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# review chapter - Random variables Covariance and...

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Random variables Covariance and correlation Sampling Asymptotics Econ 281 - Introduction to Applied Econometrics Review - Random variables, sampling and estimation Richard Walker Northwestern University April 3, 2008 Econ 281 - Introduction to Applied Econometrics Richard Walker

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Random variables Covariance and correlation Sampling Asymptotics 1 Random variables Discrete and continuous Expected value rules 2 Covariance and correlation Covariance and variance rules Correlation 3 Sampling Estimators Unbiasedness and efficiency Estimators of other parameters 4 Asymptotics Probability limits Consistency and plim rules Central limit theorems Econ 281 - Introduction to Applied Econometrics Richard Walker
Random variables Covariance and correlation Sampling Asymptotics Preliminary note: you will not need to prove any of the following results in an exam But, you will be using them in the rest of the course; your aim should be to get ‘comfortable’ with them Econ 281 - Introduction to Applied Econometrics Richard Walker

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Random variables Covariance and correlation Sampling Asymptotics 1 Random variables Discrete and continuous Expected value rules 2 Covariance and correlation Covariance and variance rules Correlation 3 Sampling Estimators Unbiasedness and efficiency Estimators of other parameters 4 Asymptotics Probability limits Consistency and plim rules Central limit theorems Econ 281 - Introduction to Applied Econometrics Richard Walker
Random variables Covariance and correlation Sampling Asymptotics Discrete and continuous 1 Random variables Discrete and continuous Expected value rules 2 Covariance and correlation Covariance and variance rules Correlation 3 Sampling Estimators Unbiasedness and efficiency Estimators of other parameters 4 Asymptotics Probability limits Consistency and plim rules Central limit theorems Econ 281 - Introduction to Applied Econometrics Richard Walker

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Random variables Covariance and correlation Sampling Asymptotics Discrete and continuous A random variable X is any variable whose value cannot be predicted exactly Econ 281 - Introduction to Applied Econometrics Richard Walker
Random variables Covariance and correlation Sampling Asymptotics Discrete and continuous A random variable X is any variable whose value cannot be predicted exactly Can take any one of a specified set of possible values (denoted by little x ) Econ 281 - Introduction to Applied Econometrics Richard Walker

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Random variables Covariance and correlation Sampling Asymptotics Discrete and continuous A random variable X is any variable whose value cannot be predicted exactly Can take any one of a specified set of possible values (denoted by little x ) The correspondence of probabilities to possible values is known as the probability distribution Econ 281 - Introduction to Applied Econometrics Richard Walker
Random variables Covariance and correlation Sampling Asymptotics Discrete and continuous Discrete random variables A discrete random variable can take one of a finite set of discrete values Econ 281 - Introduction to Applied Econometrics Richard Walker

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