Data Science

The world is producing more statistical information than ever before and many people feel over whelmed by it. It is important to know what information we should pay attention to, and what to do with these and how to use them.Since political, economic and other social conditions are rapidly changing, a researcher has to be equipped well to deal with them and use the appropriate tools with caution. This requires that the researcher has enough exposure and familiarity with different tools and techniques as the onus of selecting and implementing the right one rests with the researcher. In order to fulfil this responsibility, the researcher has to pay attention to every small details of the study, right from data collection, measurement of data, using the right tool for different types of data and making the correct inferences from the data using the correct and valid techniques of analysis. A very important aspect in this is that the researcher should become conversant with the available tools and the situations in which they can be used.

One of the major concerns of healthcare in the world today is HIV/AIDS.The health and socioeconomic consequences of a rapid spread of AIDS are very serious.Thus we need accurate forecasts of the future course of the epidemic.The special feature of AIDS is its long incubation period,whose distribution is difficult to estimate partly due to its length and partly due to its nature of the infected cohorts being followed or identified.This article mainly discusses the features of AIDS incubation period and reviews statistical analysis of a few models developed for the estimation of the incubation period.One of the i9mportant methods of projection namely,Back Calculation method is also discussed.

has been implementing a community based solid waste management initiative called 'Parivarthana Project', with the support of Global Communities. The project was initiated to undertake decentralized solid waste management which includes collection, sorting and sale of recyclables, composting and paper recycling. This project employs women from slum communities and involves around 2200 households were serviced in Rajendra Nagar and Ambedkar Nagar. Two sorting and composting centres have been established in collaboration with BBMP. In addition, occupational health, safety & saving insights through SHGs trainings are provided to BBMP waste collectors in 5 wards. Various initiatives are undertaken to educate, orient & create awareness along with improving the socio economic conditions of pourakarmikas. The major aspect in this project is community participation, involving students of Christ University, residents of slums, their children and others. This paper presents a description of this project which has been successful in making Christ University a zero waste campus.

This paper uses the concepts of milk runs as well as bin packing in order to optimize collection and reduce cost. Using the concept of “milk run” and an approach of time minimization, we can optimize the number of trucks and other vehicles used for picking and transporting waste. The objective function involves cost of transportation and is linked to distance travelled to dispose wastes. The constraints are those of vehicle capacity. The profile of different types of trucks obtained from milk run is used to compute number of trucks as well as to allot them to different trips.  

Improper and inefficient usage of energy in the country/state leads to unnecessary wastage of earth's resources. The electricity once generated cannot be stored efficiently. Thus, if excess of electricity is generated, it is wasted, if less of electricity is generated, there is shortage in the state leading to power cuts. Both situations lead to unwanted results. Successful modelling of the electricity generation can lead to effective usage of the infrastructure and the resources provided. It has environmental as well as monetary benefits. The paper will aim at understanding the dependencies of the electricity used. If we can understand these dependencies and the pattern followed in electricity usage (if found), the electricity generation and allocation can be modelled to meet the requirements as well as reduce the wastage of the resources. In countries like South Korea, North America, Europe and Japan, the electricity generation is planned and modelled which pushes us to follow...

Social Sciences studies human behaviour and it is very important that the conditions under which they occurred and also to describe the behaviour accurately and correctly. Thus it becomes important to have a "measure" of behaviour, description of all factors influencing behaviour and to what extent these influence such behaviour. They provide an opportunity for others to verify these observations. It is very important to present collected data in an accurate and easy-to-understand manner through various tools like diagrams and graphs. Every object possesses some characteristic which can be used as a scale for measurement. In the past, silver, food grains etc were used as units of measurement. concepts are large in number and part do not bear the kind of simple relationships to one another like in the physical sciences and there is a lack of strong mathematical theories against which to evaluate measurements in social sciences. A proper understanding of the scales of measurement which have to be used for different kinds of variables, is thus, an essential part of social sciences research. This paper focuses on some case studies in the usage of scales of measurement in social sciences research.

Unemployment is one of the growing economic concerns for a developing country like India, which has the world’s largest youth population. Young Indians face a lot of barriers due to poverty and lack of technical skills required to get into the right job. Though there are a lot of reforms in the education sector, gaining a stable position in the labor market is difficult. Most men in rural areas are now shifting to casual jobs rather than farming activities and women tend to be self-employed. This paper explores the trend in the unemployment rate from 2004 -2018. It provides an overall analysis of the unemployment rate among males and females, rural and urban areas, states and the union territories as well as the relationship between GSDP and unemployment. The paper provides a comparative analysis on the unemployment rate during the Covid-19 pandemic.

The Internet of Things (IoT) is the trendy and prominent term in the recent times with its wideranging applications in domains of medicine, science, military as well as domestic use. Despite its tremendous growth, privacy concerns plague IoT applications and have the potential to hamper the benefits derived from their usage. This paper carries out a statistical analysis of empirical data collected from users of IoT to assess their knowledge and awareness among users of IoT. The mode of study was through a questionnaire sent through Google forms to a selection of Indians living across the U.S. The place was chosen as some of the authors were in that country and also because its usage is more in the U.S. Many homes have extensive use of IoT, even if it's for simple operations like turning on/off electric bulbs. Privacy issues have also been a matter of concern as these devices are linked to the internet. The sample was chosen from judgment /convenience sampling. Only one member per family was asked to respond so that there is no overlap of the collected data. The respondents were asked about the privacy issues of using IOT devices and also if it bothered them to continue usage. The results depicted that not only were users aware of the privacy issues related to IoT, but they also expressed concerns over the same. Due to the convenience and ease of usage, it is highly unlikely that people will stop using these devices but definitely, the usage will be more guarded in the future.

Traditional survival analysis techniques focus on the occurrence of failures over the time. During analysis of such events, ignoring the related unobserved covariates or heterogeneity involved in data sample may leads us to adverse consequences. In this context, frailty models are the viable choice to investigate the effect of the unobserved covariates. In this article, we assume that frailty acts multiplicatively to hazard rate. We propose inverse Gaussian (IG) and generalized Lindley (GL) shared frailty models with generalized Weibull (GW) as baseline distribution in order to analyze the unobserved heterogeneity. To estimate the parameters in models, Bayesian paradigm of Markov Chain Monte Carlo technique has been proposed. Model selection criteria have been used for the comparison of models. Three different cancer data sets have been analyzed using the shared frailty models. Better models have been suggested for the data sets.