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# Statistics

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### Statistics

1. 1. Prepared by: Walter Phillip SP. Palad, R.N. STATISTICS
2. 2. SAMPLING METHODS  Sample  Population  Target population
3. 3. 4 BASIC REASONS FOR THE USE OF SAMPLES greater speed. reduce cost. greater accuracy. greater scope.
4. 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. 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. 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. 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. 8.  Purposive Sampling  Convenience Sampling  Quota Sampling  Accidental Sampling
9. 9. SAMPLING ERROR  “ chance differences ”  Taking larger sample sizes can reduce sampling error, although this will increase the cost of conducting survey.
10. 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. 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. 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. 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. 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. 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.