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by: Sudheer pai 
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Session 7 
PROPERTIES OF NORMAL DISTRIBUTION 
(Properties of normal Curve) 
A normal distribution with parameters μ and σ has the following properties. 
1.The curve is Bell –shaped 
a. It is symmetrical (Non-skew). 
That is β1 = 0 
b. The mean, media and mode are equal 
2. The curve is asymptotic to the X-axis. That is, the curve touches the X-axis only at -∞ 
and+∞. 
3. The curve has points of inflexion at μ - σ and μ +σ. 
4. For the distribution …. 
a. Standard deviation = σ 
b. Quartile deviation = 2/3 σ (approximately) 
c. Mean deviation = 4/5 σ (approximately) 
5. For the distribution – 
a. The odd order moments are equal to zero. 
b. The even order moments are given by – 
Thus, μ2 = σ2 and μ4 = 3σ4 
6. The distribution is mesokurtic. That is,β2 =3. 
7. Total area under the curve is unity. 
P[a < X ≤ b]= Area bounded by the curve 
and the ordinates at a and b 
a. P[ μ - σ < X ≤ μ + σ ] = 0.6826 = 68.26% 
b. P[μ – 2σ < X ≤ μ + 2σ] = 0.9544 = 95.44% 
c .P[μ – 3 σ < X  ≤ μ + 3σ] = 0.9974 = 99.74% 
STANDARD NORMAL VARIATE (SNV) 
A normal variate with mean μ=0 and standard deviation σ =1 is called Standard Normal 
Variate. It is denoted by Z. Its probability density function is – 
The graph of standard normal distribution is shown in the figure
The shaded area in the figure represents the probability that the variate takes a value between 
0 and z. This area can be read from the table of areas under Standard Normal Curve. 
Corresponding to nay positive z, the area from 0 to z can be read from this table. 
Let X be a normal variate with mean μ and standard deviation σ. Then 
by: Sudheer pai 
Page 2 of 6 
  
 
 X 
Z is a 
Standard Normal Variate 
Therefore, to find any probability regarding X, the Standard Normal Variate can be made use 
of. 
Note: The Standard Normal Variate (SNV)is denoted by N(0,1). 
PROBLEMS 
X is a normal variate with mean 42 and standard deviation 4. Find the probability that a 
value taken by X is 
(i)less then 50 (ii) greater than 50 
(iii) less than 40 (iv) greater than 40 
(v) between 43 and 46 (vi) between 40 and 44 
(vii) between 37 and 41. 
Solution: 
X is a normal variate with parameters μ=42 and σ=4 
Therefore, 
is a Standard Normal Variate. 
(i)
= P[Z<2] 
= area from(-) to 2 
= [area from(-) to 0]+[area from(-)0 to 2 
= 0.5 + 0.4772(from the table) 
= 0.977200 
= P[Z>2] 
= area from 2 to  
= [area from 0 to  ] - [area from 0 to 2] 
= 0.5 - 0.4772(from the table) 
= 0.0228 
by: Sudheer pai 
Page 3 of 6 
= P[Z < -0.5] 
= area from(- ) to (-0.5) 
= area from 0.5 to  
= [area from 0 to ] - [area from 0 to 0.5] 
= 0.5 - 0.1915 
= 0.3085 
= P[Z > -0.5] 
= area from (-0.5) to  
= area from (-0.5) to 0] + [area from 0 to ] 
= [area from 0 to 0.5] + [area from 0 to ] 
= 0.1915 + 0.5 
= 0.6915 
= P[-0.5 < Z < 0.5] 
= area from -0.5 to 0.5 
= area from -0.5 to 0] + [area from 0 to 0.5] 
= area from 0 to 0.5] + [area from 0 to 0.5] 
= 0.1915 + 0.1915 
= 0.3830 
= P[-1.25 < Z <-0.25] 
= area from –1.25 to 0.25 
= area from 0.25 to 1.25
by: Sudheer pai 
Page 4 of 6 
= area from 0 to 1.25] - [area from 0 to 0.25] 
= 0.3944 – 0.0987 
= 0.2957 
PROBLEMS 
Height of students is normally distribute with mean 165 cms. And standard deviation 5 cms. 
Find the probability that height of a students is 
more than 177 cms. 
less than 162 cms 
Solution: 
Let X denote height. Then, X is a normal variate with parameters μ = 165 cms. And σ=5 cms. 
Is N(0,1). 
