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Summary 2 Research Methodology and Descriptive Statistics
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For this summary I used the micro lectures and the Q&A's. I tried to be as complete as possible while still remaining a small summary.
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Summary RMDS 2Units: 12, 14, 15, 16, 17, 18, 19, 20, 21, 22
SPSS: 1, 2, 3, 4
Important from RMDS 1
Independent variable = x-axis = column = cause = variables
Dependent variable = y-axis = row = effect = units
√
2
( )
Standard deviation = S¿ ∑ x− x
n−1
x−x
Z-score = z=
S
∑z z
Pearson’s R = r = x y
n−1
Unit 12
Different questions:
- Reasons (why did YOU become an alcoholic? + story + specific applied to knowledge)
- Diagnostic analysis (why did THIS PERSON become an alcoholic? + knowledge applied to
specific) using causal hypothesis to offer explanation (not more knowledge)
o Y is the case (person = alcoholic)
o X is a cause of Y (bad childhood alcoholism)
o X is the case (person had bad childhood)
o Y maybe caused by X (person alcoholic because of bad childhood)
1
, - Developing and testing general hypotheses (why do PEOPLE become alcoholics? +
causes/relation between cause and consequence
Deterministic = if…then always (never used, measurement error, 1 observation is enough to reject)
Probabilistic = if…then relatively more/less
Three aspects of causality/bivariate hypothesis:
1. Time order (x before y)
a. Check: interrupted time series
2. Association/correlation (x correlated to y)
a. Check: variation in case analysis (association ≠ causality)
3. Non-spuriousness (no 3rd variable for correlation/test trivariate hypothesis)
a. Confounding
b. Interaction
Unit 14
Testing trivariate hypothesis: theorizing about effects formulating hypothesis testing
- Hypothesis: The bivariate relationship (mention original hypothesis)
disappears/changes/remains the same and the test variable is related to the other variables
(mention addition/confounding/interpretation/interaction)
Addition XY
Confounding (can make X
Z Y
relation disappear/weaken)
X is explained by Z Z
2
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