# CUET UG 2022 Results Today: Here Is How NTA Score Is Calculated. All About The Marks Evaluation CUET UG 2022 Result: The National Testing Agency (NTA) will release the results of the Central University Entrance Test (CUET) conducted for admission to undergraduate courses in central universities on Thursday, September 15, 2022. The result is expected to be declared by 10 PM IST. Before the results, NTA has released a notice which describes the procedure to calculate the normalized marks from the raw marks for the multi-session papers in the entrance exam. The CUET UG exam was conducted in six phases for multiple subjects.

The generalization process is important as the difficulty level of different sessions is different for a particular subject.

A committee headed by senior professors from the Indian Statistical Institute, Delhi University and the Indian Institute of Technology, Delhi agreed on a general formula for computing the normalized scores.

As per the notice, the normalization process is important to ensure that the candidates attempting a difficult exam do not get less marks than those attempting the easy one just because of the difficulty of the paper.

## How is NTA Score Calculated?

Each candidate’s RAW score, which is the score obtained before normalization, will be normalized using the equal-percentage method in a particular subject. Separate normalization will be done for each subject for which the exam was conducted in multiple shifts.

The RAW score will be converted into NTA score (percentage score and normalized score) in three stages for each candidate appearing for a subject.

Percentile is a statistical measure that indicates the value below which the percentage of given observations in a set of observations falls. For example, if a candidate has 99 percentile, it means that 99 percentile candidates have scored less than that candidate.

step 1

convert raw score to percentile score

1. Percentile is calculated for each shift separately. Firstly, the number of candidates who appeared in a shift has to be entered. The number of candidates appearing in a shift for a particular subject should be denoted by N.

2. Thereafter, all the candidates have to be sorted in one shift in the decreasing order of their marks.

3. Then, the raw marks for each candidate should be noted. The raw scores for each candidate can be denoted by the letter T.

4. One must count the number of candidates in that shift whose raw marks are less than or equal to T.

5. The number of candidates in a particular shift whose raw marks are less than or equal to T should be represented by M.

6. The percentile score should be calculated by dividing m by N and then multiplying the value by 100.

In other words, the number of candidates with a score equal to or less than the T score in a particular session must be divided by the total number of candidates who appeared in that session, and the value must be multiplied by 100 to obtain . percentile score.

step 2

Calculate Interpolated Raw Score for each candidate

1. In the second stage, the interpolated score of each candidate should be calculated for the shift in which he/she did not appear.

For example, there are six candidates, namely A, B, C, D, E, and F. The subject in which they appeared was conducted in two shifts, i.e. Shift 1 and Shift 2.

Let us take P for A, B, C, D, E, and F. denote percentile score withaPbPCPDPIand pFrespectively.

Let us convert the raw numbers of A, B, C, D, E, and F to x. denote asaxbxCxDxy, and xFrespectively.

Candidates A, B, and C appeared for one subject test in Shift 1. Meanwhile, candidates appeared for the same subject exam in D, E and F Shift 2.

2. The values ​​should be tabulated. Four columns should be created. One column should contain the name of the candidate. Other columns will be used to show the respective percentile and raw score of each candidate.

3. In the example we consider PI P. is greater thana, Pa P. is greater thanC, PC and pF are equal. PF P. is greater thanb, Pb P. is greater thanD,

PI>pa>pC=pF>pb>pD,

4. Candidate E will have only a raw score in RAW Score 2 column as he did not appear for the exam in the 1st shift.

Candidate A will only have a raw score in the RAW Score 1 column as he did not appear in the 2nd shift.

Candidates C and F have the same percentile. This means that the raw score is xC and xF are equal.

The raw score of candidate B will be a raw score in column 1 as he did not appear in the second shift.

Only Raw Score of candidate D will be a raw score in column 2 as he did not appear in the 1st shift.

5. Now, the interpolated score should be calculated for each candidate. Interpolated scores are represented by X. The cell which is left blank for each candidate as he/she did not appear in that shift will be replaced by X.

X is calculated using the formula shown below.

In the formula, P represents the corresponding entry in the percentile column. For example, C’s percentile is P . IsC,

The variable X1 denotes the first non-blank entry below X in the table. it means that x1 is less than X.

For example, the first non-blank entry below X for candidate C is x . Isb, Therefore, in the formula, x . have to enterb,

variable x2 Above X is the first non-blank entry. it means that x2 is greater than X.

For candidate C, the first non-blank entry above X is x. Isa, Therefore, one should have x. must enter the value ofa in the formula.

6. Variable P1 x. Represents the entry in the “Percentage” column corresponding to1 From “Raw Score S1”.

For candidate C, the variable p1 P. will be replaced byb,

variable p2 x. Represents the entry in the “Percentage” column corresponding to2 From “Raw Score S2”.

For candidate C, the variable p2 P. will be replaced bya,

7. Percentile, Raw Score and Interpolated Raw Score of each candidate should be tabulated.

step 3

Calculate Normalized Score

In the last step, the normalized score should be calculated. After the first two stages, each candidate was assigned a percentile value for each session conducted for a particular subject.

The normalized score represented by Z is calculated by finding the average of the rough scores of a particular candidate across all the sessions.

For example, if a candidate scored S1 in Shift 1 and his interpolated score in Shift 2 is S2, the normalized score would be (S1 + S2)/2.

Hence, the normalized score is calculated by dividing the sum of the raw scores obtained by a particular candidate in a subject by the number of sessions conducted for that subject.

If four sessions are conducted for a particular subject, the candidate’s raw scores in the different sessions should be added up, and the sum should be divided by four. 