scholarly journals A Study of Rural Entrepreneurship and their Problems in Marathwada

2021 ◽  
Vol 9 (4) ◽  
pp. 7-10
Author(s):  
Dasharath Kale
Keyword(s):  
Business Education ◽  
Online Data ◽  
Rural Entrepreneurship ◽  
Marketing Problems

This study was focus on the problems of rural entrepreneurs for increasing their business in Marathwada. The researcher has collected online data through Google from 150 respondents from Marathwada for the study during 2020-21. There are many reasons for decreasing entrepreneurship, but researchers think the main reason is that the youth should be aware of business education. The competition to do something new and better promotes entrepreneurship and there are many other reasons why Entrepreneurship is promoted. Rural entrepreneurs face many problems such as lack of skilled and managerial workforce, lack of infrastructural facilities for agri-business, marketing problems, lack of awareness regarding a career in agro-entrepreneurship, etc.

Critical and Future Trends in Data Mining

Data Mining ◽  
2011 ◽  
pp. 437-452 ◽  
Author(s):  
Jeffrey Hsu
Keyword(s):  
Data Mining ◽  
Business Education ◽  
Scientific Community ◽  
World Wide ◽  
Data Sources ◽  
Knowledge Discovery In Databases ◽  
Future Trends ◽  
Online Data ◽  
Usable Knowledge ◽  
The World

Every day, enormous amounts of information are generated from all sectors, whether it be business, education, the scientific community, the World Wide Web (WWW), or one of many readily available off-line and online data sources. From all of this, which represents a sizable repository of data and information, it is possible to generate worthwhile and usable knowledge. As a result, the field of Data Mining (DM) and knowledge discovery in databases (KDD) has grown in leaps and bounds and has shown great potential for the future (Han & Kamber, 2001). The purpose of this chapter is to survey many of the critical and future trends in the field of DM, with a focus on those which are thought to have the most promise and applicability to future DM applications.

Reliability of MTurk Data From Masters and Workers

2020 ◽  
Vol 41 (1) ◽  
pp. 30-36
Author(s):  
Steven V. Rouse
Keyword(s):  
Cognitive Abilities ◽  
Online Survey ◽  
Quality Data ◽  
Standard Samples ◽  
Online Data ◽  
Approval Ratings ◽  
Cognitive Abilities Test ◽  
Elite Status ◽  
Master Status ◽  
Amazon's Mechanical Turk

Abstract. Previous research has supported the use of Amazon’s Mechanical Turk (MTurk) for online data collection in individual differences research. Although MTurk Masters have reached an elite status because of strong approval ratings on previous tasks (and therefore gain higher payment for their work) no research has empirically examined whether researchers actually obtain higher quality data when they require that their MTurk Workers have Master status. In two different online survey studies (one using a personality test and one using a cognitive abilities test), the psychometric reliability of MTurk data was compared between a sample that required a Master qualification type and a sample that placed no status-level qualification requirement. In both studies, the Master samples failed to outperform the standard samples.

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