Presentation is loading. Please wait.

Presentation is loading. Please wait.

REVIEW Normal Distribution Normal Distribution. Characterizing a Normal Distribution To completely characterize a normal distribution, we need to know.

Similar presentations


Presentation on theme: "REVIEW Normal Distribution Normal Distribution. Characterizing a Normal Distribution To completely characterize a normal distribution, we need to know."— Presentation transcript:

1 REVIEW Normal Distribution Normal Distribution

2 Characterizing a Normal Distribution To completely characterize a normal distribution, we need to know only 2 things: –The mean ---  –The standard deviation --- 

3 HAND CALCULATIONS FOR THE NORMAL DISTRIBUTION Probability tables have been created for the normal distribution expressed in terms of z, where z = the number of standard deviations x is from its mean, , i.e.

4 TYPES OF NORMAL TABLES Two types of normal tables –Tables giving probabilities from z = 0 to a positive value of z –Cumulative normal tables giving probabilities from z = - ∞ to any value of z Excel uses this approach

5 0 z Z  Normal Curve with X and Z Scales Probabilities from 0 to z  a X Some tables give probability of falling between 0 and a positive z value µ a X

6 0 z Z  Curve with X and Z Scales Cumulative Probabilities from - ∞ to z  a X µ a X A cumulative normal table gives the probability of falling between - ∞ and any z value

7 Calculating Normal Probabilities Using Cumulative Probabilities LEFT TAIL PROBABILITIES P(X<a) or P(Z<z) = area between -∞ and a (or z) –Probability to the left –Cumulative normal table valueEXCEL: =NORMDIST(a,µ,σ,TRUE) =NORMDIST(a,µ,σ,TRUE) or =NORMSDIST(z)

8 Calculating Normal Probabilities Using Cumulative Probabilities RIGHT TAIL PROBABILITIES P(X>a) or P(Z>z) = area between a (or z) and +∞ Probability to the right 1 - (Cumulative normal table value)EXCEL: =1-NORMDIST(a,µ,σ,TRUE) =1-NORMDIST(a,µ,σ,TRUE) or =1-NORMSDIST(z)

9 Calculating Normal Probabilities Using Cumulative Probabilities IN BETWEEN PROBABILITIES P(a<X<b) or P(z a <Z<z b ) –Probability between a and b on the X scale or between z a and z b on the Z scale –(Cumulative normal table value for z b ) - (Cumulative normal table value for z a )EXCEL: =NORMDIST(b,µ,σ,TRUE) - NORMDIST(a,µ,σ,TRUE) =NORMSDIST(z b ) - NORMSDIST(z a ) =NORMDIST(b,µ,σ,TRUE) - NORMDIST(a,µ,σ,TRUE) or =NORMSDIST(z b ) - NORMSDIST(z a )

10 Calculating x Values from Cumulative Normal Probabilities Determining the x value such that the probability of getting a value less than x is p left –Find the cumulative normal probability, p, (approximately) in the table (to the left of x) and note the corresponding z value –x = µ + zσEXCEL: = NORMINV(p,µ,σ) = NORMINV(p,µ,σ) or = µ + NORMSINV(p)*σ

11 EXAMPLE Flight times from LAX to New York: –Are distributed normal –The average flight time is 320 minutes –The standard deviation is 20 minutes

12 Probability a flight takes exactly 315 minutes P(X = 315 ) = 0 –Since X is a continuous random variable

13 Probability a flight takes less than 335 minutes.4332 σ = 20 320 X 335 0 Z 0.75 EXCEL =NORMDIST(335,320,20,TRUE) OR =NORMSDIST(.75) FROM TABLE.7734

14 Probability a flight takes more than 325 minutes.4332 σ = 20 320 X 0 Z 0.25 EXCEL =1-NORMDIST(325,320,20,TRUE) OR =1-NORMSDIST(.25) 325 FROM TABLE.5987 1 -.5987 =.4013

15 Probability a flight takes between 303 and 348 minutes.4332 σ = 20 320 X 303 348 -0.85 0 Z 1.40 EXCEL =NORMDIST(348,320,20,TRUE)-NORMDIST(303,320,20,TRUE) OR =NORMSDIST(1.40)-NORMSDIST(-0.85).9192 -.1977 =.7215 FROM TABLE.9192 FROM TABLE.1977

16 75% of the flights arrive within how many minutes?.4332 σ = 20 320 X 0 Z EXCEL =NORMINV(.75,320,20) OR =320 + NORMSINV(.75)*20 x.7500 is to the left of x Try to find.7500 in the middle of the cumulative normal table. 0.67 The closest value is.7486 which corresponds to a z-value of 0.67. x = 320 +.67(20) 333.4

17 85% of the flights take at least how many minutes?.4332 σ = 20 320 X 0 Z EXCEL =NORMINV(.15,320,20) OR =320 + NORMSINV(.15)*20 x.8500 is to the right of x Thus, 1-.8500 =.1500 is to the left of x Try to find.1500 in the middle of the cumulative normal table. -1.04 The closest value is.1492 which corresponds to a z-value of -1.04 x = 320 + (-1.04)(20) 299.2

18 EXCEL CALCULATONS USING x

19 EXCEL CALCULATONS USING z

20 REVIEW Normal distribution is completely characterized by µ and σ Calculation of: –“ ” probabilities, and “in between” probabilities using: Cumulative probability table NORMDIST and NORMSDIST functions –“x values” and “z values” corresponding to a cumulative probability using: Cumulative probability table NORMINV and NORMSINV functions


Download ppt "REVIEW Normal Distribution Normal Distribution. Characterizing a Normal Distribution To completely characterize a normal distribution, we need to know."

Similar presentations


Ads by Google