Chapter Normal probability distribution

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Presentation transcript:

Chapter 6 6.1 Normal probability distribution 6.2 Standard normal probability distribution 6.3 Binomial approximation 6.4 Poisson approximation

What is Continuous Probability Distribution constructed from continuous random variables values are taken on for every point over a given interval usually generated from experiments in which things are “measured” as opposed to “counted.” Probabilities of outcome = area under the curve between those points. the entire area under the whole curve is equal to 1. What is Continuous Probability Distribution

Normal Probability Distribution It fits many human characteristics, such as height, weight, length, speed, IQ, scholastic achievement, and years of life expectancy, among others.

The normal distribution exhibits the following characteristics. It is a continuous distribution. It is a symmetrical distribution about its mean. It is asymptotic to the horizontal axis. It is unimodal It is a family of curves. Area under the curve is 1.

The normal distribution is symmetrical. Each half of the distribution is a mirror image of the other half. Many normal distribution tables contain probability values for only one side of the distribution because probability values for the other side of the distribution are identical because of symmetry.

Probability Density Function of the Normal Distribution Using Integral Calculus to determine areas under the normal curve from this function is difficult and time-consuming, therefore, virtually all researchers use table values to analyze normal distribution problems rather than this formula.

Standardized Normal Distribution The conversion formula for any value of a given normal distribution follows. A z score is is the number of standard deviations that a value, x, is above or below the mean. If the value of x <mean, the score is negative; if the value of x > mean, the score is positive; and if the value of x = mean, the associated score is zero.

How to find the probabilities of Z score? The distribution probability values are given in Table A.5.

By Using calculator Casio fx-570 MS Press mode 2 times Press SHIFT Choose SD (number 1) Press 3

The area under standard normal distribution defines by P, Q and R

Solving Normal Curve Problems Example The Graduate Management Aptitude Test (GMAT), produced by the Princeton Review in Princeton, New Jersey, is widely used by graduate schools of business in the United States as an entrance requirement. Assuming that the scores are normally distributed, probabilities of achieving scores over various ranges of the GMAT can be determined. In a recent year, the mean GMAT score was 540 and the standard deviation was about 100. What is the probability that a randomly selected score from this administration of the GMAT is between 660 and the mean?

Solution We must find Graphical representation Standardize the probability into standard normal probability

The probability value in Table 6.2 for z=1.2 is 0.3849. Hence the answer is 0.3849

DEMONSTRATION PROBLEM 6.7 Runzheimer International publishes business travel costs for various cities throughout the world. In particular, they publish per diem totals, which represent the average costs for the typical business traveler including three meals a day in business-class restaurants and single-rate lodging in business-class hotels and motels. If 86.65% of the per diem costs in Buenos Aires, Argentina, are less than $449 and if the standard deviation of per diem costs is $36, what is the average per diem cost in Buenos Aires? Assume that per diem costs are normally distributed.

Solution The standard deviation and an x value are given; the object is to determine the value of the mean. 86.65% = 50 % (the left side) + 36.65 % ( right side) So focus on right side, the area = 0.3665. Look the probability in the table. What is the value of z given the area = 0.3665?

When z=1.11, the probability is 0.3665 Hence

Exercise

Exercise Tompkins Associates reports that the mean clear height for a Class A warehouse in the United States is 22 feet. Suppose clear heights are normally distributed and that the standard deviation is 4 feet. A Class A warehouse in the United States is randomly selected. a. What is the probability that the clear height is greater than 17 feet? Answer=0.8944 b. What is the probability that the clear height is less than 13 feet? Answer=0.0122 c. What is the probability that the clear height is between 25 and 31 feet? Answer=0.2144

Binomial Approximation Some problem in binomial distribution can be approximate by using normal distribution As sample sizes become large, binomial distributions approach the normal distribution in shape regardless of the value of p. This phenomenon occurs faster (for smaller values of n) when p is near 0.50. Let see the simulation here

Whenever n for any Binomial distribution is n ≥ 30, and np>5 and nq>5 Binomial distribution technique is ruled out and will be substituted with Binomial with Normal Probability distribution. Continuous Correction Factor (c.c) Continuous correction factor need to be made when a continuous curve is being used to approximate discrete probability distributions.

Continuous Correction Factor

Example In a certain country, 45% of registered voters are male Example In a certain country, 45% of registered voters are male. If 300 registered voters from that country are selected at random, find the probability that at least 155 are males.

Solutions:

Exercise (6.23) According to ars technica, HP is the leading company in the United States in PC sales with about 27% of the market share. Suppose a business researcher randomly selects 130 recent purchasers of PCs in the United States. a. What is the probability that more than 39 PC purchasers bought an HP computer? b. What is the probability that between 28 and 38 PC purchasers (inclusive) bought an HP computer? c. What is the probability that fewer than 23 PC purchasers bought an HP computer? d. What is the probability that exactly 33 PC purchasers bought an HP computer?

Poisson Approximation When the mean of a Poisson distribution is relatively large, the normal probability distribution can be used to approximate Poisson probabilities. A convenient rule is that such approximation is acceptable when Definition

Example A grocery store has an ATM machine inside Example A grocery store has an ATM machine inside. An average of 5 customers per hour comes to use the machine. What is the probability that more than 30 customers come to use the machine between 8.00 am and 5.00 pm?

Solutions