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NCERT solutions for Class 11 Maths chapter 15 exercise 15.3 has a total of 5 questions with some questions having subpart also. Questions from exercise 15.3 mainly deal with the comparison between two sets of data in which we have to compare the variation and consistency among the given sets. Exercise 15.3 Class 11 Maths uses the same concept, hence if the initial few questions are done properly, the whole exercise can be tackled easily.
JEE Main Scholarship Test Kit (Class 11): Narayana | Physics Wallah | Aakash | Unacademy
Suggested: JEE Main: high scoring chapters | Past 10 year's papers
Solving NCERT Solutions for Class 11 Maths chapter 15 exercise 15.3 is highly recommended as it is easy as well as scoring from the exam point of view. Sometimes, direct questions are asked from this exercise as well in Boards. Also, students can refer to the following exercise of NCERT for further information about upcoming exercises.
Statistics Miscellaneous Exercise
Question:1. From the data given below state which group is more variable, A or B?
Marks | 10-20 | 20-30 | 30-40 | 40-50 | 50-60 | 60-70 | 70-80 |
Group A | 9 | 17 | 32 | 33 | 40 | 10 | 9 |
Group B | 10 | 20 | 30 | 25 | 43 | 15 | 7 |
Answer:
The group having a higher coefficient of variation will be more variable.
Let the assumed mean, A = 45 and h = 10
For Group A
Marks | Group A $f_i$ | Midpoint $x_i$ | $\dpi{100} y_i = \frac{x_i-A}{h}$ $= \frac{x_i-45}{10}$ | $y_i^2$ | $f_iy_i$ | $f_iy_i^2$ |
10-20 | 9 | 15 | -3 | 9 | -27 | 81 |
20-30 | 17 | 25 | -2 | 4 | -34 | 68 |
30-40 | 32 | 35 | -1 | 1 | -32 | 32 |
40-50 | 33 | 45 | 0 | 0 | 0 | 0 |
50-60 | 40 | 55 | 1 | 1 | 40 | 40 |
60-70 | 10 | 65 | 2 | 4 | 20 | 40 |
70-80 | 9 | 75 | 3 | 9 | 27 | 81 |
$\sum{f_i}$ =N = 150 | $\sum f_iy_i$ = -6 | $\sum f_iy_i ^2$ =342 |
Mean,
$\overline{x} = A + \frac{1}{N}\sum_{i=1}^{n}f_iy_i\times h =45 + \frac{-6}{150}\times10 = 44.6$
We know, Variance, $\sigma^2 = \frac{1}{N^2}\left [N\sum f_iy_i^2 - (\sum f_iy_i)^2 \right ]\times h^2$
$\\ \implies \sigma^2 = \frac{1}{(150)^2}\left [150(342) - (-6)^2 \right ]\times10^2 \\ = \frac{1}{15^2}\left [51264 \right ] \\ =227.84$
We know, Standard Deviation = $\sigma = \sqrt{Variance}$
$\therefore \sigma = \sqrt{227.84} = 15.09$
Coefficient of variation = $\frac{\sigma}{\overline x}\times100$
C.V.(A) = $\frac{15.09}{44.6}\times100 = 33.83$
Similarly,
For Group B
Marks | Group A $f_i$ | Midpoint $x_i$ | $\dpi{100} y_i = \frac{x_i-A}{h}$ $= \frac{x_i-45}{10}$ | $y_i^2$ | $f_iy_i$ | $f_iy_i^2$ |
10-20 | 10 | 15 | -3 | 9 | -30 | 90 |
20-30 | 20 | 25 | -2 | 4 | -40 | 80 |
30-40 | 30 | 35 | -1 | 1 | -30 | 30 |
40-50 | 25 | 45 | 0 | 0 | 0 | 0 |
50-60 | 43 | 55 | 1 | 1 | 43 | 43 |
60-70 | 15 | 65 | 2 | 4 | 30 | 60 |
70-80 | 7 | 75 | 3 | 9 | 21 | 72 |
$\sum{f_i}$ =N = 150 | $\sum f_iy_i$ = -6 | $\sum f_iy_i ^2$ =375 |
Mean,
$\overline{x} = A + \frac{1}{N}\sum_{i=1}^{n}f_iy_i\times h =45 + \frac{-6}{150}\times10 = 44.6$
We know, Variance, $\sigma^2 = \frac{1}{N^2}\left [N\sum f_iy_i^2 - (\sum f_iy_i)^2 \right ]\times h^2$
$\\ \implies \sigma^2 = \frac{1}{(150)^2}\left [150(375) - (-6)^2 \right ]\times10^2 \\ = \frac{1}{15^2}\left [56214 \right ] \\ =249.84$
We know, Standard Deviation = $\sigma = \sqrt{Variance}$
$\therefore \sigma = \sqrt{249.84} = 15.80$
Coefficient of variation = $\frac{\sigma}{\overline x}\times100$
C.V.(B) = $\frac{15.80}{44.6}\times100 = 35.42$
Since C.V.(B) > C.V.(A)
Therefore, Group B is more variable.
