Essays on Analytical Methods in Economics and Finance Assignment

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The paper "Analytical Methods in Economics and Finance" is an outstanding example of a micro and macroeconomic assignment. The summary statistics of the variables selected as the determinants of success of a given store are indicated in the table. Included in the summary statistics are the measures of central location such as the mean as well as the measures of dispersion such as the standard deviation. Table 1   Revenue People Income COMPTORS Price Mean 343965.68 5970.26 41522.96 2.8 5.68 Standard Error 5307.89863 139.0845281 582.1376385 0.142857143 0.0510302 Median 345166.5 6032 41339.5 3 5.75 Mode #N/A 5917 #N/A 3 6 Standard Deviation 37532.51115 983.47613 4116.334718 1.010152545 0.36083803 Sample Variance 1408689393 967225.2984 16944211.51 1.020408163 0.13020408 Kurtosis -0.58050278 0.965044145 0.866669536 -0.192246809 -0.7738904 Skewness -0.17644248 -0.5668814 0.380395523 0.296984848 -0.6727417 Range 152895 4827 21627 4 1 Minimum 256640 3172 30999 1 5 Maximum 409535 7999 52626 5 6 Sum 17198284 298513 2076148 140 284 Count 50 50 50 50 50 From the summary statistics of the variables included in the table above, the measures of central location; mean and median seem not to differ significantly for all the five variables analyzed.

This indicates that the distribution of the sample data is approximately symmetrical. To further analyze the distribution of the sample data above, the use of a histogram would be appropriate since it would illustrate whether the data comes from a skewed or symmetrical distribution. The histogram of the annual gross revenue is as illustrated in figure 1 below. The histogram is bell-shaped, which indicates that the distribution of the sample data is approximately symmetrical. This implies that the sample data was drawn from a population with an approximately normal distribution. Figure 1 The equation of the multiple-regression model which is to be estimated is as shown below; REVENUE = β 0+ β 1 PEOPLE + β 2 INCOME + β 3 COMPTORS + β 4 PRICE   As indicated by the equation above, REVENUE is the dependent variable in the model.

The model has four independent variables namely PEOPLE, INCOME, COMPTORS and PRICE. The regression model is considered appropriate in this case because the relationship between the dependent variable and each of the independent variables is assumed to be linear.

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