Data Analysis Assignment Report

Added on - 28 May 2020

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Running head: DATA ANALYSISData AnalysisName of the Student:Name of the University:Author’s Note:
1DATA ANALYSISExecutive SummaryThe report analysis stock market data from DEC 2014 to DEC 2016 on different commoditiesand thus predict the future changes in the prices of McDonalds. McDonalds is one of the largestfast food restaurant chain in the world. They are famous for hamburgers, chicken recipes anddesserts. The restaurants offer both drive through as well as counter services for its customers.The present examination was done by analysing daily stocks data. Multiple regression analysis isused to examine the correlation between the stock prices of McDonalds and change in prices ofother stocks. The analysis of the future prices of McDonalds is done through adjusted R2,Analysis of Variance (ANOVA), residual analysis and Variance Inflation Factor (VIF).
2DATA ANALYSISTable of ContentsDescription of the data.....................................................................................................................3Variance Inflation Factor.................................................................................................................3Residual Analysis............................................................................................................................3Analysis of Variance........................................................................................................................5Coefficient of Determination R2......................................................................................................5Hypothesis tests for the inputs.........................................................................................................6Coefficients......................................................................................................................................6Prediction of Tomorrow’s Share Prices...........................................................................................7Conclusion.......................................................................................................................................8References........................................................................................................................................9Appendix........................................................................................................................................10VIF.................................................................................................................................................10
3DATA ANALYSISDescription of the dataThe data presents the stock prices from 8thDec 2014 to 1stDec 2016 (383 days). Inaddition, the data contains inputs from 8 independent variables and one dependent variable(future prices of McDonalds). For each of the 383 days the change in prices of the assetsmeasured are:CopperAluminiumWest Texas Intermediate OilThe Baltic Dry IndexThe Standard and Poors 500 Index of stock prices (the S&P500)Also McDonalds future pricesMost of the variables used to predict the future change are interaction variables. Moreover,some of the variables have a suffix “vel” or “acc.” “vel” followed by a number refers to thechange in price in the number of days. “acc” refers to the change in velocity.Thus while “copper” would have referred to the price of “copper”, “copper_acc1” would indicatehow the price of copper accelerates (decelerates) over a period of 2 days.Similarly “MCD_vel2” means the change in price of McDonalds going back one day.Variance Inflation FactorVariance inflation factor (VIF) is used to assess multi-collinearity in a data-set.Multi-collinearity refers to the phenomenon of correlation between two or more variables inmulti-regression. In the situation that Multi-collinearity exists in a model, with theaddition of more predictors the precision of the regression coefficient of the modeldecreases.The test for VIF showed that there is no or very low correlation between the inputvariables. The VIF for each of the 8 factors was found to be5.PhSTAT software wasused to find multi-collinearity.Thus it can be inferred that all the 8 response variables which are used to measure thefuture prices of McDonalds are independent and thus can be used in the model.Residual AnalysisTo assess the distribution in a data set the normal probability plot is used. The normal probabilityplot of the residuals shows that the data is normally distributed. Hence, it can be inferred thatfurther calculations done with the data set would be valid.
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