Forecasting Cloud Storage Consumption Using Regression Model

Scientific Study , 2017 , 13 Pages , Grade: A

Computer Science - Commercial Information Technology

The primary aim of the study was to develop a regression model for forecasting monthly cloud storage consumption. Second, to ascertain if the month is a reliable predictor of cloud storage capacity consumed. The model was developed using Minitab18 statistical software. The dependent variable was cloud storage capacity consumed, while the independent variable was the month of cloud storage consumption. The model was validated by checking the assumptions of regression to establish its suitability in making future predictions. Twelve-month data sets was analyzed to make future prediction for each passing month. The model made predictions with near accuracy from the actual cloud storage data consumed in each month. The model determines the intervals of monthly storage consumption. The study concluded that the month is a globally significant linear predictor of cloud storage capacity consumed over a period.

Table of Contents

1.0. Introduction
1.1. Background of the study
1.2. Problem statement
1.3. Objectives of the study:
1.4. Research hypothesis:

2.0. Related works/ Review of related literature

3.0. Methods
3.1. Method and source of data collection
3.2. Sample size
3.3. Method of data analysis, procedure and instrument used for analysis
3.4. The regression model
3.5. Dependent and Independent Variable
3.6. Validation of model

4.0. Analysis
4.1. Regression Equation
4.2. Discussion
4.3. Key findings

5.0. Conclusion

6.0. References

• Grade: A
• Authors: lecturer Abdallah Ziraba (Author), Mbata David (Author)
• Publication Year: 2017
• Pages: 13
• Catalog Number: V413003
• ISBN (eBook): 9783668660397
• ISBN (Book): 9783668660403
• Language: English
• Tags: cloud Computing