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...

Now, let us look at the topic of whether my research will be an inductive or deductive or you can say  qualitative  or  quantitative ? Well, the answer depends on the objective of the study and the type of research you conduct. If you want to validate an existing or a known theory, then your research is deductive. However, if you’re going to do  analytical research  or develop a new approach based on the  sample data , then it is inductive. In some situations, the study may be both deductive and inductive depending upon the  research problem  at hand and the complexity of the problem. In this blog, I will explain to you the difference, meaning of inductive and deductive research with examples, and it’s up to you to decide whether your study comes under the inductive or deductive category. The  statistical support services  offered inductive research with different types. Inductive Research Inductive research makes an inferenc...

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...

Posted by u/statswork just now What Approach Should I Take: Qualitative Or Quantitative – Statswork In practice, Data collection and Data Analysis involves two approaches: Qualitative and Quantitative approaches. Each approach has diverse kinds of objectives and statistical methodology.  Quantitative research Methodology  is useful in testing the assumptions and theories which are already Qualitative research is useful in understanding the concepts and formulating the theories.  Experimental research and surveys  are examples of quantitative research. Quantitative Research It focuses on testing the hypothesis we claim about the problem. Expressed by numbers, tables, and graphs Needs many observations The questionnaire should be in closed form i.e. with multiple-choice questions Qualitative Research It focuses on developing and formulating a hypothesis Expressed by words or text Needs a few observations The qu...

Harry is a pizza shop owner, and he’s perplexed to prefer a better location among two locations that he already shortlisted. He created up his mind to conduct a study to opt for the quintessential area. Location A is narrow, and he notices that there’s a high school two blocks away, some business offices accessible, and a Laundromat not far away. Location B is more extensive and next to a market with some business offices scattered around the space, amidst many vacant tons. If you were Harry, which might you choose? Mark Twain once quoted, “FACTS ARE STUBBORN THINGS, BUT  STATISTICS  ARE PLIABLE.” You are a  statistician  in many ways. Statistics is that the technique of conducting a study of a couple of specific topics by aggregation, organizing, decoding, and eventually presenting data. Statistics are used to analyze what’s happening within the world around us. In this data-driven world, all activities of ours are monitored by someone else every time. Statist...

In this blog, I will explain to you how the  statistical analysis  is being applied for two independent samples. In practice, the test statistic used for comparing the two means from a population is by using the  t-test  because t-test shrinks the data to a single t-value and it is then compared with the significant value for the final conclusion. Now, let us understand the theoretical background in performing the t-test for two variables. Suppose X1 and X2 be the two independent random variables and let, be the sample with size n1 and n2 from a population with mean µ1, µ2 and variance σ12, σ22 respectively. Understanding the Problem Statement The primary or basic task in any  statistical data analysis  is to know or find out what the problem is and how the data is being measured. Construction of Test Hypotheses Once you understand the problem at hand, the next step is to frame an appropriate hypothesis to test for  statistical s...

The clustering technique in  Statistical Analysis  is used to determine the subsets as clusters in the data using the specified distance measure. However, this technique cannot be applied easily for longitudinal or time-series data. In this blog, I will discuss some of the methods used for modeling longitudinal or panel data using the  Clustering Analysis  technique as explained in Schmatter (2011). Longitudinal data is actually a sample of observations which are measured repeatedly over time. And, nowadays, longitudinal/repeated measure data or panel data exists in all areas of  Applied statistics  such as finance, psychology, economics, and social sciences. Most studies deals with analyzing homogeneity in such  Time series data  (Diggle et al 2002), however, there are few researchers’ shows interest in analyzing the heterogeneity in such data and they proposed different modeling technique for the same. Let us now discuss the applicabilit...