Statistical interpretation research paper sample

Interpretation

Statistics is one of those fields that can be used in almost every walk of life, when there is a calculation, there is a name of statistics always come over the mind (Anderson 1971). The main reason behind this scene is to have different statistical measures and formulas that are relevant for the analytical vision of the companies particularly. Mean, Standard Deviation, Skewness and Kurtosis are some of the major examples of the models used in the field of statistics along with the flare of correlation and covariance for analyzing the things in an effective manner (Härdle and Simar 2012). The modeling and tests are extremely essential for the individuals to analyze the stock return. In this assignment, all of the sophisticated tools and models related to Statistical analysis will be used on E-Bay.
– The question is all about describing the mean, standard deviation, skeweness and other statistical measures after applied it on the company (Kolaczyk 2014). The mean of the stock price growth of E-Bay is 2. 79%, which is quite low. The level of deviation from the mean is high, shows a figure of 17. 36% only which is showing that the mean return has the tendency to move in either directions by 17. 36%. The stock price of the company can move in upward or downward direction by 17. 36% as confirmed by this analysis. The median growth of the share of E-bay is 1. 47%, while the level of error in the calculation is only 1. 25%. The skeweness of the data set is showing that the data is positively skewed and very near to the mean, which is showing that in the future, the stock price of the company will be in the positive node, and will increased positively in the near future. Kurtosis on the other hand, is very near to standard deviation that analyzes the level of volatility in the share prices and rate of return, which is also very high in the share price of Ebay. It can be said that the data comprises on 194 readings are normally distributed that can be found in the below mentioned histogram
– Correlation matrix is an important statistical measure that analyzes the level of relationship among two different shares. There are four different variables whose returns are in excess, and it is important to analyze the level of relationship among these variables with the help of correlation function (Kolaczyk 2014). Most of the relations among the 1st and 2nd variable is positive and high as well, while it is somewhat negative in 1st, 2nd and 3rd variable, however it is positive in 2nd and 3rd variable. In summary, it can be said that the excess return is in positive and the relationship among all of these four variables are positive, showing that all of the variables will move along with each other accordingly.
– The amount of volatility found from the White Test is low along with the intensity as well, which is again 0. 0026 as per the White Test (Little and Rubin 1987). As per the test there is a presence of Unconditional heteroskedasticity in the data, because the volatility level is very low, hence future returns can be analyzed accordingly
– The autocorrelation level as per the Durbon Watson test is showing that there is a positive relationship among all of the variables used in the assignment, shows that the movements of all of the variables will be according to each other.
– Residual correlation which has been found through the T-Statistics is again showing a positive relationship among all the variables accordingly, with a standard error of 7% which is very low.

References

Anderson, T. W. 1971. The Statistical Analysis Of Time Series. New York: Wiley.
Härdle, Wolfgang, and Léopold Simar. 2012. Applied Multivariate Statistical Analysis. Berlin: Springer.
Kolaczyk, Eric D. 2014. Statistical Analysis Of Network Data With R. New York, NY: Springer.
Little, Roderick J. A, and Donald B Rubin. 1987. Statistical Analysis With Missing Data. New York: Wiley.