Probability concepts and the normal distribution

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Definition: Mathematical or Random Experiments – any procedure or process of obtaining a set of observations which may be repeated under basically the same conditions which lead to well – defined outcomes. Examples: Tossing of a Coin Rolling a die Definition: Sample Space – the set of all possible outcomes in a mathematical or random experiment.

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Transcript of Probability concepts and the normal distribution

Page 1: Probability concepts and the normal distribution

Definition: Mathematical or Random Experiments – any procedure or process of obtaining a set of observations which may be repeated under basically the same conditions which lead to well – defined outcomes.

Examples: Tossing of a Coin

Rolling a die

Definition: Sample Space – the set of all possible outcomes in a mathematical or random experiment.

Definition: Event – any subset of the sample space.

Page 2: Probability concepts and the normal distribution

Example: Consider the experiment of rolling a die. Then, the sample space S is the set . Now, define the following events as follows:

E1 = event of getting a prime number

E2 = event of getting an odd number

E3 = event of getting an even number

6 ,5 ,4 ,3 ,2 ,1S

5 ,3 ,21 E

5 ,3 ,12 E

6 ,4 ,23 E

Page 3: Probability concepts and the normal distribution

Definition: Let S be a sample space and let A be any event of S. The probability of A denoted by P(A) is a real number satisfying the following axioms:

i)

ii) P(S) = 1

iii) If A and B are mutually exclusive, then .

From the preceding axiom, the following results are immediate:

i) If is a null event, then .

ii) If is the complement of an event A, then .

iii) If A and B are any events, then .

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Page 4: Probability concepts and the normal distribution

Probabilities can be approached in the following ways:

a)Classical Probability

b)Empirical Probability

c) Subjective Probability – uses a probability value based on an educated guess or estimate employing opinions and in exact information.

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Page 5: Probability concepts and the normal distribution

Example: If there are 50 tickets sold for a raffle and one person buys 7 tickets, what is the probability of that person winning the price.

Example: In an office there are seven women and nine men. If one person is promoted, find the probability that the person is a man.

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Page 6: Probability concepts and the normal distribution

The Normal Distribution

- the central idea in the study of parametric statistical inference.

- the basis and assumption of common parametric tests;

namely, the t – test or z – test.

Definition: The normal distribution is defined by the density function:

where and are respectively the population mean and the population standard deviation of the distribution, and .

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2

1

2

1

X

eXf

14159.3

718.2e

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Remark: For a given value of and , the density function generates a graph, called the normal curve.

Illustration:

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Properties of the Normal Curve

1. The curve is bell – shaped and symmetric about a vertical axis through .

2. The total area under the curve is 1.

3.

4. The curve extends from the mean in both directions towards

infinity.

5. The curve has a single peak.

6. The mean lies at the center of the distribution.

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Various Normal Curves for Different Mean and Standard Deviations

I.

II. but

III.

2121 but

21 21

2121 and

Page 10: Probability concepts and the normal distribution

Remark: The mean and the standard deviation vary in values and hence several normal curves can be possibly drawn. Thus, a standard normal distribution with a fixed mean and a fixed standard deviation must be established.

The following transformation transformed the

X – score into a Z – score. Z is called the standard normal random variable with mean and .

Remark: A Z – score tells us the number of standard deviations a score lies above or below its mean.

X

Z

0 1

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Applications

Example: A graduate student got a score of 58 in professional course and 49 research. In his major course, the mean score was 55 with a standard deviation of 6. On the other hand, the mean score of his research course was 45 with a standard deviation of 4. In which of the two courses did he perform better?

Page 12: Probability concepts and the normal distribution

Definition: If then the random variable Z will fall between the corresponding values

and . Thus,

.

Example: Using Excel, find the area under the standard normal curve corresponding to .

1. P(Z < 1.56) 3. P(Z > 2.46)

2. P(-1.32 < Z <1.54)

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zZP

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Applications

1. If the scores for the test have a mean of 100 and a standard deviation of 15, find the percentage of scores that will fall below 112.

2. An advertising company plans to market a product to low – income families. A study states that for a particular area, the average income per family is $24,596 and the standard deviation is $6,256. If the company plans to target the bottom 18% of the families based on income, find the cutoff income. Assume the variable is normally distributed.

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3. The average waiting time for a drive – in window at a local bank is 9.2 minutes, with a standard deviation of 2.6 minutes. When a customer arrives at the bank, find the probability that the customer will have the following time. Assume that the variable is normally distributed.

a. Less than 6 minutes or more than 9 minutes

b. Between 5 and 10 minutes.