(i) Probability that the student is more than 177 cms tall is – 
= P[Z > 2.4] 
= area from 2.4 to  
= [area from 0 to ] – [area from 0 to 2.4] 
= 0.5 – 0.4918 
= 0.0082 
ii) Probability that the student is less than 162 cms. Tall is ----- 
= P[Z < -0.6] 
= area from (-) to (-0.6) 
= area from 0.6 to  
= [area from 0 to ] – [area from 0 to 0.6] 
= 0.5 – 0.2258 
= 0.2742 
PROBLEMS 
Mean life of electric bulbs manufactured by a firm is 1200 hrs. The standard deviation is 200 
hrs. 
(i) In a lot of 10,000 bulbs, how many bulbs are expected have life 1050 hrs. or more? 
(ii) What is the percentage of bulbs which are expected to find before 1500 hrs. of service? 
Solution: 
Let X denotes the life of the bulbs. Then, X is a normal variate with parameters μ=1200hrs 
σ=200 hrs 
(i) Probability that life of a bulb is 1050 hrs. or more is ---
by: Sudheer pai 
Page 5 of 6 
=P[ Z ≤ -0.75] 
=0.2734 + 0.5 
=0.7734 
In a lot of n=10,000 bulbs, expected number of bulbs with life 1050 hrs. or 
more is --- 
N * P[X≥1050]=10000*0.7734=7734 
(ii) Probability that life of a bulb is 1050 hrs. or more is --- 
=P[ Z < 1.5] 
=0.5 + 0.4332 
=0.9332 
The percentage of bulbs with life less than 1500 hrs is --- 
100 * P[X<1050]=100*0.9332=93.32 
PROBLEMS 
The mean and standard deviation of marks scored by a group of students in an examination 
are 47 and 10 respectively. If only 20% of the students have to be promoted, which should be 
the marks limits for promotion? 
Solution: 
Let X denotes marks. Then, X is a Normal variate with parameters μ=47 and σ=10. 
is N(0,1). 
Let a be the marks above which if a student scores he would be promoted. Then, since only 
20% of the students have to be promoted the probability of a student getting promotion should 
be 20/100=0.2 
Therefore, 
And so, P[Z≥.z] = 0.2 where z= 
a  47 
1 
That is, [area from z to ∞]=0.2 
That is, [area from 0 to z]=0.3 
From the table of areas, the value of z for which [area from 0 to z] = 0.3 is z=0.84
by: Sudheer pai 
Page 6 of 6 
Therefore, z=0.84. 
And so, 
Thus, the marks limit for promotion is a = 55.4

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S7 sp

  • 1. by: Sudheer pai Page 1 of 6 Session 7 PROPERTIES OF NORMAL DISTRIBUTION (Properties of normal Curve) A normal distribution with parameters μ and σ has the following properties. 1.The curve is Bell –shaped a. It is symmetrical (Non-skew). That is β1 = 0 b. The mean, media and mode are equal 2. The curve is asymptotic to the X-axis. That is, the curve touches the X-axis only at -∞ and+∞. 3. The curve has points of inflexion at μ - σ and μ +σ. 4. For the distribution …. a. Standard deviation = σ b. Quartile deviation = 2/3 σ (approximately) c. Mean deviation = 4/5 σ (approximately) 5. For the distribution – a. The odd order moments are equal to zero. b. The even order moments are given by – Thus, μ2 = σ2 and μ4 = 3σ4 6. The distribution is mesokurtic. That is,β2 =3. 7. Total area under the curve is unity. P[a < X ≤ b]= Area bounded by the curve and the ordinates at a and b a. P[ μ - σ < X ≤ μ + σ ] = 0.6826 = 68.26% b. P[μ – 2σ < X ≤ μ + 2σ] = 0.9544 = 95.44% c .P[μ – 3 σ < X  ≤ μ + 3σ] = 0.9974 = 99.74% STANDARD NORMAL VARIATE (SNV) A normal variate with mean μ=0 and standard deviation σ =1 is called Standard Normal Variate. It is denoted by Z. Its probability density function is – The graph of standard normal distribution is shown in the figure
