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Statistics 401 Mod 4 SLP - Regression Analysis - Coursework Example

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Statistics Name Institution I have been collecting data since the first module which in my presumption forms a pattern that can be used to predict the future corresponding value. In other words, the data is in my opinion related by some mathematical formula…
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Statistics 401 Mod 4 SLP - Regression Analysis
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The points so formed when the variable values of SAL are plotted against the variable values of the DJIA would have a line of best fit which can be attached to a specific mathematical formula. The mathematical formulae might be linear, exponential, logarithmic, polynomial, moving average and the like. By making use of this formulae, it would be possible to make predictions of other values of the variable SAL and the variable values of the DJIA given the corresponding variable values. Below is a copy of the data that I have collected to date:- SEX AGE SAL(K) DJIA 1 39 23 14 2 29 33 16 2 18 32 16 1 21 54 12 1 50 48 18 2 49 37 16 1 62 70 15 2 23 23 12 1 20 36 13 1 30 35 14 2 32 21 11 1 48 55 16 This data forms a regression pattern and indeed can be used for the prediction of a corresponding element of the data given one.

My stock's closing price can be determined from the closing value of the DJIA. The null hypothesis of this distribution is that “My stock's closing price cannot be determined from the closing value of the DJIA”. It is usually a statement in negation form which this one is precisely. On the other hand, the alternative hypothesis is that; “My stock's closing price can be determined from the closing value of the DJIA”. . In the otherwise case, then the null hypothesis is not right and the alternative hypothesis is taken as the right resolution.

I computed a simple regression using the values of the SAL variables as the Y- value and the values of the DJIA variables as the X- values. By so doing, I found the regression results as shown in the screen short below. As can be seen from the results, their indeed is a very slight relationship between My stock's closing price and the closing value of the DJIA. The p-value from the results is very large as it is 2.8. this p- value is much larger than the acceptable value of 0.5. It establishes that indeed the null hypothesis is true.

In that regard, I can comfortably say that to some great extent, My stock's closing price cannot be determined from the closing value of the DJIA. This implies that other mechanisms have to be employed in an effort to establish my stock's closing price. REFERENCES Soper, H.E., Young, A.W., Cave, B.M., Lee, A., Pearson, K. (1917). "On the distribution of the correlation coefficient in small samples. Appendix II to the papers of "Student" and R. A. Fisher. A co-operative study", Biometrika, 11, 328-413.

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