Buddhism vs. Christianity Essay Example | Topics and Well Written Essays - 1000 words

Buddhism vs. Christianity - Essay Example The life of Buddha, the founder of Buddhism started as Siddhartha, the boy who was born in the abundance of life. His father denied him the opportunities of confronting with the real trials and tribulations of life. But Buddha happened to witness certain sights, later referred as the Four Sights of Buddha, which made him realize the realities of life and it ultimately paved the way for Buddhism. It was at the request of his son Siddhartha, the king allowed him to visit the beautiful park outside the palace. Though the father was precautious enough to wrap all the unpleasant sights from his son, some of them caught the sight of him. The sight of Old Age was the first one and it really haunted Siddhartha as it was his debut experience. The haggard state of an old man roused a number of questions in his mind and it provided him a hint about the hard realities of life. His realization that no one can prevent from being old has exerted significant influence in his later teachings. It is the second visit that enables him to encounter with the fearful state of sickness, like the sight of old age torments his mentally. Afterwards, the sights of death and renunciation, the third and fourth respectively, also have the same effect on Siddhartha. This leads him to realize that there are two ways to solve the problems of life—one is to lead a pleasant life by totally ignoring all the problems of life and the other way is realizing that all these sufferings are the part of life and try to overcome these problems. Siddhartha selected the second as it was far better than the first and preached by giving up his luxurious life in the palace. The birth of Jesus was just different from that of Buddha who took birth as a man 2000 years ago in the town of Bethlehem in the land of Israel. One of the notable similarities between the lives of Buddha and Jesus is that both lived a life of simplicity and showed others the real value of it. But a

Statistical computation of maximum likelihood estimates using R Math Problem

Statistical computation of maximum likelihood estimates using R - Math Problem Example SMA do not account for seasonal changes. The duration of the moving average can best be determined according to the type of application data to forecast. Long time periods gives smoother response by removing random variations but react slower to changes in the data as it lags the trend. Short time periods produce more oscillation but closely follow the trend. SMA is calculated by averaging the most recent number of actual values. SMA is calculated by using the following equation (Chase & Jacobs 2006): Where Ft Forecast for coming period At-1 Actual value in the past At-2, At-3, Actual values two, three, periods ago. N Number of periods to be averaged In the attached excel document, SMA is calculated for three periods: three, four, and five. Different n time periods will produce different results of data values. The values of MAD corresponding to each period are shown in the following table: Table 1: MAD values for different periods of SMA Time Period (n) MAD 3 4.36 4 3.10 5 3.95 Table one demonstrates that the smallest value of MAD exists for the period of n=4. This indicates that the type of data being analyzed is best estimated using a period of four. Figure 1: SMA for periods of 3,4, and 5. Figure one confirms the results of MAD analysis from table one. The best fit trend line is the SMA for n=4. This line follows the actual data curve specially on the 15th, 22, and 25 where major change occurred in wind speed. The period that best fits the actual data is dependent on the type of data analyzed which is the wind speed. Weighted Simple Moving Average (WSMA): A weighted moving average puts different weights to each element, providing that the sum of all weights equals 1. Weights are...Short time periods produce more oscillation but closely follow the trend. In the attached excel document, SMA is calculated for three periods: three, four, and five. Different n time periods will produce different results of data values. The values of MAD corresponding to each period are shown in the following table: Figure one confirms the results of MAD analysis from table one. The best fit trend line is the SMA for n=4. This line follows the actual data curve specially on the 15th, 22, and 25 where major change occurred in wind speed. The period that best fits the actual data is dependent on the type of data analyzed which is the wind speed. A weighted moving average puts different weights to each element, providing that the sum of all weights equals 1. Weights are chosen by experience and trial and error. A general rule applies that recent past is more indicative of the future and should get higher weighting. However, if the data are seasonal weights should be established accordingly. The weighted moving average advantage over the simple moving average is the ability to vary the effects of past data. In the excel document, in the Weighted SMA sheet, the weights of the moving average are determined by trial and error to produce the least value of MAD since there is no expert opinion as to guide the setup of