Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than...

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Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.
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Page 1: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Sampling Distributions for Proportions

Allow us to work with the proportion of successes rather

than the actual number of successes in binomial

experiments.

Page 2: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Sampling Distribution of the Proportion

• n= number of binomial trials

• r = number of successes

• p = probability of success on each trial

• q = 1 - p = probability of failure on each trial

hat"-p" read is ˆn

rp

Page 3: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Sampling Distribution of the Proportion

If np > 5 and nq > 5 then p-hat = r/n can be approximated by a normal random variable (x) with:

n

pqp

p

p̂ˆ and

Page 4: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

The Standard Error for p̂

n

pq

ondistributi sampling p̂ the

of deviation standard The

Page 5: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Continuity Correction

• When using the normal distribution (which is continuous) to approximate p-hat, a discrete distribution, always use the continuity correction.

• Add or subtract 0.5/n to the endpoints of a (discrete) p-hat interval to convert it to a (continuous) normal interval.

Page 6: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Continuity Correction

If n = 20, convert a p-hat interval from 5/8 to 6/8 to a normal interval.

Note: 5/8 = 0.625

6/8 = 0.75

So p-hat interval is 0.625 to 0.75.

• Since n = 20,

.5/n = 0.025

• 5/8 - 0.025 = 0.6• 6/8 + 0.025 = 0.775

• Required x interval is 0.6 to 0.775

Page 7: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Suppose 12% of the population is in favor of a new park.

• Two hundred citizen are surveyed.

• What is the probability that between10 % and 15% of them will be in favor of the new park?

Page 8: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

• 12% of the population is in favor of a new park.

p = 0.12, q= 0.88

• Two hundred citizen are surveyed.

n = 200

• Both np and nq are greater than five.

Is it appropriate to the normal distribution?

Page 9: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Find the mean and the standard deviation

023.0200

)88(.12.

12.0

ˆ

ˆ

n

pq

p

p

p

Page 10: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

What is the probability that between 10 % and 15%of them

will be in favor of the new park?

• Use the continuity correction

• Since n = 200, .5/n = .0025

• The interval for p-hat (0.10 to 0.15) converts to 0.0975 to 0.1525.

Page 11: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Calculate z-score for x = 0.0975

98.0023.0

12.00975.0

z

Page 12: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Calculate z-score for x = 0.1525

41.1023.0

12.01525.0

z

Page 13: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

P(-0.98 < z < 1.41)

0.9207 -- 0.1635 = 0.7572

There is about a 75.7% chance that between 10% and 15% of the citizens surveyed will be in favor

of the park.

Page 14: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Control Chart for Proportions

P-Chart

Page 15: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Constructing a P-Chart

• Select samples of fixed size n at regular intervals.

• Count the number of successes r from the n trials.

• Use the normal approximation for r/n to plot control limits.

• Interpret results.

Page 16: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Determining Control Limits for a P-Chart

• Suppose employee absences are to be plotted.

• In a daily sample of 50 employees, the number of employees absent is recorded.

• p/n for each day = number absent/50.For the random variable p-hat = p/n, we can find the mean and the standard deviation.

Page 17: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Finding the mean and the standard deviation

046.050

)88(.12.

12.0

ˆ

ˆ

n

pqthen

pSuppose

p

p

Page 18: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Is it appropriate to use the normal distribution?

• The mean of p-hat = p = 0.12

• The value of n = 50.

• The value of q = 1 - p = 0.88.

• Both np and nq are greater than five.

• The normal distribution will be a good approximation of the p-hat distribution.

Page 19: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Control Limits

138.012.050

)88.0(12.0312.03

092.012.050

)88.0(12.0212.02

n

qpp

n

qpp

Control limits are placed at two and three standard deviations above and below the

mean.

Page 20: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Control Limits

The center line is at 0.12.

Control limits are placed at -0.018, 0.028, 0.212, and 0.258.

Page 21: Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.

Control Chart for Proportions

Employee Absences

0.3 +3s = 0.258

0.2 +2s = 0.212

0.1 mean = 0.12

0.0 -2s = 0.028

-0.1 -3s = -0.018