Informatics Publishing Limited

Kamakshaiah Musunuru ¹

Affiliations
1 Business Analytics, Dhruva College of Management, Hyderabad, IN

Abstract

R is not only a statistical suite but also efficient data mining software for data manipulation, calculation and graphical display. In fact, R being a language also has an effective data handling and storage facility. Besides having a suite of operators for calculations on arrays, in particular matrices. The R is developed from a simple and effective programming language (called “S”) which includes conditionals, loops; user defined recursive functions and input and output facilities. Methods: In this paper the data mining capabilities of R has been explained with the help of a study on secondary data sources, obtained from certain authenticated sources. The study is all about to understand stress with respect to certain other factors like heavy drinking, perceived health and life satisfaction. As it mentioned the data so used is secondary in nature, which is in its crude from having no sense to the user. But by a systematic execution of certain data mining tools, like correlation and MANOVA, certain important relationships along with ties were realized. Conclusions: The realizations were that all variables are strictly correlated with Karl Pearson correlation coefficient ranging from 0.73 to 0.99. In significant test all variables do not belie with alternative hypothesis, which means the association/ relationship is not zero. In MANOVA, the null hypothesis is rejected as the p-value is less than 0.05. Apart from this, most interestingly the variables are behaving like cohorts whereby resulting cohort effect.

Keywords

R Language, Rstudio, Secondary Data, Data Mining, Correlation, Manova

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Kamakshaiah Musunuru ¹

Affiliations
1 GSIB - GITAM University, Rushikonda, Visakhapatnam, Andhra Pradesh, IN

Abstract

The effect of poor and unhygienic water on health is a pandemic problem across many nations. As per the estimations, approximately 37.7 million Indians are suffering from waterborne diseases annually; diarrhea is observed to be worst illness that is causing huge child mortality. The bad sanitation and hygiene also affects poor productivity which in turn cripples the economy. The economic burden due to poor sanitation and unhygienic drinking water is estimated at $600 million a year. 700 million people residing in rural India comprise more than about 1.42 million habitations spread over 15 diverse ecological regions. In fact, providing drinking water to such a large population is an enormous challenge. Hence, in this very context, a study have been undertaken so as to study and visualise the global water consumption and improved sanitation facilities to know about India's predicament in comparison to other countries. Certain powerful statistical tools like principal component analysis and itemised cluster analysis were employed to realise the study objectives. The countries were identified in certain important groups lying in similar situation with respect to sanitations and hygiene drinking water facilities. Most importantly the α (chronbach alpha) and β (factor saturation) are very fair to the clusters identified, whereby, affirming that the study variables, i.e. both urban and rural populations with respect to sanitation facilities and availability of hygiene drinking water could strongly characterise the countries under study.

Keywords

Sanitations Facilities, Hygiene Drinking Water, Public Health, Urban and Rural Populations.

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Kamakshaiah Musunuru ¹, Venugopal Reddi ²

Affiliations
1 GITAM School of International Business, GITAM University, Gandhi Nagar, Rushikonda, Visakhapatnam, Andhra Pradesh, IN
2 GITAM Institute of Management, GITAM University, Gandhi Nagar, Rushikonda, Visakhapatnam, Andhra Pradesh, IN

Abstract

Background: Healthcare industry in India is growing at a tremendous pace owing to its strengthening coverage, services, and increasing expenditure by public as well as private players. Healthcare outfits as organizations pretty much depend on patient admissions. So ultimately, this brings emphasis on importance of the healthcare consumers and impact of their behavior on hospital’s performance. This paper seeks to find out (1) impact of socioeconomic profile of the patients on service quality perception, (2) impact of service quality perception on patient’s behavior, and (3) assess the usability of such impact to formulate healthcare strategy. This study is basically an exploratory cum causal research, which attempts to explore certain relationships between socioeconomic characteristics versus behavioral characteristics of patients. The data were collected from 800 small and medium private clinics where competition is stringent. The resultant data assumed to be related to three constructs viz. socioeconomic profile, service quality perception, and patient’s behavior. There are 13 variables in the dataset. Study used reliability analysis to evaluate the internal consistency in the data. Factor analysis together with structural equation modeling was used to evaluate study constructs. Certain socioeconomic characteristics are significant towards certain service quality dimensions. There is also certain level of evidence in support of study proposition that patient’s satisfaction and attitude depends on their perception of service quality. The hospitals as healthcare organizations can make use of the impact of socioeconomic profile of patients while strategizing care so that it impacts patient’s service quality perception. More specifically, while strategizing patient’s perception of accuracy, the hospitals can make use of entire socioeconomic makeup as a single construct.

Keywords

Service Quality, Healthcare Service, Patient’s Perception, Patient’s Attitude, Patient’s Satisfaction.

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Kamakshaiah Musunuru ¹, S. S. Prasada Rao ²

Affiliations
1 GITAM School of International Business, GITAM University, Visakhapatnam, Andhra Pradesh, IN
2 GITAM Institute of Management, GITAM University, Visakhapatnam, Andhra Pradesh, IN

Abstract

The goal of this research is to study the performance of foreign exchange trade in both India and China. India and China raised rapidly in recent times and there is abundant of speculation that these countries might reach to the level of few other developed nations as far as international trade is concerned. Whereas there isn’t any doubt that these countries emerging as economic powers in the Asia-Pacific region, a lot of effort is required at international platform with respect to trade and commerce. One of such areas of competition is international currency trade. The aim of this study is to understand trends of currency trade in order to predict how likely these countries are going to emerge as best in the region. The study used certain secondary datasets from very reliable and authenticated sources. As far as statistical techniques are concerned, random walk forecasting methods were employed to test the study hypothesis. The study gathered certain evidence that though there are similarities in present and past performance, it is not likely to be the same in the future. However, the study concludes that random forests forecasting as a methodology is highly useful in studying trends in the data.

Keywords

Asia-Pacific Region, Currency Trade, International Trade, Random Walk Forecasting, Time Series Analysis.

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