# ECO220Y1 Study Guide - Final Guide: Statistical Inference, Sampling Frame, Level Of Measurement

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16 Oct 2011
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ECO220Y LECTURE ONE SEPT 14th
Overview, Sampling, Data, & describing categorical data
Context for data values (5Ws:who,what,when,where,why)
Cases/records: rows in a database; (who)
Respondents: people who answer the survey;
Subjects/Participants: People who are experimented;
Experimental units: inanimate subjects/participants;
Observations: data values;
Variables: columns in a database; characteristics recorded about each individual or case; (what)
- Relational database;
Types of Variables (why)
Always consider the question Why do we need this variable/what do we want to know from it
Categorical variable: names categories; answer questions about how cases fall into those categories e.g.
area codes;
-- Identifier Variable: unique value for each case, for the purpose of identification (e.g. student ID)
-- Nominal Variable: only to name categories;
-- sample proportion is what matters
Quantitative variable: measures numerical values; tells quantity;
-- sample mean is what matters
Other Variable:
-- Ordinal variable
Two Types of Information
Quantitative information:
- Numerical measurements of a quantity or amount
- e.g. A 10% increase in price leads to a 10% decrease in quantity demanded;
Qualitative information:
- e.g. An increase in price tends to decrease the quantity demanded;
3 Types of Data Sets
Cross-sectional: snapshot of different units taken in the same time period;
e.g. GDP 2010 for 20 countries;
Time Series: track something over time;
e.g. Canadian GDP from 200 until 2010;
Panel (Longitudinal): A cross-section of units where each is followed over time;
e.g. GDP of 20 countries from 2000 until 2010;
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