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

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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
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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?
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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
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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
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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)
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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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lecture2-updates - Economics 10: Introduction to...

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