1.- BASIC CONCEPTS-con-video

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1.- BASIC CONCEPTS-con-video

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  1. EPSY 5210 Ed. Statistics

    Slide 1 - EPSY 5210 Ed. Statistics

    • Instructor: Hector Ponce
    • Background:
    • Research Interest
    • Experience with Quantitative Analysis
    • Additional comments
  2. In the Beginning

    Slide 2 - In the Beginning

    • Necessary Information
  3. What’s statistics?

    Slide 3 - What’s statistics?

    • The science of organizing and analyzing information.
    • Inference
    • To find:
    • Areas under the bell curve (e.g., z test)
    • Comparing means (i.e., t-test, and ANOVA)
    • Correlations (Pearson r)
    • Compare proportions (chi square)
  4. Parameters/statistics

    Slide 4 - Parameters/statistics

    • Mean (average):
    • Standard deviation (for a sample):
  5. What’s statistically significant differences?

    Slide 5 - What’s statistically significant differences?

  6. The normal curve distribution function:

    Slide 6 - The normal curve distribution function:

  7. Effect size: Cohen’s d, r, and r2

    Slide 7 - Effect size: Cohen’s d, r, and r2

    • To what extent a phenomenon exists.
    • Ratio: Cohen’s d
    • Percentage: r and r2
  8. Population and Samples

    Slide 8 - Population and Samples

    • Population: Comprises all members of a group
    • Quantitative values are parameters
    • Inferential statistics infer population characteristics from sample data
    • Notation is in Greek symbols
    • Sample
    • Quantitative values are estimates
    • Descriptive statistics describe samples and do not infer or generalize to populations
    • Notation is in alphanumeric
  9. Types of Statistics

    Slide 9 - Types of Statistics

    • Parametric statistics (z-test, t-test, ANOVA )
    • Meet certain theoretical assumptions
    • Example - Variable is normally distributed in the population
    • Data must be interval or ratio
    • Non parametric statistics (Chi square)
    • Less rigorous theoretical assumptions
    • Example - don’t meet normal distribution assumptions
    • Example – distribution unknown or “free”
  10. Statistical Values

    Slide 10 - Statistical Values

    • Constants: Values that don’t change
    • Example: Pi is a constant of 3.1214, diameter of the earth is 7,918 miles
    • Variables: Values that are free to change
    • Example: Length or depth are variable
    • Example: An price assigned to a product
    • Discrete: Value can only be whole numbers
    • Example: Family size
  11. Statistical Values (con’t)

    Slide 11 - Statistical Values (con’t)

    • Continuous: Value can range from negative infinite to positive infinite. Normally, the range is from “0” to some positive number
    • Example: Weight or height are continuous (97.3 lbs or 5’3.2”)
  12. Measurement

    Slide 12 - Measurement

    • Four Scales
    • Qualitative Scales
    • Nominal: Identification of substance
    • Gender
    • Ethnicity
    • Ordinal: Ranks order of substance
    • In a competition: First place, second place.
    • Quantitative Scales
    • Ratio: Absolute zero of substance: Kelvin
    • Speed
    • Weight
    • Interval: Arbitrary zero: Celsius
    • GRE scores
  13. Types of Measurements

    Slide 13 - Types of Measurements

  14. Research Variables

    Slide 14 - Research Variables

    • Independent Variables: Vary naturally or are manipulated by the research
    • Dependent Variables: “Dependent” on the independent variable; outcome
    • Weight (dependent variables) dependent on caloric intake (independent variable)
  15. References

    Slide 15 - References

    • Dr. Young
    • Dr. Roberts