Regression Analysis of Dependent Variables

Same as the results of 10-year period, the healthcare excess return is positively correlated with the utility excess return while negatively correlated with the material excess return. Compared to the 10-year results, it is found that beta of X1 decreases from 0.2750 to 0.2045 and beta of X2 decreases from -0.3165 to -0.3382. Also, beta of X0 drops which indicates without incorporating the event risk, more other variable is explained by the explanatory variables. As the p-value is less than 5% significance level, the relationships are both statistically significant. The standard errors of X1 and X2 are both small enough to indicate that the observations are close to the fitted

The figures of both the trace statistics and the Max-Eigen statistics are all greater than their critical values at 5% significant level and also their corresponding probabilities are less than 5%, this implies that we reject the null hypothesis of no co-integration relationship at the 5% significant level for None and At most 1 respectively. But as we reject the null hypothesis of no co-integration relationship at the 5% significant level for None and At most 1, we fail to reject the null hypothesis of At most 2 co-integration relationship at the 5% significant level; since both the trace statistics (41.94812) and Max-Eigen test statistics (19.94812) are less than their critical values at same significant levels of (47.85613) and (27.58434) respectively. The co-integration test score shows the existence of long-run relationship among agricultural growth, export, foreign direct investment, infrastructure development, intellectual property right, literacy rate and research &

The inappropriate relationships between correctional officers and offenders has garnered a lot of attention as of late. As when news media focuses and depicts some police officers negatively, correctional officers are apt to face similar treatment from the press when a mistake is made. Recently, what gains attention, and is the most apt to be sensationalized, are inappropriate relationships with offenders especially of a sexual nature. Nevertheless, sensationalized or not, at times some of the attention is arguably well deserved. In 2013, CBS and many other news outlets and media reported on four female correctional officers that were impregnated by the same inmate. The resulting investigation opened a Hoover Dam of compromised officers.

Background: A significant association exists between Obstructive Sleep Apnea (OSA) & Atrial Fibrillation (AFib). Limited studies have demonstrated that the AFib patients with OSA have worse symptoms and increase hospitalizations as compared to those without OSA. We assessed the impact of previously diagnosed OSA on in-hospital outcomes (Length of Stay and Cost of Stay) in the patients with AFib.

In the research, data was extracted from FRED which is the database of the St Louis Federal Reserve Bank and Bloomberg. Ordinary least squares (OLS) analysis was used in order to perform the regressions needed to calculate the results. The data was taken exclusively on a domestic level although quantitative easing was implemented abroad as well by the Bank of Japan in 1999.The data was chosen solely from the United States due to easier access to the data and the focus of the research to analyze United States economic affairs.

One commonly used test in checking for the presence of autocorrelation when working with time series data is the ____.

If correlation occurs, then there is a problem called autocorrelation. Autocorrelation appears because successive observations over time are related to each other. This problem arises because the residual (error bullies) are not independent of one observations to other observations. It is often found in the time series data (time series) because of "disturbances" on an individual / group tend affect the "disturbance" at the individual / group the same period next.

Variables are defined in the section of “conceptualization of the problem” in this paper. The factors affecting the measurement of study variables were various in ten studies. The factors were used in all nine research studies from primary sources were age, comorbidities, and genders. In addition to those factors, some research studies used additional factors. For example, the studies (Bateman, et al., 2013; de Jager, et al., 2012; Lee, et al., 2015; Hermos, et al., 2012; Krag, et al., 2016; MacLaren, et al., 2014) also used medication as the factor. In addition to the factors (age, comorbidities, genders, and medication), the cohort study (Bateman, et al., 2013) also used other factors,

However, China economy is beginning to slow down reaching a CDP growth of only 6.7%. The strong declines in manufacturing and construction output have been key drivers of China’s growth are now instrumental in the decline. These declines are impacting heavy industries, like steel cement and coal all of which are state-owned enterprises are clustered and of strategic importance t the central government (Eckart, 2016).

Other than the current result of the DW test, positive serial correlation is still a major possible outcome of time series data. Positive serial correlation indicates that the positive errors for one observation increase the probability of a positive error for another observation, and vice versa.

The overall projects calls for regression in which we test the impacts of our independent predictors on the dependent variable, the percent of those voting to leave.

This report aims to apply statistical concepts to a real world business situation. A multiple regression model is applied to the data in order to try and predict the changes in stock price of the selected company, and the goodness of fit of the data to the model is critically analysed by testing the overall model, conducting significance tests of the regression coefficients, coefficient of multiple determination (R² and Adjusted R²). Finally, a prediction is made with a confidence interval estimate in order to analyse if the applied model and data are useful for the

In the first part of the population “listed insurance companies”, we will use the R_(i,t) as the return on the stock i on the companies, R_(m,t) is the return on EGX30 market index and 〖XR〗_(j,t) is the change in the foreign exchange rate over time period t. Then we will calculate the coefficient (FXE) γ_i monthly (using daily data), quarterly, semiannually, and annually (using weekly data) from 2000 till 2016

2. Since CapExpt is denominated in HKD while the rests of the selected data are denominated in RMB, we can apply the given exchange rate of HKD 1 = RMB 1.1037 to convert the CapExpt into RMB for comparable calculations. We will eventually convert our estimation about SHXS’s equity value back to HKD again by using the same exchange rate.

CNX Nifty being an important barometer to indicate country’s growth has always been followed with lots of interest from both academia and industry. Now, CNX Nifty could be predicted or not on a random basis gives rise to many a questions. This sounds redolent with any predictive modeling though with a certain degree of accuracy in built in to the system. The major point of consideration is that predictive modeling could be done by various measures and mechanisms. In predictive modeling Multiple Adaptive Regression (MARS), Classification and Regression Trees (CART), Logistic OLS or Non Linear OLS could be used. Here in this study the researcher has utilized Neural Network as a “Predictive Modeler” to predict CNX Nifty closing on certain random time zones under consideration.