Analysis 1
1.1. Time Series Plot
1.2. Scatter Plot
1.3. Auto Covariance
The covariance value is in the acceptable limit.
1.4. Auto Correlation
The correlation value is in the acceptable limit.
It would be better, if I make some transformations in the data, like I should show the y value decreases with the increase in x value, but in this case the y value is not linearly decreasing with the x value.
Analysis 2
2.1. Auto Regression AR Model
2.2. Moving Average
Output Data
The auto recession is a simple and accurate model because the error level of the auto recession model is small and the confidence level is about 95%. The auto recession model gives good significant results. The ARIMA model is considered to be the best model than auto recession and moving average model because the standard error of the ARIMA model is very low. It gives 95% of the confidence level for the results. ARIMA model also shows the statistical graph, in which the average price is linearly increased with the time.
Analysis 3
The ARIMA model is considered to be the best model than auto recession and moving average model because the standard error of the ARIMA model is very low. It gives 95% of the confidence level for the results. ARIMA model also shows the statistical graph, in which the average price is linearly increased with the time.
Hypothesis Test
The hypothesis test was conducted using the required parameters and residues from ARIMA model. The hypothesis test clearly shows that there is no violation of statistical procedure from the model.
4. Forecasting and Conclusion
The forecast shows that the initial analysis done was accurate; there is no deviation of results from the sample and main analysis of data. The ARIMA model is the most accurate model than the other models.
Conclusion
The data analysis is being done to predict the results and also it is used for forecasting. In this analysis, various models have been used to analyze the data. Each analysis gave a accurate results, which can be used for prediction.
