Contribution Of Export Business To Bangladesh Growth Commerce
The aim of this study is to find out the contribution of export business to the economics growth of Bangladesh. Export business plays an important role to the economic development of a country. Export goods are taken into account as it generates the best correlation value of 0.956512916.
The cu-sum obtained from the data set is plotted in the line graph which shows initial increase, then rise to a peak and finally decreased in the export goods to the world.
The linear model is used as it generates a high R2 value of 0.9149 and also the equation is simple and easy to understand which is y=41.776x - 83063.
The model is tested graphically by plotting the calculated value of dependent data and the original value of dependant data.
The cu-sum graph depicted that there is a sharp increase in the goods exporting in the first few years and then reached to a peak. Finally the trend is decrease sharply again.Introduction:
This study has been carried out to measure the overall condition of export goods of Bangladesh to the other countries in the world. The generated report may help to study the export business status of the Bangladesh and make important decision to increase the export goods to different part of the world. Export business provides the maximum revenue to a countries economy. Bangladesh is poor country with high density of population. ExportTheory:Dependant variables:
Dependent variables are those whose existence is depend on other data variable. Dependent variables are plotted in Y axis in the graphs.
For example in the equation Y=m*X + c
Here the value of Y is depends on the value of variable x; m and c are constant variable here.Independent variables:
Independent variables are not depending on other data variables. Their existence is not depend on other data set.
In the above equation X is dependent variable.Correlation:
The relationship between a dependent variable and one or more independent variable is represented by the correlation.
There are three types of correlation -
Negative correlation: when there is a strong relationship between two variables then it is said negative correlation but the in opposite direction.
For example the price of a vehicle is lower with the use of the vehicle. The older a second hand Laptop is, the lower the price.
Positive correlation: Positive correlation also means strong relationship between the two variables. The more you earn, the more your property. The more you will eat, the more you will be fatter.
Zero correlation: when there is little or no correlation exists between two variables then it is said to be zero or no relationship.
For example the number of time one go out is not probably depend on the number of brother or system he/she has.
Available in http://www.writefix.comCu-sum:
By calculating and plotting cumulative sum based on the data the cu-sum charts is constructed. If the series X1, X2……X24 are data points then corresponding cumulative sums will be calculated S0, S1,…..,S24. Notice that the total number of data points lead to one more sums. Here 24 data points leads to 25 sums.
Cu-sum graph formulae is -
h0 = b / (P+Q) - identify the spacing between improper border line on cu-sum graph.
h1=a/(P+Q) - identify the spacing between suitable border line on a cu-sum graph.
Note that when α =β, h0 = h1, both sets of lines is in the same spacing.
Methodology Matters, The use of the Cu-sum Technique in the assessment of trainee competence in new procedure, by Steve Bolsin and Mark Colson, International Journal for Quality in Health Care 2000; Volume 12, Number 5:pp.433.438The goodness of fit:
The goodness of fit shows how well the set of data relates to the model used. The goodness of fit is denoted by the value of R2 obtained from the model equation. It has 0 or 1 value to represent the minimum and maximum value consecutively. The closer the R2 to 1 denotes the higher the relation of the model.Model Discussion:Method:
The data set has been taken from the World Bank data web site. The data set shows the seasonally adjusted value of export goods. Here the data is considered from 1991 to 1997 of each month data.
The data values considered here is collected from the World Bank environmental data web site. business is very important to economic development.
The data values selected to carry out this study is obtained from the web site of the World Bank database. As the data set is a sequence of observation through time, so we will use time series model building. The goods export can easily be represented by using time series model.
Appendix A contains the data setCorrelation of the data:
The correlation value between the dependent and independent is 0.956512916 which shows that there is a close correlation exists between the data variables.
See Appendix A for correlationCu-sum Calculation:
The average of the dependent dataset is used to calculate the cu-sum. Then using the equation Average - Original Data of the dependent variable, a new data set is created. These values are used to obtain the Cumulative values in a range by adding the previous value with the present value. A line graph is plotted and the graph is called the Cu-sum graph.Conclusion:
The discussion above depicted a real scenario of export business condition of Bangladesh. The study shows that there was a sharp increase in the export goods from the beginning and it reached to a highest peak. But from the peak it then dramatically decreased again which indicated the export business was not good on that time. This will result a significantly fall in the domestic economy of Bangladesh.
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