  • 2. The shaded area in the figure represents the probability that the variate takes a value between 0 and z. This area can be read from the table of areas under Standard Normal Curve. Corresponding to nay positive z, the area from 0 to z can be read from this table. Let X be a normal variate with mean μ and standard deviation σ. Then by: Sudheer pai Page 2 of 6     X Z is a Standard Normal Variate Therefore, to find any probability regarding X, the Standard Normal Variate can be made use of. Note: The Standard Normal Variate (SNV)is denoted by N(0,1). PROBLEMS X is a normal variate with mean 42 and standard deviation 4. Find the probability that a value taken by X is (i)less then 50 (ii) greater than 50 (iii) less than 40 (iv) greater than 40 (v) between 43 and 46 (vi) between 40 and 44 (vii) between 37 and 41. Solution: X is a normal variate with parameters μ=42 and σ=4 Therefore, is a Standard Normal Variate. (i)
  • 3. = P[Z<2] = area from(-) to 2 = [area from(-) to 0]+[area from(-)0 to 2 = 0.5 + 0.4772(from the table) = 0.977200 = P[Z>2] = area from 2 to  = [area from 0 to  ] - [area from 0 to 2] = 0.5 - 0.4772(from the table) = 0.0228 by: Sudheer pai Page 3 of 6 = P[Z < -0.5] = area from(- ) to (-0.5) = area from 0.5 to  = [area from 0 to ] - [area from 0 to 0.5] = 0.5 - 0.1915 = 0.3085 = P[Z > -0.5] = area from (-0.5) to  = area from (-0.5) to 0] + [area from 0 to ] = [area from 0 to 0.5] + [area from 0 to ] = 0.1915 + 0.5 = 0.6915 = P[-0.5 < Z < 0.5] = area from -0.5 to 0.5 = area from -0.5 to 0] + [area from 0 to 0.5] = area from 0 to 0.5] + [area from 0 to 0.5] = 0.1915 + 0.1915 = 0.3830 = P[-1.25 < Z <-0.25] = area from –1.25 to 0.25 = area from 0.25 to 1.25
  • 4. by: Sudheer pai Page 4 of 6 = area from 0 to 1.25] - [area from 0 to 0.25] = 0.3944 – 0.0987 = 0.2957 PROBLEMS Height of students is normally distribute with mean 165 cms. And standard deviation 5 cms. Find the probability that height of a students is more than 177 cms. less than 162 cms Solution: Let X denote height. Then, X is a normal variate with parameters μ = 165 cms. And σ=5 cms. Is N(0,1). (i) Probability that the student is more than 177 cms tall is – = P[Z > 2.4] = area from 2.4 to  = [area from 0 to ] – [area from 0 to 2.4] = 0.5 – 0.4918 = 0.0082 ii) Probability that the student is less than 162 cms. Tall is ----- = P[Z < -0.6] = area from (-) to (-0.6) = area from 0.6 to  = [area from 0 to ] – [area from 0 to 0.6] = 0.5 – 0.2258 = 0.2742 PROBLEMS Mean life of electric bulbs manufactured by a firm is 1200 hrs. The standard deviation is 200 hrs. (i) In a lot of 10,000 bulbs, how many bulbs are expected have life 1050 hrs. or more? (ii) What is the percentage of bulbs which are expected to find before 1500 hrs. of service? Solution: Let X denotes the life of the bulbs. Then, X is a normal variate with parameters μ=1200hrs σ=200 hrs (i) Probability that life of a bulb is 1050 hrs. or more is ---
  • 5. by: Sudheer pai Page 5 of 6 =P[ Z ≤ -0.75] =0.2734 + 0.5 =0.7734 In a lot of n=10,000 bulbs, expected number of bulbs with life 1050 hrs. or more is --- N * P[X≥1050]=10000*0.7734=7734 (ii) Probability that life of a bulb is 1050 hrs. or more is --- =P[ Z < 1.5] =0.5 + 0.4332 =0.9332 The percentage of bulbs with life less than 1500 hrs is --- 100 * P[X<1050]=100*0.9332=93.32 PROBLEMS The mean and standard deviation of marks scored by a group of students in an examination are 47 and 10 respectively. If only 20% of the students have to be promoted, which should be the marks limits for promotion? Solution: Let X denotes marks. Then, X is a Normal variate with parameters μ=47 and σ=10. is N(0,1). Let a be the marks above which if a student scores he would be promoted. Then, since only 20% of the students have to be promoted the probability of a student getting promotion should be 20/100=0.2 Therefore, And so, P[Z≥.z] = 0.2 where z= a  47 1 That is, [area from z to ∞]=0.2 That is, [area from 0 to z]=0.3 From the table of areas, the value of z for which [area from 0 to z] = 0.3 is z=0.84
  • 6. by: Sudheer pai Page 6 of 6 Therefore, z=0.84. And so, Thus, the marks limit for promotion is a = 55.4