Business Analysis of Data from the Australian Government Department of Foreign Affairs and Trade - Assignment Example

?Task 2: 2(A 3 examples of statistical charts or diagrams have been extracted from one source, i.e. Australian Government Department of Foreign Affairs and Trade. These figures will be presented and discussed below one by one. The first selected figure discusses about the share of selected services in Australian imports of US services. The Histogram in figure 1 shows three services areas belonging to two periods, i.e. 1986-87 and 1999-00. (Figure 1) The figure shows that the imports of US services in Australia have considerably increased from 1986-87 to 1999-00. These imports have not increased a lot on the transportation sector, neither has increased in travel sector, but there has been observed a considerable rise in the imports of other services that the Australian consumers have been enjoying from the US services. The figure has covered all necessary parts that it could however it represents a very narrowed approach in terms services imported by Australia from US. Instead of the portion of ‘other services’, there should have been defined and represented the services more clearly than just putting them all into one category. Other than that, the diagram perfectly presents the actual message, i.e. increased imports since the last 20 years and does not seem to be misleading. The second figure shown below is a table that discusses the total trade that has been made between US and Australia in four different fiscal years. (Figure 2) The main conclusion that has been actually been drawn from the figure is that the total trade has been increasing between Australia and US. The total exports have risen from 1984-85 to 1999-00, where the pace of rising imports has been faster than imports. Resultantly, the trade balance of Australia has been affected in negative numbers, where the country is importing more and exporting less to US, but over the trade has been expanded. The data given in the table has projected the authentic information. Therefore, given the context of the information, there might not be need for an improvement in the figure. Additionally, the diagram could be misleading if the currency value had not been defined above, as then the numbers could not describe the actual value in financial terms. The third figure selected is a histogram which shows the levels of foreign investments made in Australia by different countries in the world. (Figure 3) The figure concludes the fact that highest investments have been made by US and the European countries which are directly the part of European Union. The data is selected from the 6 years period, i.e. from 1994-95 to 1999-00. The increasing trend in each case (EU, ASEAN, China/HK, USA, NZ, Japan, and Other) shows that foreign direct investment got an overall increment of 150% in Australia only. A further improvement in this histogram can be made in terms of separating the significant countries from EU so that they could be individually compared to the FDI made by US alone. The only misleading thing that can be noticed in the figure is about the colors of the bars that represent a specific financial year, as it is a bit confusing as only grey and blue colors have been represented to describe 6 years, whereas different colors could show the figure more clearly to those who don’t understand it well. 2 (B): The data given below in figure (4) is related to the top 15 countries of very high human development index (HDI). The values of HDI of different periods/years are shown below: (Figure 4) The figure represents simple data with HDI of 15 countries over a 31 year period. The one factor common in all the countries is that HDI is increasing, and how much or with what percentage it is increasing can be represented through a histogram, shown in figure 5 below: (Figure 5) The figure above now shows a clear representation of the values of HDI for 15 countries. A keen look at the picture shows that HDI among the top 15 countries has significantly increased for Norway, Ireland, Germany, Hong Kong, China, Iceland, and Denmark. The mentioned countries seem to be having lesser HDI values in previous years and so might their positions be among the countries’ rankings. Another effective use of the data will let us think about the other countries not discussed up till now, and those countries seem to have stable HDI values from 1980 or before that. Also, these countries seem to have stable values and this is the reason that their values have not changed a lot. Some of the countries have experienced only 0.01 value increase in their HDI which shows that either their HDI values are already stable or they have lesser growth in terms of HDI compared to what they needed to be. Task 3: The Retail Price Index (RPI) is the term used in United Kingdom for calculating the inflation on monthly basis. It actually measures the change in the cost of a basket of retail services and goods. RPI is derived after combining all the 120,000 prices which are accumulated throughout UK. The composition process of RTI is given as follows: 1. A baseline must be selected first against which the RPI calculated in future has to be compared. The baseline setting will be an independent variable and the government or any other agency can set any year or time period as a baseline. There must be two points in time among which the comparison has to be established. 2. For the baseline period, the statistical basis of the costs of goods and services must be assembled. The criteria for this process can be on the discretion of the group carrying on the process, but it is advised that it should employ comprehensive approach. 