Financial data analysis Essay Example | Topics and Well Written Essays - 1000 words

Financial data analysis - Essay Example A clear linear relationship is not evident, which could be an indicator that WHEATHD is a poor predictor of WHEATSF. Figure 1: the plot of WHEATSF against WHEATHD Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 .421a .177 .174 27.2183 .177 53.344 1 248 .000 Table1: Model regression summary Table 1 above presents a summary of the regression summary. From this, adjusted R squared is 0.17, a figure that is very small indicating that the model is not very good in predicting the dependent variable as it is highly subject to chance rather than statistical relationship between the two variables. However, the p-value is less than 0.01, an indicator that the model is statistically significant, or rather we have enough evidence to assert that WHEATHD has some predictive power on WHEATSF. Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 500.582 24.519 2 0.416 .000 WHEATHD(P) -.443 .061 -.421 -7.304 .000 Table 2: a. Dependent Variable: WHEATSF(P) Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 532.035 17.694 30.069 .000 WHEATSF(P) -.400 .055 -.421 -7.304 .000 Table 3: a. ... itable statistical technique to use, but I surmounted this by examining the expected outcome to decide on the best method (Hyndman and Koehler, 2006). PART II In this part, 1- 250 sample values are used to forecast the subsequent 11 values. Using excel to forecast In using excel spreadsheets to do the forecast, we highlight the raw data and insert the scatter plot. Then, we insert the trend line in the scatter plot and subsequently format it to include the trend line equation. The trend line equation is then used to substitute the values of x for the 11 series periods that are sampled for prediction. The following table shows the values of x and the substituted values y. Y=532.03-0.4x x Y (Forecasted) Actual 308.5 408.63 443 311.5 407.43 446.5 314.5 406.23 450 313.5 406.63 447 319.5 404.23 451.5 324.5 402.23 451.5 324.5 402.23 451.5 333.5 398.63 461.25 337.5 397.03 465.75 324.5 402.23 460.75 327.5 401.03 462.5 Sum 4436.53 4991.25 Figure 2: Excel scatter plot with the equation fitted in. Using eview The raw data for the prices are input in the software and a forecast generated automatically. The output, which is shown in figure 3, comes with a table with forecast errors already computed. The table alongside shows statistical arithmetic that is associated with this particular model, including a number of methods for calculating the forecasting errors. Figure 3: Forecast for 251 - 261 Sample Figure 4: graph before model 1forecast Figure 5: graph after model 1 forecast Forecast errors Forecast errors are the estimations of the probability that the results of the forecast deviates from the actual values. Fore example, looking at figures 4 and 5 of the first forecast model, it is clear how the forecast values differ slightly from the actual values. A number of errors that

Sickle Cell-Advocacy Paper Assignment Example | Topics and Well Written Essays - 1000 words

Sickle Cell-Advocacy Paper - Assignment Example United States Centres for Disease Control and Prevention, CDC (2014) shows that it costs $11,702 to treat those children with SCD under Medicaid cover and $14,772 for those children under the employer-sponsored insurance. Combined, both groups had no less than one hospital stay. Furthermore, a research by Kauf, Coates, Huazhi, Mody-Patel and Hartzema (2009) estimates the median lifetime costs for people with SCD at $186,406 when discounted and $392,940 when undiscounted. Thus, the economic cost of SCD is a critical public health concern which makes paediatric SCD inaccessible. As such, this memo appeals to the Department of Health and Human Services to subsidise on the costs and take regulatory action that would promote paediatric SCD care initiatives that seek to increase access of the much needed paediatric SCD healthcare services. The sickle cell disease would normally cause the red blood cells to harden and become sticky, adopting a C shape, thus its name from a similarly looking farm tool. With the sickle cells dying early, there would constantly be a shortage of red blood cells, causing severe pains, infections, organ damage or anaemia (MCHB, 2014). These complications make patients constantly seek for medical services. Even though the exact number of people living with the disease remains unknown, CDC (2014) estimates between 90,000 and 100,000 Americans to be affected. Of these, African-Americans are worst hit with 1 in every 500 newborns diagnosed with SCD. These are significant numbers going by the costs already associated with caring for patients with SCD. As noted by Kauf et al. (2009), the components of cost of care for SCD patients include the inpatient and emergency department, ED hospitalisation, having found out from their study that patients with SCD incur averagely one ED visit per patient yea r, 3.7 inpatient hospitalisations and about 24.1 hospital days. According to Raphael et al. (2013), placing children under high-acuity services such as