1 / 27

Statistical Analysis Essentials: A Guide for Data Interpretation

Understand fundamental statistical concepts, from sample representation to variable measurement, and learn about inferential statistics and frequency distributions. Includes graphing data techniques like histograms, boxplots, and normal distribution analysis.

camille-stevens
Download Presentation

Statistical Analysis Essentials: A Guide for Data Interpretation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Basic Statistical Review EPS 625 – Intermediate Statistics Robert A. Horn, Ph.D.

  2. The Decision Tree

  3. Key Terms • Sample • Statistic • Representative of the population • Commonly symbolized with Roman Letters • Population • Parameter • Commonly symbolized with Greek Letters • Sampling • Random Sample • Random Assignment

  4. Measurement Scales

  5. Key Terms • Variables • Categorical (Nominal – Ordinal) • Discrete • Qualitative • Frequency • Continuous (Interval – Ratio) • Quantitative • Measurement

  6. Key Terms • Independent (Predictor) Variable • Active (experimental) • Attribute (measured) • Dependent (Criterion) Variable • Extraneous Variable • Confounding • Third Variable

  7. Key Terms • Descriptive Statistics • Measures of Central Tendency • Mean, Median, Mode • Measures of Variability • Range, Standard Deviation, Variance • Inferential Statistics • Parametric • Nonparametric

  8. Frequency Distributions

  9. Graphing Data – Constructing a Graph

  10. Distorting DataThrough Graphing

  11. Bar Graphs (Categorical Data)

  12. Histograms (Continuous Data)

  13. Stem-and-Leaf Displays

  14. Boxplots

  15. Describing Distributions • Symmetric (Normal Distribution) • Modality • Unimodal, Bi-Modal, Multi (tri)-Modal • Skewness • Negative, Normal (Symmetrical), Positive • Kurtosis • Platykurtic, Mesokurtic (Normal), Leptokurtic • Linearity • Linear or Curvilinear

  16. Describing Distributions

  17. Describing Distributions

  18. Describing Distributions

  19. The Normal Distribution

  20. Summation Notation () • One of the most common symbols in statistics is the uppercase Greek letter sigma, (), which is the standard notation for summation. • It is readily translated as “add up, or sum, what follows.” • The general rule, which always applies, is to perform operations within parentheses before performing operations outside parentheses.

  21. Common Statistical Symbols • X A Raw Score • Mean of a Sample •  Mean of a Population • s Standard Deviation of a Sample •  Standard Deviation of a Population • s 2 Variance of a Sample • 2 Variance of a Population

  22. Key Terms • Probability •  = Level of Significance • p = Probability (Sig.) • Confidence Intervals • Effect Size • d Family • r Family • Standard Scores • z • 

  23. Hypothesis Testing

  24. Non-Directional (two-tailed)

  25. Directional (one-tailed – negative end)

  26. Directional (one-tailed – positive end)

  27. Statistical Results and APA t(9) = 5.08, p < .05, d = 1.61 F(2, 57) = 9.75, p < .01, 2 = .42 | = Single Space NOT t(9)=5.08,p<.05,d=1.61 F(2,57)=9.75,p<.01,2=.42

More Related