Given information
The normal distribution is a continuous probability distribution that is symmetrical around its mean, most of the observations cluster around the central peak, and the probabilities for values further away from the mean taper off equally in both directions. Extreme values in both tails of the distribution are similarly unlikely.
Step-by-step explanation
A normal distribution is a proper term for a probability bell curve. In a normal distribution, the mean is zero, and the standard deviation is 1. It has zero skew and kurtosis of 3. Normal distributions are symmetrical, but not all symmetrical distributions are normal.
The normal distribution is a continuous probability distribution that is symmetrical around its mean, most of the observations cluster around the central peak, and the probabilities for values further away from the mean taper off equally in both directions. Extreme values in both tails of the distribution are similarly unlikely. As with any probability distribution, the normal distribution describes how the values of a variable are distributed. It is the most important probability distribution in Statistics because it fits many natural phenomena.
Unlock all Textbook Solutions
Introductory Statistics
Solutions
Chapter
Section
- Problem 1
- Problem 2a
- Problem 2b
- Problem 3a
- Problem 3b
- Problem 4a
- Problem 4b
- Problem 5
- Problem 6a
- Problem 6b
- Problem 7
- Problem 8
- Problem 10
- Problem 10
- Problem 11
- Problem 12
- Problem 13
- Problem 14
- Problem 15
- Problem 16
- Problem 17
- Problem 18
- Problem 19
- Problem 20
- Problem 21
- Problem 22
- Problem 23
- Problem 24
- Problem 25
- Problem 26
- Problem 27
- Problem 28
- Problem 29
- Problem 30
- Problem 31
- Problem 32
- Problem 33
- Problem 34
- Problem 35
- Problem 36
- Problem 37a
- Problem 37b
- Problem 37c
- Problem 38
- Problem 39
- Problem 40
- Problem 41
- Problem 42
- Problem 43a
- Problem 43b
- Problem 44
- Problem 45
- Problem 46
- Problem 47a
- Problem 47b
- Problem 48
- Problem 49
- Problem 50
- Problem 51
- Problem 52
- Problem 53
- Problem 54
- Problem 55
- Problem 56
- Problem 57
- Problem 58
- Problem 59
- Problem 60