PSY300 lect 1 notes.docx

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Department
Psychology
Course
PSY300
Professor
Dr Peter Innes
Semester
Fall

Description
PSY300: Advanced Methods in Psychology Lecture 1 Revision: Means, Means and More Means! Two Types of Data - Ratio and interval  scale  parametric data - Ordinal and nominal  non-parametric data - This distinction determines the types of statistical analyses that may be applied to the data Parametric: Centrality and Spread M = (ΣX)/N 2 2 SD = (Σ(X-M) )/N SD = √ Z Scores - A Z score is the number of standard deviations a score is above or below the mean - Formula to change a raw score to a Z score: Z = (X-M)/SD - Formula to change a Z score to a raw score: X = (Z) (SD) + M The Normal Distribution - “If you get 8/10 on a Wordsum, and it was normally distributed, what top % of the distribution would you occupy?” - “If we wanted to contact „at risk‟ individuals, defined as the lowest 2% (Z < -2), what Wordsum score would we use as a cutoff to recognise such individuals?” Independent Samples t-Test - Shape: t-distribution with df based on two samples: df Total df1+ df 2 - Observed t-score for the difference between the two actual means: t = (M – 1 )/S 2 Difference - If the observed t-score above is larger than the critical value of t for p = .05, the null hypothesis is rejected Theory of ANOVA - Total SS: We calculate how much variability there is between scores (total sum of squares; SS ) T - Between SS: We then calculate how much of this variability can be explained by the model we fit to the data; ho
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