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Lecture 1: Review of Probability & Statistics (Statistics II (Sampling…
Lecture 1: Review of Probability & Statistics
Probability
A random variable and its probability distribution
measure the shape of a probability distribution
Central tendency
mean
median
variability
variance
standard deviation
Symmetry
Skewness
Thickness and thinness of the tail
kurtosis
Two random variables and their joint distribution
distribution
Joint distribution
Marginal distribution
Conditional distribution
LIE
Law of iterated expecatations
Measures of Association
Often used probability distributions in econometrics
Normal distribution
未学 distribution
Chi-square distribution
t distribution
F distribution
Statistics I
Population, random sample and representative sample
Population and parameter
Simply random sampling and random sample
Representative sample
Exploring data and descriptive statistics
Graphical methods for describing data
Numerical methods for describing data
Introduction to STATA
Statistics II
Sampling distribution of the SAMPLE mean(average
the finite sample distribution of the sample average
the asymptotic distribution of the sample average
Estimation of the POPULATION mean
Point estimation
Set(interval) estimation
Hypothesis testing concerning the POPULATION mean
Comparing means from different populations
Recap: relationship between two variables
Graphical representation: scatter plot
Numerical representation: sample covariance and sample correlation