The Analyst Paper
NEED A NEW ANALYSIS PAPER FOR WEEK 6
Write up a 1 page explanation of why we use ANOVAS (why not just t tests) and why correlations are helpful to social scientists. Give an example from the SDA book of why ANOVAS were used rather than t tests. Explain. (ALL READY COMPLETED)
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You are placed into groups of 3 to complete the short written weekly “Group Work” assignments. There are 3 roles that each member must take; 1 role per group assignment. You also must switch roles every week (so every student should take on every role twice). Here are the roles; you decide amongst yourselves who will take on which specific role first.
1. Leader: In this role, the student will lead a brief review to the other group members about the specifics of the assignment and what has to be done and by whom. The leader gives deadlines of when work needs to be turned into him/her so that s/he can review it and make sure it looks good before formally submitting it. The leader is ultimately responsible for the final product.
2. Workhorse: The workhorse dives into the project and is responsible for the vast majority of the “work” for the assignment. This may include: writing up a first draft of the assignment and crunching numbers. This role is difficult, because it assumes the workhorse fully understands the concepts and assignments. If s/he doesn’t, it’s the analyst’s job to assist her/him. Ultimately, the leader signs off on all work.
3. Analyst: The analyst takes a critical look at the draft and work the workhorse has submitted and makes appropriate edits/asks appropriate questions. The analyst is also responsible for writing up a “Group Work Analysis Report” where s/he evaluates the effectiveness of both the leader and the workhorse. Included in the short report (at least one paragraph, but can be up to one full page) will be a number grade for the leader and workhorse using a scale from 1 “Very ineffective” to 5 “Very Effective”. The analyst will also add at least one full paragraph explaining his/her scores in the report. This report is turned in as a separate document
Group Work Week 6
“ANOVAS”
Analysis of Variance or ANOVA is a hypothesis testing procedure similar to a T-test in that it compares the mean differences between samples. Like a T-test an ANOVA is used to determine whether observed differences between samples are significant enough to conclude that the differences are the result of systematic differences between the means and not sampling error. The major advantage that a ANOVA has over a T-test is that an ANOVA can evaluate the mean differences between two or more treatments. This allows researchers much greater flexibility in experiment design, and is why we use ANOVAs and not just T-tests.
Correlation is used to measure and describe the relationship between two variables. Correlation is used with studies that have two scores per individual. Correlations are usually used to measure linear relationships (positive or negative) between two related variables. The significance of a correlation is measured by the strength or consistency of the relationship. Correlations are helpful to social scientists because we often want to know how one metric describing an individual is related to another. As an example, a question a social scientist might want to ask how does income affect levels of democracy. They could attempt to answer this question with a correlation. Through this they would gain a greater understanding of how the variables are related.
In the SDA book, they used an ANOVA to study voting tendencies of different social groups in the 2008 presidential election. An ANOVA was used because there were more than two sets of data. The election featured members of groups that were not previously part of presidential elections (African Americans and Women). This made these groups much more salient in voting tendencies. To find whether these differences where the result of a systematic difference or sampling error an ANOVA was used.