Question:2 From the prices of shares X and Y below, find out which is more stable in value:
X | 35 | 54 | 52 | 53 | 56 | 58 | 52 | 50 | 51 | 49 |
Y | 108 | 107 | 105 | 105 | 106 | 107 | 104 | 103 | 104 | 101 |
Answer:
X( $x_i$ ) | Y( $y_i$ ) | $x_i^2$ | $y_i^2$ |
35 | 108 | 1225 | 11664 |
54 | 107 | 2916 | 11449 |
52 | 105 | 2704 | 11025 |
53 | 105 | 2809 | 11025 |
56 | 106 | 8136 | 11236 |
58 | 107 | 3364 | 11449 |
52 | 104 | 2704 | 10816 |
50 | 103 | 2500 | 10609 |
51 | 104 | 2601 | 10816 |
49 | 101 | 2401 | 10201 |
=510 | = 1050 | =26360 | =110290 |
For X,
Mean , $\overline{x} = \frac{1}{n}\sum_{i=1}^{n}x_i = \frac{510}{10} = 51$
Variance, $\sigma^2 = \frac{1}{n^2}\left [n\sum x_i^2 - (\sum x_i)^2 \right ]$
$\\ \implies \sigma^2 = \frac{1}{(10)^2}\left [10(26360) - (510)^2 \right ] \\ = \frac{1}{100}.\left [263600 - 260100 \right ] \\ \\ = 35$
We know, Standard Deviation = $\sigma = \sqrt{Variance}= \sqrt{35} = 5.91$
C.V.(X) = $\frac{\sigma}{\overline x}\times100 = \frac{5.91}{51}\times100 = 11.58$
Similarly, For Y,
Mean , $\overline{y} = \frac{1}{n}\sum_{i=1}^{n}y_i = \frac{1050}{10} = 105$
Variance, $\sigma^2 = \frac{1}{n^2}\left [n\sum y_i^2 - (\sum y_i)^2 \right ]$
$\\ \implies \sigma^2 = \frac{1}{(10)^2}\left [10(110290) - (1050)^2 \right ] \\ = \frac{1}{100}.\left [1102900 - 1102500 \right ] \\ \\ = 4$
We know, Standard Deviation = $\sigma = \sqrt{Variance}= \sqrt{4} = 2$
C.V.(Y) = $\frac{\sigma}{\overline y}\times100 = \frac{2}{105}\times100 = 1.904$
Since C.V.(Y) < C.V.(X)
Hence Y is more stable.
Firm A | Firm B | |
No. of wage earners | ||
Mean of monthly wages | ||
Variance of the distribution of wages |
Which firm A or B pays larger amount as monthly wages?
Answer:
Given, Mean of monthly wages of firm A = 5253
Number of wage earners = 586
Total amount paid = 586 x 5253 = 30,78,258
Again, Mean of monthly wages of firm B = 5253
Number of wage earners = 648
Total amount paid = 648 x 5253 = 34,03,944
Hence firm B pays larger amount as monthly wages.
Question:3(ii) An analysis of monthly wages paid to workers in two firms A and B, belonging to the same industry, gives the following results:
Firm A | Firm B | |
No. of wage earners | ||
Mean of monthly wages | ||
Variance of the distribution of wages |
Which firm, A or B, shows greater variability in individual wages?
Answer:
Given, Variance of firm A = 100
Standard Deviation = $\sigma_A = \sqrt{Variance}= \sqrt{100} = 10$
Again, Variance of firm B = 121
Standard Deviation = $\sigma_B = \sqrt{Variance}= \sqrt{121} = 11$
Since $\sigma_B>\sigma_A$ , firm B has greater variability in individual wages.
