Objective<br />To find out the most consistent player<br />To find out the better Batsmen/Bowler<br />To conclude that the runs scored are independent of days and weeks<br />
Introduction..<br /><ul><li> We have analyzed T20 Cricket data of the Indian Team’s performance at the International Level.
Data obtained is of batsmen and bowlers which is distinguished.
ASSUMPTION- Player will not be considered for the consistency test if played only 1 match.</li></li></ul><li>Tools Used<br />Standard Deviation<br />Coefficient of Variance<br />Correlation<br />Chi - square<br />
Standard Deviation<br /><ul><li> Is most useful in describing or analyzing a data.
It is of two types :</li></ul> 1. Simple correlation<br />2. Multiple correlation<br /> In this analysis, we have considered Simple Correlation.<br />∑xiyi – n.mean(x.y)<br />√(∑xi^2 – nx^-2) * √(∑yi^2 – ny^-2)<br />
Chi - Square<br /><ul><li>In Chi Square cases, null and alternative hypothesis to be tested are :
H0 : There is no association or dependence of 1 factor on another.
H1 : There is association or dependence of 1 factor on the other.</li></ul>Uses of Chi Square Test :<br /> It is a test of significance for association/ dependence.<br /> It is a test of Goodness of Fit.<br />X^2(k-1) = ∑ [(Oi– ei)^2]/ei<br />k<br />i=1<br />
Conclusion<br />Based on the analysis, the names of the players who should be a part of the final T20 Team are :<br />GautamGambhir<br />Yuvraj Singh<br />Rohit Sharma<br />VirendarSehwag<br />M.S.Dhoni<br />R.P.Singh<br />IrfanPathan<br />Harbhajan Singh<br />
Submitted By : Group 3<br />Pratiksha Saikia<br />Sneha Sahal<br />Vibhuti Bhatt<br />Ashish Hablani<br />Bejoy P. Alex<br />Debabrata Halder<br /> Naveen Kumar<br /> Prashant Dixit<br /> Robin Singh<br />