Statistical Data Analysis Services

In every  research studies , the scientist wants to identify the truth or they wish to develop meaningful insights into the problem. In order to make any valid conclusion about the  research problem or hypothesis , we need valid evidence. Moreover, the evidence can be represented by  collecting data  (numeric or non-numeric in nature). In any  statistical analysis ,   data collection  is the fundamental step and there are two forms of data collection;  Primary and Secondary method  of data collection. I will describe you the meaning of primary data, examples of primary data collection and different ways of collecting the same. Primary Data: The researcher collected the Primary data through surveys, experiments, interviews, etc, and it is considered to be the  best research methodology   as the data are collected from the original source. However, before collecting the primary data, the main task of the researcher is to identif...

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...

In Brief: Today online social media platforms such as Twitter, Facebook or Youtube shield a big share of the wide-ranging digital communication. Different software tools allow the assembling of information about users and the collection of data about their communication behavior. Mainly, the microblog Twitter provides manifold opportunities in Data Analysis to its functionality and the availability of appropriate software. A critical review on Using Twitter as a data source: an overview of social media research tools (2019)   by Wasim Ahmed . Research by Wasim Ahmed (2019) presented an influence on the latest developments in digital methods, methodologies for researching Twitter and other social media platforms. Ahmed gives an overview of the main trends in research methodology, especially how to use Twitter data efficiently in given a multitude of methodologies . Overview of research methods In searching for the role of the participants...

Professional statistical  Data Analysis Services  are able to meet the requirements of any customer. We'll help  Statistics Services  you to collect, analyze, interpret all the data you need. Methodology can be defined as the rationale for the methods used in each study.“ Methodologies ” refer to the overall approach to the research process, from the theoretical underpinning to the collection and analysis of data.  Statswork  i s a pioneer statistical consulting company providing full assistance to researchers and scholars. Statswork offers expert consulting assistance and enhancing researchers by our distinct statistical process and communication throughout the research process with us. Contact Us: Website: www.statswork.com Email: info@statswork.com UnitedKingdom: +44-1143520021 India: +91-4448137070 WhatsApp: +91-8754446690

COMPARISON OF MULTILEVEL MODEL AND ITS STATISTICAL DIAGNOSTICS Diagnostics in Statistical Analysis is atmost important because there may be few influential observations which may distort the inference of the problem statement at hand. It is to be noted that all influential observations are not outliers, but some outliers are influential. In this blog, I will point out few standard statistical diagnostics in multilevel data. Multilevel data and its diagnostics Multi-level models are the statistical models of parameters (like in usual linear regression model) that vary at more than one level. It is also referred with many terms, namely, mixed-effect models, random effect model, hierarchical models and many more. In recent times, with the advent of statistical software and computations, multi-level or hierarchical models are widely used for longitudinal repeated measures analysis and in many meta data applications. Multi-level models could also applicable for non-linear case too ...