PS 235 Lecture Notes Spring 2010 Clayton Thyne.  Qualitative – small N, rich description, limited generalizability  Quantitative – large N, less description,

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Presentation transcript:

PS 235 Lecture Notes Spring 2010 Clayton Thyne

 Qualitative – small N, rich description, limited generalizability  Quantitative – large N, less description, strong generalizability  Done properly, there really isn’t much difference between the two…both are meant to test H by showing how X influences Y.

 We begin w/ our hypothesis  As X increases, Y should decrease…maybe…as a state becomes more democratic, it should be less likely to fight  Y = f(X)…maybe…war = democracy  Our IV is democracy, which must vary  1. Choose N democracies and N non-democracies  2. Analyze their propensity for war  3. Conclude

Non-democracies: Iraq Libya China Syria Democracies: Mexico France Japan Canada Expectation: Should be involved in many wars Expectation: Should be involved in few wars Reality: Involved in many wars Reality: Involved in many wars Variation in IV DV doesn’t vary Conclusion: H not supported Your theory leads to this (your H)…

 You probably recall from HS that Y=mX+b, where m tells us how a variation in X impacts Y  For example…  So, Y= -1/2X + 2  Now include our vars  Y=pr(war)  X=democracy ∆X = 4 ∆Y = -2 Y intercept democracy Pr(war) If we find this, our hypothesis is supported

 With a large N, we really have numerous countries… …and we’d look for the line of “best fit”  If this were a qualitative design, we’d expect… democracy Pr(war) Non-democracies: Iraq Libya China Syria Democracies: Mexico France Japan Canada

Design from Thyne & Moreno (2008) 1.Intro sets up puzzle 2.Lit review explains and evaluates previous literature 3.Theory leads to several hypotheses, including… …so, we expect… primary/univ funding = democracy… should be a negative relationship democracy Pri/univ funding

 The first number is the impact of X on Y.  The “constant” is the Y intercept  So, roughly…  Y = mX + b…  Pri/univ funding = -.004xDemocracy  So, our hypotheses is supported…initially

 This effect is when controlling for other IVs (holding them constant)  We also need to consider the #s in parentheses, which tell us if the impact of Y on X is meaningful democracy Pri/univ funding If the obs are tight, it’s meaningful, so we put a * by the slope If the obs are spread out, it’s NOT meaningful, so no stars

 You should have 1+ testable hypotheses  You should define DV and IV  You should choose either (1) qual or (2) quan tests  Quan analyses can be done in excel…it’s pretty simple

 H: democracies will trade more  Y (trade) = mX(democracy)  We want to find m (the slope) abbrevpolity2ttrade USA RUS IND THI JPN GMY ROK INS Sample data from the class website Select the data… Then go to “insert”  “scatter”

 H: democracies will trade more  Y (trade) = mX(democracy)  We want to find m (the slope) abbrevpolity2ttrade USA RUS IND THI JPN GMY ROK INS For the slope, create a formula in a separate cell… ==CORREL(b2:b9,c2:c9) ….776 So… Y (trade) =.776*democracy …as democracy increases, trade also increases. Hypothesis is supported!