Srm assignment2 group1

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Bivariate Regression Analysis Group -1 Abhijeet Dash UM14001 Abinash Mallick UM14004 Esha Epsita UM14024 G.Tarakeshwar UM14025 Krishna K. Sahoo UM14029 Kundan Mohapatra UM14032 Nitika Baralia UM14036 P.Goutam Prasad Rao UM14037 Padmalaya Mallick UM14038 Sukanya Dash UM14056

Transcript of Srm assignment2 group1

Page 1: Srm assignment2 group1

Bivariate Regression Analysis

Group -1

Abhijeet Dash UM14001Abinash Mallick UM14004 Esha Epsita UM14024 G.Tarakeshwar UM14025 Krishna K. Sahoo UM14029 Kundan Mohapatra UM14032Nitika Baralia UM14036P.Goutam Prasad Rao UM14037Padmalaya Mallick UM14038Sukanya Dash UM14056

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Assigment-2

Objective: To find the relationship between coal

production and electricity generation in India

Apriori reasoning: Thermal energy is a major

source of electricity generation. It contributes about 60% to the total electricity generation in India. The other sources being Hydro, Wind, Nuclear, Solar and Tidal.

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Hypothesis

Ho: There exists no relation between Electricity generation and coal production in India.

H1: There is a relation between Electricity generation and coal production in India.

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Dependent Variable: Electricity generation

Independent Variable: Coal production

Source of Data:http://www.bp.com/statisticalreview

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Data and Results

The file contains the source Data which is needed for analysis ---

Results of SPSS Linear regression models -------------------

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Analysis Table of All Models

Equation Alpha Beta1 Beta2 Beta3 R Squared

Simple Linear 1.36E-25 0.993 0.986

Linear Trend 1.87E-22 0.988 0.975

Log-linear 7.27E-25 0.992 0.984

Semi-log 1.71E-26 0.994 0.988

Quadratic 3.25E-24 1.174 -0.184 0.987

Cubic 1.12E-22 1.06 0.072 -0.145 0.987

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Interpretation of the Results

As per the regression results, R square value for the semi-log model is the highest, however we can see close R-square value for Log Linear, Cubic, Quadratic and Linear model as well. Hence we can say that this model explains the relationship between independent and dependent variables.

As R square value is very high and, the significance value is nearly 0 which is less than 5% (taken as default), we can reject the null hypothesis stating that there is a relationship between the coal production and electricity generation.

Considering the above models it is clear that the semi-log model has a better explanatory power

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Conclusion

Hence, the semi-log model best explains our alternate hypothesis that electricity generation is co-related to coal production in India.

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Thank you