Class Notes (837,548)
CMNS 260 (43)
Lecture 4

# Lecture Week 4

4 Pages
59 Views

School
Department
Communication
Course
CMNS 260
Professor
Frederik Lesage
Semester
Spring

Description
• Quiz next week • KEYWORD: Causality recap: a causal explanation is “a statement in social theory about why events occur that is expressed in terms of causes and effects. They correspond to associations in the empirical world” (p.32) ◦ Acausal explanation requires: temporal, association, and that you eliminate plausible alternatives. • KEYWORD: Hypothesis:Ahypothesis is a statement from a causal explanation of a proposition that has at least one independent variable and one dependent variable, but it has yet to be empirically proven (87) ◦ 5 Characteristic of causal hypothesis At least 2 variables causal relationships between these variables expressed as a prediction or an expected future outcome logically linked to the research question (and therefore to a related theoretical framework) is falsifiable (capable of being tested against empirical evidence and shown to be true or false) ◦ Types of hypotheses Null hypothesis predicts there is no relationship if evidence support null hypothesis then?? Direct relationship (positive correlation) Indirect relationship (negative correlation) • Ways of stating causal relationships ◦ causes, ◦ x leads to y ◦ x is related to y ◦ x influence y ◦ x is associated with y ◦ if x higher, then y lower • Causal diagrams • Agood abstract will give you a sense for what is in the journal article • Example extra reading ◦ Unit of analysis is young women ◦ Variables: social networks ◦ Hypothesis 1: The primary motive for SNS use for bothAmerican and Japanese young women will be peer communication (regardless of nationality variable, both will still have as a primary motive…peer communication.) ◦ Hypothesis 2:American young women will be more likely to post photographs on Facebook while Japanese participants will be more likely to post diaries on Mixi (dependent variable: what are they posting on the sites, type of post. Independent variable: nationality) ◦ Findings 1: Hypothesis 1 was partially supported, on average for americans true, Japanese participants said it was for passing time first, communication second. ◦ Findings 2: Hyp 2 was confirmed, all of theAmerican participants used Facebook and the overwhelming majority of Japanese used Mixi. ◦ Can we generalize? No, not applied to males, or younger/older women • Dangers of not clearly defining and applying units of analysis ◦ ecological fallacy ◦ reductionism ◦ teleology ◦ tautology ◦ spuriousness • Importance of choosing appropriate unit of analysis ◦ ecological fallacy (dean made a mistake in logic) ◦ cheating and gender example-as the percentage of women in class increases, the number of cheaters increases because when there are more women, there are less men, and vice versa. There is also a negative correlation between women and cheating. ◦ However, when seeing which genders cheat in each section, the numbers of male cheaters and female cheaters are the same. • Reductionism is the opposite ◦ take a statistic (2/10 and changing it to 1/5 and then applying that logic to 5 students in the front row. • Critical analysis of mixi example • Spuriousness ◦ the connection between cell phone towers and birth rates ◦ full of shit ◦ Digging down, the science doesn’t make sense or support this. Measuring variables, reliability and validity • Measurement ◦ systematic observation can be replicated (by someone else) ◦ Measures in
More Less

Related notes for CMNS 260
Me

OR

Join OneClass

Access over 10 million pages of study
documents for 1.3 million courses.

Join to view

OR

By registering, I agree to the Terms and Privacy Policies
Just a few more details

So we can recommend you notes for your school.