Soc210 notes week 1 - Hasting PDF

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Soc 210 Spring 2019 Lecture Notes

Orestes P. Hastings

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Introductions 1. 2. 3. 4.

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Introduce myself Introduce Carolyn Each person introduces themselves to two people around them Go over the syllabus

Beginnings • What is data? – – – – –

information facts variables ”the raw material of knowledge” (p. 4) quantitative and qualitative [Give an example of each] ∗ Our focus is on the quantitative

• What is a statistic? – A simplification of the data – A description of the data • Example: At the end of this semester, why do we assign grades? – Why not show on your transcript every assignment and paper? ∗ That would be too much? – Your grade is a summary of your performance and learning in class. • Example 2: Why is a GPA? Why do we calculate it? – We want to compare students? – Is it a good measure? ∗ Has flaws. Think about the counterfactual? · What is a counterfactual? What would happen if you didn’t have it? – GPA is a statistic to summarize all of the data on how well you did in all of the assignments in all of your classes. • All statistics are flawed, at least in the sense of being incomplete. • I like to use the metaphor of a map. A map leaves out a ton of detail, but that’s what makes it useful. • What is statistics? – Procedures to organize, summarize, and communicate numerical information. – This is how we make the map. – Sometimes, to answer research questions.

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Soc 210 Spring 2019 Lecture Notes

Orestes P. Hastings

• Examples: • How does gender affect pay? – Testable claim? Women make less than men. Women make less than men because they are women? • Data? Census collects earnings data.Earnings data1 • Analysis: earning ratio of women’s median to men’s median.

• Another example: drop if not time Does income inequality reduce trust? – Claim: In states that are more unequal, people are less trusting. 1

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Soc 210 Spring 2019 Lecture Notes

Orestes P. Hastings

– Data: income data from IRS linked to a survey of people’s trust – Analysis result... • Exercise: Make up 2 personally interesting research questions. Write them down. Homework: Get the book and read Chapter 1 (pp 1-14)

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Descriptive and Inferential Statistics • From reading Ch 1 – What’s the difference between descriptive and inferential statistics ∗ Descriptive - describe the data at hand ∗ Inferential - making inferences about a population from an analysis of a sample. • Distribution of data - the number of observations that fall into each category of a variable. Handout • The first column of Table 2.2 shows country of birth of U.S. foreign born population. • Numbers are true, but not always the most useful. P roportion =

f f requency = N total

P ercentage = proportion × 100%

(1) (2)

• What % are from Mexico? Second column • Often we don’t care at all about the number. Just the %. Look at this example from the General Social Survey on subjective class identification. It’s a sample. If I say 200 poeple are working class, you’d be like, out of how many! • Make a frequency distribution of degree from Table 2.3 Category Less than HS HS BA Graduate

Tallies iiii

f 4 24 6 6 40

% 10.0 60.0 15.0 15.0 100

**Make a bar graph** • What about a variable with lots of categories, like age? • Each year could be a category or • Make categories of age

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Cumulative % 10 70 85 100

Soc 210 Spring 2019 Lecture Notes

Orestes P. Hastings

or • Histogram [Use Stata or excel to make histograms] The point here is to understand the idea of a continuos distribution

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