Statistical Data Analysis Services

Factor Analysis The analysis of variance is not a mathematical theorem, but rather a convenient method of arranging the arithmetic.- Ronald Fisher The inexpensive Factor Analysis is a prominent statistical tool to identify a lot of underlying dormant factors. For more than a century it is used in psychology and also in a wide variety of situations. Factor analysis explains correlations among multiple outcomes as a result of one or more factors.   As it attempts to represent a set of variables by a smaller number, it involves data reduction.   It explores unexplained factors that represent underlying concepts that cannot be adequately measured by a single variable.   It is most popular nowadays in survey research where the responses to each question represent an outcome.   It is because multiple questions are often related and the underlying factor may influence the subject responses. The reduction technique of factor analysis in reducing a large number of...

SEM using AMOS Structural Equation Modelling (SEM) is a widely used technique in statistics to primarily study relationships based on structures. It encompasses various models involving mathematics, statistical procedures etc. This technique is known to be extremely effective when it comes to measuring latent constructs. Many of us might be familiar with concepts like Multiple Regression Analysis and Factor Analysis , this in simple term, is a combination of these techniques. It is, in fact, a mere extension of the General Linear Model. You can test a bunch of regression techniques at the same time. Structural Equation Modelling includes a model that makes room for a lot of other statistical techniques such as path analysis, confirmatory factor analysis and latent growth modelling etc. This is impressive as SEM as a type of model covers many models that are both traditional and complex. It is also effective in the assessment of variance and Multiple Regression along with e...

We are in the age of big data . The frameworks like Hadoop have managed to solve the problem of data storage.  Data Science  is defined as a combination of various tools, algorithms, and machine learning principles to understand, analyze and process raw data to provide insights that can help organizations make informed decisions. Data science created quite a buzz among the tech-enthusiasts, especially after being deemed ‘the sexiest job of the 21 st  century’ by the Harvard business review. It is a systematic and scientific approach to gaining valuable insights from the deluge of data that began with the proliferation of smart devices and the internet of things. Data science is often closely associated with the concepts of  data mining services  and  big data analytics ; while the former is a broader term representing systematic processes involved in the knowledge extraction from any data, the latter two are specific processes involved in analysing...