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Lesson01_Static.11

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  • 1. Statistics for Management Introduction and Data Collection
  • 2. Lesson Topics
    • Statistical Thinking and Management
    • Descriptive versus Inferential Statistics
    • Types of Data and their Sources
    • Types of Sampling Methods
    • Survay methods
    • Types of Survey Errors
  • 3. 1. Statistical Thinking and Management Three Aspects of Quality Improvement Management Philosophy Behavioral Tools Statistical Methods
  • 4. 2. Statistical Methods
    • Descriptive Statistics
    • Inferential Statistics
    Collecting and describing data. Making decisions based on sample data.
  • 5. Descriptive Statistics
    • Collect Data e.g. Survey
    • Present Data e.g. Tables and Graphs
    • Characterize Data e.g. Mean
    A Characteristic of a: P opulation is a P arameter S ample is a S tatistic.
  • 6. Inferential Statistics
    • Estimation
    • Hypothesis
    • Testing
    Making decisions concerning a population based on sample results.
  • 7. 3. Types of Data
  • 8. 3. Data Sources Primary Data Collection Secondary Data Compilation Observation Experimentation Survey Print or Electronic
  • 9. Quota 4.Types of Sampling Methods Samples Non-Probability Samples Judgement Chunk Probability Samples Simple Random Systematic Stratified Cluster
  • 10. Probability Samples Probability Samples Simple Random Systematic Stratified Cluster Subjects of the sample are chosen based on known probabilities.
  • 11. Simple Random Samples
    • Every individual or item from the
    • target frame has an equal chance of
    • being selected.
    • Selection may be with replacement or
    • without replacement .
    • One may use table of random numbers
    • for obtaining samples.
  • 12. Systematic Samples
    • Decide on sample size: n
    • Divide population of N individuals into groups of
    • k individuals: k = N / n
        • Randomly select one individual from the 1st group.
    • Select every k-th individual thereafter.
    N = 64 n = 8 k = 8 First Group
  • 13. Stratified Samples
    • Population divided into 2 or more groups according to some common characteristic.
    • Simple random sample selected from each.
    • The two or more samples are combined into one.
  • 14. Cluster Samples
    • Population divided into several “ clusters ”,
    • each representative of the population.
    • Simple random sample selected from each.
    • The samples are combined into one.
    Population divided into 4 clusters.
  • 15. 5. Survey methods
    • Interview (Anket, Face to face, Telephon, Letter)
    • Observation
    • Experimentation
    • Data compilation
  • 16. 6. Types of Survey Errors
    • Coverage Error
    • Non Response Error
    • Sampling Error
    • Measurement Error
    Excluded from selection. Follow up on non responses. Chance differences from sample to sample . Bad Question!
  • 17. Lesson Summary
    • Described the use of Statistical Thinking to improve
    • quality.
    • Addressed the notion of Descriptive versus Inferential
    • Statistics.
    • Defined and described different Types of Data and
    • Sources
    • Listed Types of Sampling Methods.
    • Described different Types of Survey Errors.