lecture2-updates - Economics 10 Introduction to Statistical...

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Economics 10: Introduction to Statistical Methods Class #2 Introduction: Learning from Data

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Recap of Last Lecture Major uses of statistics: “Descriptive statistics” – more on this today! Prediction/Forecasting Evaluation How causality is assessed in the social sciences Experiments often difficult to do Rely instead on observational data, and “natural” experiments
Outline of this Lecture Data Types of Variables Types of Data “Univariate” descriptive statistics Graphical: histograms, densities, boxplots Numerical Measures of “central tendency” (e.g., mean) Measures of “spread” or “dispersion”

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Example of a Data Set Data from TN Project STAR experiment Kindergartners in TN were randomly assigned into small classes Designed to answer Q: do small classes improve academic outcomes?
Example of a Data Set Each row is an observation or case

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Example of a Data Set A variable is any characteristic of an observation Each column is a variable Variables in this data set : female: indicates whether observation is female race: describes race of observation smallk: indicates whether obs. assigned to a small class readssk: reading scale score at end of kindergarten
Types of Variables Numerical or quantitative variables Takes numerical values for which arithmetic operations such as adding, and averaging make sense Continuous: infinite possible values Discrete: integer values, generally non-negative Examples Continuous: hourly wage, GDP growth rate Discrete: hours worked, years of education

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Types of Variables Categorical variables Data are recorded as belonging to one or more groups Categories can be recoded as numbers, but numbers have no inherent meaning Example Gender: male or female Can recode female as 1, male as 0 (or vice versa) Called a dummy variable or indicator variable
Types of Variables Variables in this data set : female: categorical, coded as a dummy variable race: categorical smallk: categorical, coded as a dummy variable readssk: numerical

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Types of Data: Unit of Observation Cross-section data Data on different individuals (people, firms, countries) collected at a given point in time Notation: x i , i = 1, …, n i : some individual ( i = 2 individual #2, etc.) n = total # individuals under observation, sample size x : value (constant) that variable x takes on More common in microeconomics Example: Current Population Survey Monthly labor force survey (e.g., used to calculate the unemployment rate)
Unit of Observation Time-series data Data on the same phenomenon at different points in time (years, months, etc.) Notation: x t , t = 1, …, T t : some time period; x : some value (constant) T = total # time periods (order matters!) More common in macroeconomics

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This note was uploaded on 05/05/2010 for the course ECON 010 taught by Professor Giummo during the Spring '08 term at Dartmouth.

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lecture2-updates - Economics 10 Introduction to Statistical...

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