from a variety of industries and uses analysis methods that are better suited to the purpose and use of the data. The uses of each analysis method are as follows:
In principal component analysis, multivariate data are aggregated into two dimensions (first and second principal components), and a two-dimensional plot shows the scatter of the data. By aggregating the data into two dimensions that can be intuitively grasped by humans, the characteristics of the data can be easily grasped. It is also used to detect outliers based on the observation of scattering.
Cluster analysis groups objects as clusters by measuring the distance between individual objects represented by multiple factors. For example, it is used to group respondents into clusters by measuring the distance between groups of responses or groups of questions based on survey responses.
Multiple regression analysis is a method of making predictions using multiple explanatory variables for a single numerical objective. For example, it is used to forecast sales by estimating the impact of each factor based on the hypothesis that there are many factors that affect sales.
Structural equation modeling has been attracting attention in recent years, although it is viewed in a slightly different way from the individual analysis techniques introduced so far. Structural equation modeling, also called covariance structure analysis, is an integrated term for analytical methods that uses covariance to estimate the structure behind data.
Individually realized analysis methods include multiple regression analysis, factor analysis, and path analysis. In particular, path analysis, a method for estimating causal relationships, such as what factors surrounding the respondents are likely to lead to what behaviors, from the results of a multi-item questionnaire, is attracting attention.
As illustrated in the previous section, this method is used to analyze trends in survey results and to examine sales strategies, and is used in marketing and social science research. Also, in scientific research, the results of multi-component chemical analysis may be used to classify the subject of analysis.
For example, chemical analysis of industrial products can be used to estimate the dissimilarity of products, and component analysis of vegetables can be used to estimate their place of origin. It is also possible to group the characteristics of numerous products from different manufacturers. This type of application in the field of chemical analysis is called chemo metrics, and its use has been increasing in recent years.
Multivariate analysis software contains the calculation algorithms necessary to perform multivariate analysis as an internal program. Many software packages provide an excellent graphical user interface (GUI), allowing the user to input the necessary data, select the analysis to be performed, and the computer handles the entire complex process and produces the analysis results.
Different analyses can be performed on different sets of data with the click of a mouse. These features are very different from the user's own algorithm programming method.
It is recommended that you try out multivariate analysis software before purchasing it. This is because multivariate analysis is a field that is advancing year by year, and there is a large difference between different software.
When selecting multivariate analysis software, the two most important factors to consider are whether it can do what you want to achieve and whether it is easy to use. In addition, as software has become more complex in recent years, an increasing number of vendors are offering paid maintenance services.
In addition to maintenance, many analysis softwares offer a set of operational troubleshooting and user training. In this case, it is advisable to determine whether technical assistance is required based on the feel of the trial.
Multivariate analysis software packages do not require users to know the specific calculation methods themselves. In recent years, many program codes for multivariate analysis have been made publicly available, but the advantage of packaged software is that the user does not need to have any programming knowledge to perform the analysis.
However, even when using packaged software, it is at least necessary to have knowledge of the structure of the data, the significance of the analysis, and the selection of the analysis method that best suits the purpose. Some vendors provide user training on these topics. You may want to consider taking advantage of such training to promote user understanding.
*Including some distributors, etc.
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Hitachi High Tech was established in April 1947 and operates in 26 countries with products and services ranging from semiconductor manufacturing equipment and Medical and Biosystems to Analytical Systems and Manufacturing related equipment and solutions. A unique state-of-the-art technology company with two functions as a manufacturer and a trading company with the motto of "Tackling social issues," the Hitachi High-Tech Group aspires to be a company that pursues not only economic value, such as revenue and profit, but also provides social and environmental value by contributing to resolving social issues through its business activities, including products and services. They also provide one-stop services, such as evaluations and analysis at a global level.
Sartorius AG, started in 1870 and headquartered in Göttingen, Germany, is a manufacturer and supplier of lab products and bioprocess solutions. It is the parent company of the Sartorius Group and provides instruments, consumables, and services for chemical, biopharmaceutical, and academic set-ups. The company sells its products under several brand names, such as Cubis, Ambr, and Flexsafe, and provides services like bioprocess consulting, biologics testing, and instrument service. It is available in over 60 countries and is listed on the Frankfurt Stock Exchange with preference and ordinary shares. It operates two divisions, namely bioprocess solutions and lab products and services.
*Including some distributors, etc.
*Including some distributors, etc.
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