chpt 10

• Sampling method


  • Related to representativeness
  • Only a probability sample (random sample) is truly representative of a population
  • Selection method, not sample size, determines sample representativeness
• Sample accuracy


  How close a random sample's statistic is to the true population's value it represents
• Sample size


  Affects the accuracy of findings
• Non-sampling error


  Pertains to all sources of error other than sample selection method and sample size
• Sampling error


  Involves sample selection and sample size
• Larger probability sample


  More accurate (less sample error)
• Sample size of around 1,000, the margin of sample error is about +/-3%
• Sample error for samples higher than N=1000 decreases very slow, but the price for bigger sample very quick
• With the lower end of the sample size axis, large gains in accuracy can be made with a relatively small sample size increase
• Besides the size itself, it is important to consider


  • Sample Variability
  • Interval of Confidence
• Sample size formula


  1. Variability

  2. Confidence Interval
• Variability


  Amount of dissimilarity in respondents' answers to a particular question
• As the sample size increases, the variability of sampling distribution decreases
• As the sample size increases the shape of the sampling distribution becomes more similar to a normal distribution
• Standard deviation


  Statistic that measures the dispersion of a dataset relative to its mean
• Confidence interval


  Range whose endpoints define a certain percentage of the responses to a question
• A 95% confidence interval is a range of values that you can be 95% certain contains the true mean of the population
• Practical Considerations


  1. How to determine the amount of acceptable sample error

  2. How to decide on the level of confidence to use

  3. How to balance sample size with cost of data collection