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KSE-100 Data Analysis

Descriptive Statistics

Descriptive analysis used to describe the main feature of a collection of data. Many descriptive analyses of the variables are calculated under the study in order to explain the basic characteristic of these variables. In the table of descriptive analysis many statistic are calculated like median, mean, maximum value and minimum value, kurtosis, standard deviation, skewness, probability, and jarque-bera.

These all statistic of descriptive explain various features of the variables like median is the central value in the series which divides the arranged series of data in to two equal distributed parts in such a path that the total number of observation smallest than the median is equal to the number which is greater than it and mean is the value which represent average of all the variable values. Rest maximum value and minimum values of the variables are also determine along with the skewness and standard deviation which shows the degree of dispersed of variable around its value of mean and the degree of asymmetry of a data distribution around its mean value respectively. Kurtosis is actually nothing however it characterizes the flatness or peakedness of a data distribution as compared with the normal distribution, where as positive kurtosis shows the peakedness and the negative kurtosis illustrates flatness of a data distribution. Then Jarque-Bera (JB) test is a test of normality which is actually asymptotic that apply on the large samples and where it firstly compute kurtosis and skewness measures of ordinary least square (OLS) residual and then calculate the p value with null hypothesis that the data is normally distributed. If the calculated p value in JB analysis is low then reject the null hypothesis. Last of all characteristics is probability is calculated which also measure nothing however the chances of an event will...