This paper is formulated towards that of regression analysis use in the business world. The article used for this paper was written in order to understand the meaning of regression as a measurement tool and how the tool uses past business data for the purpose of future business economics. The research mentioned in this article pertained to quantile regression, or how percentiles of specific data are used in estimating that of future possibilities in data.
The hypothesis to the study of quantile regression showed that regression analysis in the business world may not give a complete picture of how data is distributed, but rather a curve or educated guess. The main findings of the study where used in order to persuade those involved in economic development to continue exploring the means of refining quantile regression so that it can be used as an extensive strategy in completing that of regression in the business world.
The gender pay gap in Vietnam, 1993–2002: A quantile regression approach The purpose of the study is to investigate the gender pay gap between men and woman between 1993 and 2002 in Vietnam. The research questions where what is causing the gap and why are men paid significantly more than women. The hypothesis of the study is a “glass ceiling” effect the reason why the women are paid so little. The main findings of the study are women in some instances make more money at being self-employed. There are no specific reasons for the gap but since 2002 it has been closing gradually.
The Essay on Business Intelligence and Data Warehousing as a Solution
As it is anticipated that there is a fundamental objective of the company to reduce costs, make informed decisions and consolidate information, there is urgent need to for resilient development of the business intelligence and data warehousing (Collier, 2012). The poor response by IT in the provision of strategic information indicates that the system is incapable of guiding the company to success. ...
Ordinal Regression Analysis The purpose of an ordinal regression analysis is to determine the difference and significance of existing ordinal values on a scale that ranges from low to high inclusive of below average, average, and above average. Which Presidential Candidate would be the best person for the United States? Which method of medical treatment is the best cure for this patient? The research question can vary based on the topic; however, the hypothesis represents the results that are calculated by the ordinal regression analysis.
For example, “Ordinal regression is often used to analyze ordered response or pseudo-continuous response data, such as the determinants of the likelihood of voting for a candidate in congressional voting, determinants of quality of life for patients receiving a particular therapy, or a host of other topics” (China and World Economy, 2003).
The main findings of an ordinal regression analysis is to estimate the positive and negative range of ordinal numbers relative to a specified topic, which can be used to determine the best candidate, method of medical treatment, or a host of other topics.
Risk Analysis Using Regression Quintiles The purpose of the study was to study risk management based on quantile regression. Regression quantile methods offer a mechanism for estimating models for the conditional median function, and the full range of other conditional quantile functions. The questions asked in this paper is if the writers can use quantile regression analysis to better predict value-at-risk (VaR).
The hypothesis of the paper is “This model has the advantage of computational convenience, as well as the robustness properties of the quantile regression method.
The estimation procedure can be easily implemented on a regular personal computer (Guo, Lam, & Xiao, 2012. )” The paper finds that the quantile regression analysis is more robust than other risk metrics. The paper also notes that future research is necessary to ensure accuracy of estimation. Inflation and central bank Independence: A Meta-Regression Analysis The purpose of this study is to determine if inflation has an effect on central bank independence (CBI).
The Essay on Regression Analysis Does Dropping Out Of School Impact The Rate Of Violent Crimes
Regression Analysis-- Does Dropping out of School Impact the Rate of Violent Crimes The rate of school dropouts and the rate of violent crimes in U.S. were being suspected to have correlation since long time ago. Yet, up until recently, only the psychological methodology was being used to establish a link between these two social problems. Applying mathematical research to deal with the issue, was ...
Some of the research questions asked were “To what extent has the literature confirmed that there is a negative association between CBI and inflation?
and Can we explain the pattern in the results of empirical research on the relationship between CBI and inflation” (De Haan and Klomp, 2010)? According to De Haan and Klomp (2010), the hypothesis is that “CBI and inflation are negatively related” (p. 595).
The main findings of the article are in some industrial countries’ economies the turnover rate of central bank governors positively correlates to the countries’ inflation rate. This means if the turnover rate is high, CBI seems to be lower and inflation higher. ?
