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Brock University (12,083)
CHYS 2P51 (49)
Lecture 10

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School
Department
Child and Youth Studies
Course
CHYS 2P51
Professor
Lauren Mc Namara
Semester
Fall

Description
CHYS 2F50 LECTURE 10 NOVEMBER 9, 2012 THE OTHER DESIGNS Correlational and regression-based designs - The core statistic in about 80% of al child and youth research? - Key words (correlational and regression) that mean the statistic talked about will be correlation coefficient Self-esteem and Self-monitoring - How does self-monitoring relate to self-esteem? - Young adults (N=148) from a Research Methods course answered questions on two scales that targeted the following constructs: o Other-directedness (Self-Monitoring Scale, 11 items; T/F scale) o Self-esteem (Rosenberg Self-esteem Inventory; 10 items; 4 point likert) - What is the relationship between the two? - Need two interval level measures – has to be a common scale of measurement, and 2 variables - Whenever you are talking about correlation there has to be a pair of data - 3.4 means high self-esteem, 0.17 means low on other-directedness Self-Esteem Other-Directedness 3.4 0.17 2.6 0.9 3.1 0.45 3.2 0.27 3 0.36 2.8 0.67 - What if there are two variables and the concern is their relationship? - Scatterplot – basically a way to show two people’s scores at the same time; properly interpreted – portrays the usually imperfect relationship  X is independent, Y is dependent variable o Direction – positive and negative reln. (Really high directedness means low self- esteem, and vice versa) o Magnitude/Strength depends on scatter – strong or weak (if points are really close to the line [vertically] that is a strong relationship, and vice versa); strong relationship is when the line is a good description of the relationship o Shape/Form (up or down in a straight line) – linear is all we really care about…mono-what? (Low levels is really low self-esteem, medium levels is high self-esteem, high levels is low-esteem) - Points for Construction Class Chart Example - Direction: negative - Magnitude: descending to right = strong relationship - Shape: linear relationship Seed Chart Example (lead to the invention of the correlation coefficient) - Direction: positive - Magnitude: weak relationship - Shape: non-linear relationship “The right to live does not connote the right of each man to reproduce his kind…” - Not everyone has the right to reproduce, just because you live does not mean you should procreate CHYS 2F50 LECTURE 10 NOVEMBER 9, 2012 “As we lessen the stringency of natural selection, and more and more of the weaklings and unfit survive…” - More and more of the weak people in society will procreate, not just our own capabilities but also our resources; the more and more we increase the human race the more of weak and dumb there will be “We must increase the standard, mental and physical, of parentage.” - Only the smart, attractive, healthy, etc. should be allowed to have children; provide them with incentives (hotels, etc.) or deny the opportunity to those that are not smart, attractive, etc. The guy who did the first scatterplot – considered father of eugenics - In order to improve society, we have to improve the parents; we can’t change people so we have to make sure only the good ones reproduce- how? We measure and figure out a couple things Karl Pearson - There is no way we can implement this unless we use “correlation” - It was essentially invented to advance the science of eugenics - What view does this give us on reality? - “Danger of transmission of mental deficiency Pearson Overview 2 Key Features: o Correlation is a single number that summarizes the relationship between two variables o It never tells you anything about a particular person, only describe relationship between 2 variables - Requires data that are linearly related; i
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