Question:4 The following is the record of goals scored by team A in a football session:
No. of goals scored | 0 | 1 | 2 | 3 | 4 |
No. of matches | 1 | 9 | 7 | 5 | 3 |
For the team B, mean number of goals scored per match was 2 with a standard deviation $1.25$ goals. Find which team may be considered more consistent?
Answer:
No. of goals scored $x_i$ | Frequency $f_i$ | $x_i^2$ | $f_ix_i$ | $f_ix_i^2$ |
0 | 1 | 0 | 0 | 0 |
1 | 9 | 1 | 9 | 9 |
2 | 7 | 4 | 14 | 28 |
3 | 5 | 9 | 15 | 45 |
4 | 3 | 16 | 12 | 48 |
$\sum{f_i}$ =N = 25 | $\sum f_ix_i$ = 50 | $\sum f_ix_i ^2$ =130 |
For Team A,
Mean,
$\overline{x} = \frac{1}{N}\sum_{i=1}^{n}f_ix_i =\frac{50}{25}= 2$
We know, Variance, $\sigma^2 = \frac{1}{N^2}\left [N\sum f_ix_i^2 - (\sum f_ix_i)^2 \right ]$
$\\ \implies \sigma^2 = \frac{1}{(25)^2}\left [25(130) - (50)^2 \right ] \\ \\ = \frac{750}{625} =1.2$
We know, Standard Deviation = $\sigma = \sqrt{Variance}$
$\therefore \sigma = \sqrt{1.2} = 1.09$
C.V.(A) = $\frac{\sigma}{\overline x}\times100 = \frac{1.09}{2}\times100 = 54.5$
For Team B,
Mean = 2
Standard deviation, $\sigma$ = 1.25
C.V.(B) = $\frac{\sigma}{\overline x}\times100 = \frac{1.25}{2}\times100 = 62.5$
Since C.V. of firm B is more than C.V. of A.
Therefore, Team A is more consistent.
$\sum_{i=1}^{50}x_i=212, \sum _{i=1}^{50}x_i^2=902.8,\sum _{i=1}^{50}y_i=261,\sum _{i=1}^{50}y_i^2=1457.6$
Which is more varying, the length or weight?
Answer:
For lenght x,
Mean, $\overline{x} = \frac{1}{n}\sum_{i=1}^{n}x_i =\frac{212}{50}= 4.24$
We know, Variance, $\sigma^2 = \frac{1}{n^2}\left [n\sum f_ix_i^2 - (\sum f_ix_i)^2 \right ]$
$\\ \implies \sigma^2 = \frac{1}{(50)^2}\left [50(902.8) - (212)^2 \right ] \\ \\ = \frac{196}{2500} =0.0784$
We know, Standard Deviation = $\sigma = \sqrt{Variance}= \sqrt{0.0784} = 0.28$
C.V.(x) = $\frac{\sigma}{\overline x}\times100 = \frac{0.28}{4.24}\times100 = 6.603$
For weight y,
Mean,
Mean, $\overline{y} = \frac{1}{n}\sum_{i=1}^{n}y_i =\frac{261}{50}= 5.22$
We know, Variance, $\sigma^2 = \frac{1}{n^2}\left [n\sum f_iy_i^2 - (\sum f_iy_i)^2 \right ]$
$\\ \implies \sigma^2 = \frac{1}{(50)^2}\left [50(1457.6) - (261)^2 \right ] \\ \\ = \frac{4759}{2500} =1.9036$
We know, Standard Deviation = $\sigma = \sqrt{Variance}= \sqrt{1.9036} = 1.37$
C.V.(y) = $\frac{\sigma}{\overline y}\times100 = \frac{1.37}{5.22}\times100 = 26.24$
Since C.V.(y) > C.V.(x)
Therefore, weight is more varying.
The NCERT Class 11 Maths chapter Statistics is scoring and easier than other chapters in Class 11 Maths. Students need to remember the exact method to solve the questions and in order to get good marks. Exercise 15.3 Class 11 Maths deals with the questions in which comparison is done between two sets of given data. Hence NCERT solutions for Class 11 Maths chapter 15 exercise 15.3 provides a good opportunity to boost marks with less effort in the final examination.
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