1. Prepared by:
Walter Phillip SP. Palad, R.N.
STATISTICS

2. SAMPLING METHODS
 Sample
 Population
 Target population

3. 4 BASIC REASONS FOR THE
USE OF SAMPLES
greater speed.
reduce cost.
greater accuracy.
greater scope.

4. TYPES OF SAMPLING
METHODS:
PROBABILITY SAMPLING
 use some form of random selection
 equal probabilities of being selected
 there is an “OBJECTIVE” way of assessing reliability of result.
NON PROBABILITY SAMPLING
 the sample is not a proportion of the population and there is
no system in selecting sample.
 the selection depends on the situation

5. PROBABILITY
SAMPLING
 Pure/ Simple Random Sampling
( Lottery sampling or Fishbowl
Method )
 equal chance of being selected.
 Systematic Sampling ( Restricted
Random Sampling )
 alphabetical arrangement,
residential or house arrays,
geographical placement, etc.
 e.g. 20% of sample size. If 100%
is divided by 20%, then the result
is 5, so every 5th name will be
taken from the population.

6.  Stratified Random Sampling
 grouped in to a more or less homogenous classes
 CLASSIFICATION: Horizontal and Vertical
 Horizontal: BSED, BSN, BSHRM at same year
 Vertical: 1st year, 2nd year, 3rd year and 4th year or Age 10,
11, 12, etc.
 Cluster Sampling ( Area Sampling )
 heterogonous individual
 used when population is very large and wide (community)

7. NON PROBABILITY SAMPLING
 the sample is not a proportion of the
population and there is no system in
selecting sample.
 the selection depends on the situation

8.  Purposive Sampling
 Convenience Sampling
 Quota Sampling
 Accidental Sampling

9. SAMPLING ERROR
 “ chance differences ”
 Taking larger sample sizes can reduce sampling error,
although this will increase the cost of conducting
survey.

10. STANDARD ERROR OF THE
MEAN
Note: Standard deviation is computed by getting the square
root of the variance.
Note: To compute for standard error of the mean, divide the
computed standard deviation by the square root of the total
( sum ) frequencies

11. CONFIDENCE INTERVALS AND
CONFIDENCE LEVELS
Statisticians use a confidence interval to describe the
amount of uncertainty associated with a sample
estimate of a population parameter.
The confidence level describes the uncertainty
associated with a sampling method.

12. EXAMPLE
1. A sample of 16 students is taken. The
average age in the sample was 22 years with
a standard deviation of 6 years. Construct a
95 % confidence interval for the average age
of the population.

13. 2. A sample of 100 bean cans showed an
average weight of 13 ounces with a standard
deviation of 0.8 ounces. Construct a 90%
confidence interval for the mean of the
population.

14. PRACTICE SET:
1. Construct a 90% confidence for the population
mean, m. Assume the population has a normal
distribution. In a recent study of 22 eighth graders,
the mean number of hours per week that they
watched television was 19.6 with a standard
deviation of 5.8 hours.

15. 2. A random sample of 40 students has a
mean annual earnings of $3120 and a
standard deviation of $677. Construct the
90% confidence interval for the population.