Statistics Project Work Essay Example | Topics and Well Written Essays - 1250 words

Statistics Project Work - Essay Example 2 Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients t Sig. 95% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 19.212 2.953 6.505 .000 12.981 25.443 GDP per Capita 7.072E-05 .000 .243 1.028 .318 .000 .000 Price Inflation .103 .401 .061 .258 .800 -.742 .949 a Dependent Variable: Savings Rate SR = 19.212 + 0.0000707(GDP) + 0.103(PINF) + u ‘u’ is the noise- an identically and independently distributed (iid) random variable. i) b0, the intercept would be expected to assume a positive sign; b1, the coefficient of GDP is expected to have a positive sign since GDP is intended to contribute positively to the ability of a nation to save; b2, the coefficient of price inflation is expected to have a negative coefficient since inflation has a negative contribution to the ability of a nation to save. ii) The marginal propensity to consume is worked out when disposable income and change in consumption are both available in a d ataset. The disposable income is in this case the amount left after the individual has spent out on all the essential needs. It could be equated to the savings rate. Therefore using the above obtained equation we can formulate it to be: SR = 19.212 + 0.0000707(GDP) + 0.103(PINF) + u iii) b0 is positive (19.212). This value has an impact on the general values obtained using the model, though not necessarily on b1 and b2 since the model was developed from a purely randomized data- the GDP, SR and PINF for any country are the products of many other factors that cannot be controlled with certainty (Wood, Hewlin & Lah, 2011). iv) The ‘u’ term in these equations stands for the noise (the uncontrollable random variable) whose nature is random and unpredictable. 3. ANOVA(b) Model Sum of Squares df Mean Square F Sig. 1 Regression 85.335 2 42.667 .612 .554(a) Residual 1184.575 17 69.681 Total 1269.910 19 a Predictors: (Constant), Price Inflation, GDP per Capita b Dependent Variab le: Savings Rate Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 19.212 2.953 6.505 .000 GDP per Capita 7.072E-05 .000 .243 1.028 .318 Price Inflation .103 .401 .061 .258 .800 a Dependent Variable: Savings Rate Both the GDP per Capita and the tice inflation (PINF) have positive coefficients, which means that they contribute positively to the ability of the nationals to save. The situation is as real as it happens in real sense. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .259(a) .067 -.043 8.34751 a Predictors: (Constant), Price Inflation, GDP per Capita From the adjusted R-square statistic, it is noted that only 4.3% of the variation in the ability of nationals to save can be explained by the two independent variables together (GDP per capita and price inflation of commodities). This is a clear indication that there are other more powerful determinants of the the ability of a nation to save. The unrepresented factors account for as much as 95.7% of the total variation observed. 4. Descriptive Statistics N Std.

Security and Integrity of health care information systems Term Paper

Security and Integrity of health care information systems - Term Paper Example Unfortunately, maintaining security and integrity of the information systems and applications is still a challenge to many hospitals and associated organizations that handle patients’ records, even after changeover to electronic storage and operations. In the healthcare industry, different stakeholders such hospitals, governments, insurance companies, pharmaceutical agencies, and the patients have various privileges to the electronic records where necessary, in order to accomplish their duties. Access to the HIS, information exchange, and disclosure of confidential data becomes prone to attack from multiple threats. This paper discusses change in the field of nursing, the use, security, and integrity of health information systems, potential threats to the HIS and EPR as identified in various researches, and their effects. It also discusses some measures to insecurity and poor integrity of health information systems. Keywords: Nursing Informatics, Healthcare Information System, Change Theory, Electronic Patient Record, Medical Identity Theft, Threats, Vulnerabilities, HIPAA, HITECH, Information Exchange, Frauds, Security, Integrity, Privacy, Confidentiality, Authorization, Authentication, Technical And Administrative Safeguards, Information Flow, Audit Logs, Healthcare Organizations, Medical Records, Business Associates, Patients, Stakeholders 1. Introduction With the changes taking place around the globe and especially changes in technology â€Å"informatics is no longer an option for nurses and other health care providers. It is a requirement† (Ball, DuLong &Hannah, 2011, p. 5). The use of computerized information systems in healthcare has undoubtedly increased the efficiency of medical record keeping, but contributed to the risk of security exposure. Sensitive personal and medical information on patients that requires privacy, risks being compromised incase of security breaches on the healthcare information systems. Protecting the healthcare inf ormation systems and data is therefore an important factor in improving healthcare quality. The increasing need for information sharing between the healthcare stakeholders (patients, providers, and payers) and the modern digital trend in record keeping create a need for better security of information. Whenever insecurity of IS exists, unauthorized access, dissemination of information, and operations on data and systems can occur, whose effect could not only affect the patients, but the healthcare providers and physicians decisions. Medical identity theft is one of the major frauds in cases of IS insecurity. Although the EHR pose various benefits to the patients, such that they can routinely review their health records electronically, it’s a fact that numerous people can view the EHR simultaneously. The systems is built on a number of compatible information technology tools, whose corruption or hacking is a lead to healthcare IS breaches. Patients’ information can be st olen for personal gains, or falsified for wrong diagnosis among other effects. Security, privacy, confidentiality, data availability, and integrity are the ethical priorities in EHR. Medical identity theft and other breaches can be detected and prevented under various procedures to secure healthcare information and IS against fraud. Several laws have been enacted and continue to be implemented ways to enforce security in healthcare IS and their content. The HITECH Act and HIPAA security rules are various government legislations that assist in