Statistical Data Analysis Services

Structural equation modeling  (SEM) becomes a major statistical technique in examining complex research problems in marketing and  international business . In most research, the SEM uses covariance-based modelling and later few researchers argued to use the partial least square approach for SEM. In this blog, a critical review of the SEM technique presented in Richter et al (2014) is discussed with application to the business sector. SEM Study (SEM Using AMOS) Six journals related to  business management  and marketing have been considered and the articles related to SEM has been scrutinized for this purpose. After the classification of methods used, it is found that 379 articles used covariance-based SEM and 45 used partial least square based SEM. Researchers are often interested in finding the same results by using these both methods of Structural equation modelling. However, the consistency of the partial least square method or the development of a n...

In modern years, there is a growing demand in the field of  business analytics . It actually means that what outcome we should get in business from the data to make better decisions. This is often sound like relating a business problem to an operation research problem. However, there is often a question that arises in connecting the business analytics to the operation research problem. In this blog, I will explain to you the meaning of business analytics and how it is related and useful in the operation  research methods  or decision making including linear programming, inventory management, simulation, and Markov Chains. Analytics are used to identify (i) what has happened? (ii) What should happen? And (iii) what will happen? In the business. These three forms of question are categorized into  Descriptive, Prescriptive and Predictive analytics  respectively. Apart from the benefits and uses of business analytics, the main goal of business analytics is to i...

Fraudsters are solely turning into smarter. It’s never excellent news once a client finds out there have been unauthorized transactions on their MasterCard. Once after the initial shock, the first move most customers come up is to report the bank about the fraud. But what happens next? Financial establishments require comprehensive analytics to make a robust bank fraud detection strategy.  Advanced Analytics  computer code provides the tools necessary for banks to acknowledge and act on suspicious patterns, quickly give notice customers of fraud incidents and position themselves for quicker settlements. Few examples of fraud that happen in banking: • Corruption • Cash Fraud • Billing Fraud • Check Tampering Fraud • Skimming • Larceny • Financial Statement Fraud Data Analytics  will keep a thorough analysis of information and appearance for patterns that indicate potential fraud. For example: • Customers with a deposit, checking, MasterCard and private loan acc...

In Brief: With the combination of math,  statistics , and computer science,  big data analysis  and ML algorithms are becoming more and more computationally emphasized. Google Trends data can aid in advance in forecasts of the current level of activity for several different economic time series. Google Trend  is presently one of the most common analytics tools noted by numerous studies and applying by policymaker units. There are many details behind such as timeliness, a broad range of relevant study fields, user interface, and free data access. Encouraged by advances in computing power,  ML  methods have recently been anticipated as substitutes to time-series regression models typically used by World banks  for predicting main economic variables . The ML models are particularly suitable for handling large datasets when the number of possible regressions is more significant than that of existing explanations. Continue Reading:   h...