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Lecture 2

SOCB05 Lecture 2.docx

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Kriste O' Neil

SOCB05 Lecture 2Slide 5The turbulence causes them to turn on the seat belt sign not the other way aroundSlide 6Most times in social science when were talking about causation were talking about probability Its the idea that most likely the effect comes after the cause Not all the time but in probability we use terms like most likely very often increased prevalence etc Example for subpoint of point 2 You go to a friends house for the first time and see a playpenbox of toys What might you assume That they have a younger sibling A child Sellinggetting rid of old toys Are these necessarily true You dont know In sociology most of the time you dont know but you can use techniques to determine when its more likely that this X presence of toysplaypen is more likely to cause something or be the result of somethingSlide 7Independent variable factsthe effect or the variable thats being explainedtheyre the exclaiming explaining variable or the causethe variable being impacted uponcan have an impact upon another variableX IVY DVX IVY DVDependent variable factsNote Causation is not the main objective of most qualitative research Qualitative work cant really evaluate causation Some people might say this is a flaw prof disagrees If the goal of qualitative research is not to determine something causes something else its not a flaw its just not its purposeSlide 8When youre trying to evaluate whether one variable is causing or having an effect on another often times youll come up with hypothesesIe Lets say youre looking at gender and major choice what might be a hypothesis you can make Females choosing English major Males choosing managementThese are specific predictions and you can test them When creating hypotheses you want them to be specific and must have a particular direction If it doesnt have a direction you cant test itIe Is gender related to income a good hypothesis No it doesnt specify which gender and if its a high or low income A better one would be males are more likely to achieve a higher income than femalesSpeak in terms of more and less when talking about hypotheses Hard to say in a concrete way like men have more incomeOnce you start thinking about cause and effect have an idea of what your variables are then you start to create your hypothesis so you can actually test if causation existsSlide 9ExamplesKashafiro sp sat in tribal meetings in order to determine how age affected the level of political participation in such formal gatheringsDV Political participationIn the study of 2000 Canadian women it was announced those amongst heterosexual relationships regular use of contraception increased in relation to their years of schoolingIV EducationYounger people are more likely to favour same sex marriage than older aged cohortsIV Age not young people or older aged because theres a difference between a variable and an attributeagevariable attributes young middle oldLow level of education for example is not a variable Education would be the variable Attributesmagnitudes would be low medium and high levels We have characteristics for that variable Another example is prejudice variable and we measure its intensity When youre doing qualitative research you dont tend to measure variables in the same way For example youre interested in young womens experiences with domestic violence you wouldnt categorize as low medium and high Instead you look at what they say and categorize that by theme In this case were looking at causation variables must be defined with different attributes ExamplesSex race and health status Variables or attributes Variables Attributes of sex male and female race black Asian white Mexican etc health status excellent fair poor Have to be clear on what the variables mean to youSlide 11
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