3. The baseline RPI must be first calculated. The basic formula for the calculation is adding up all the costs of different goods selected, and then dividing the sum by the total number of items that are involved. 4. A time period must be then selected to which the baseline average will be compared. All the future time periods will then be compared to one baseline selected. 5. All the prices of goods and services must be added then for comparing the selection time period with baseline period. This is calculated by adding the prices of all the goods and services and then dividing the sum by total number of goods selected. 6. Calculating the percentage change in Retail Price Index for the selected period, i.e. by subtracting the RPI of baseline from the selected time period’s baseline. The difference is then divided by the comparison RPI. The number then has to be multiplied with 100 for getting percentage change in the price increase or decrease. An example of the Retail Price Index of UK and Euro Zone has been given below in figure 6. The fluctuations in the graph show the different price indices over a period of time, where the baseline has been kept the same for all the periods. (Figure 6) The RPI calculated for a monthly period will be helpful for government in terms of looking through the trends of inflation. It will also be helpful for the governors in terms of deciding about when to control the inflation and how much flexibility there will be in the interest rates. The higher RPI will be an important indicator for a union of workers as then they will realize that the wage they have been earning will be having lesser buying power. Therefore they will ask for the same percentage rise of their wage as is recorded the percentage rise of inflation for a year or a month. The higher the RPI, the lower must be the pensioners’ expectations in terms of how much well off they are going to be in the next year, and vice versa. The fluctuations in RPI values will also let the companies decide as well as revise their product prices and other schemes. Task 4: The data for the used cars has been taken from the used cars available in U.A.E. Honda (Civic) has been chosen as a sample case study. The age and price of the 20 cars of Honda have been collected and they are presented as a table below: Car Age (Years) Car Price (Thousand AED) 1 16 5 2 10 11 3 10 12 4 6 17 5 4 28 6 4 30 7 3 31 8 4 33 9 4 34 10 3 34 11 4 35 12 4 35 13 3 35 14 3 35 15 3 36 16 3 36 17 3 38 18 3 40 19 2 43 20 2 49 Table 1: 20 Used Cars Samples of Honda Civic a) The scatter plot for above data has been developed as shown below: (Figure 7) The figure shows a linear relationship between the car age and the price it is worth of. The graph shows that older the car, lesser the price would be. Therefore, the car of 1995 model is only worth AED 5000, where as the car of 2009 model is worth AED 49000. b) The regression equation for the scatter plot developed above can be given as follows: P = A + 10.5 + c Where P defines the price of the car, given the A (age) is determined and the regression residual is known. The value 10.5 is the value which is y-intercept. c) The equation above is not valid as per the given data is concerned, and the reason is that the graph is not in perfect or ideal linear system, and there are a lot of abnormalities in the graph. For example, a car 16 years of age will have a price of AED 5000 and using the equation the price of the car 10 years of age must have a price roughly AED 21000, which is not the case in real, as the price shown above for the car of same age is AED 11000 and 12000 respectively. Hence it cannot be determined through the given equation. d) The age factor is the most important indicator in determining the price of the car. But the given data and scatter plot does not support this argument. However there is an inverse relationship between the car age and price. But we cannot argue any further than that as the prices variably change for every linear change in age of the cars. e) The other factors can play an important role in terms of supporting the given regression equation. The depreciation value is always calculated after determining the remaining life of all the connected parts in the car and this is the reason that an aged car will have more depreciation value and thus there is lesser chance of the above equation to be valid. Task 5: 5 (A): The survey conducted on the road involved the observation of 200 cars. Among the 200, 21 were red, 14 blue, 67 white, 71 black, 6 green, 14 yellow, and 7 were silver. Now the respective probabilities for the cars of different colors will be as follows: Red cars= 21/200 = 0.105 Blue cars= 14/200 = 0.07 All other cars= 165/200 = 0.825 Now the probability that the car involved in an accident is red is calculated to be equal to 0.0105. 5 (B): B1: i) The probability that the jars are under 100g in weight is = 0.0196 ii) The probability that the jars are under 98g in weight is = 0.03921 iii) The probability that the jars are under 97g in weight is = 0.0491 iv) The probability that the jars are over 100g in weight is = 0.0098 B2: The mean weight should be set at 98g. B3: The probabilities determined above show that the jars of lesser than the weight of 98g will have higher probabilities in the cases mentioned above. Therefore, there must be strict criteria determined in order to automatically weigh the jars. Work Cited: http://hdr.undp.org. 2003. Human Development Reports. [ONLINE] Available at:http://hdr.undp.org/en/humandev/. 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