MGVCL OLD PAPER

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MGVCL OLD PAPER 

Madhya Gujarat Vij Company Ltd. is an electricity company that was incorporated on 15 September 2003 by Gujarat Electricity Board. The Company obtained the Certificate of the Commencement of Business on 15 October 2003. 



Purpose: If test is conducted in batches with different set of questions, there is possibility that the difficulty level may differ and in such an event to have scores of both batches comparable, process Normalization is adopted. 2. Process: Mean and Standard Deviation is ascertained for the Base as well as Targeted Batch. Formula is applied using these figures to the Scores of Targeted Batch and Normalized score is obtained. The base factors for the calculation are: A) Proportion of Deviation B) Difference between Target Value and Average Value C) Average Value and the formula used to get Normalized Score is A x B + C. The elements comprising the above factors are modified to achieve precise results based on of data (Scores of candidates in different Batches) resulting in different methods. These methods are explained in Annexure “A”. 3. Assumptions / Pre-requisite: Basic assumption in this process is that scores in both Base Batch and Targeted Batch have Normal Distribution. The main disadvantage of Normalized scores is that they always assume a normal distribution. But if this assumption is not met, the scores cannot be interpreted as a standard proportion of the distribution from which they were calculated. It is said that you need to take at least 30 samples, to be "sure" that you have an exact enough mean and deviation estimates. It is interesting to note here that, even if a sample is taken from one batch, the size needs to be adequate enough, and then only it can represent approximate distribution of that batch. (Ref : Central Limit Theorem) The choice of n = 30 for a boundary between small and large samples is a rule of thumb, only. There is a large number of books that quote (around) this value,for example, Hogg and Tanis' Probability and Statistical Inference (7e) says "greater than 25 or 30". A. Considering above said Assumptions / Pre-requisite Normalization can not be done under following circumstance and the score needs to be left as it is for ranking purpose. • In case the size of Base Batch or Target Batch is less than 30 • In case the test Question Papers are not comparable (i.e. with different subject matter content, different pattern / level) B. The distribution of scores is normal. It may be skewed towards right or left to some extent depending upon the overall performance of candidates


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OLD Paper with Official Answer Key

13 October 2018 Second bench

13 October 2018 Third bench

14 October 2018 First bench

14 October 2018 Second bench

14 October 2018 Third bench

 15 October 2018 Second bench

 15 October 2018 First bench

15 October 2018 Third bench

Method A or D can be used in all other cases however Method A may be preferred where the examination is related with specific domain knowledge whereas Method D would be suitable for General Knowledge. It is desirable that the size of Base Batch and Target Batch is not less than 300.In this case additional elements like Average and Standard Deviation of top 0.1% of overall candidates as well as that of targeted batch are brought in the picture. 2. By using Proportion of difference ( Average score of Top

0.1% candidates minus Average+ SD of all candidates’ score) for all shifts to targeted shift the purpose to normalize the data more precisely is achieved if there is significant variation in marks scored by top 0.1% candidates in different batches. 3. Concept of Base / Standard and Target Batch is maintained. 4. Since ratio as indicated in 2 is used as one of the factor for the purpose of normalization of candidate’s score, instead of difference between score of the candidate and average score of the Base Batch, difference between score of the candidate and average + SD of score of the Base Batch is taken. 5. Having taken proportionate difference as stated above Average + SD of score for all batches is added to it. Here SD is also added because while calculating proportionate difference SD is also deducted from candidate’s score. 


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