1. Review of Econ424 Fall 2007

2. –open book –understand the concepts –use them in real examples –Dec. 14, 8am-12pm, Plant Sciences 1129 –Vote Option 1(2) Option 2(3) Option 3 (4) Decision: Option 3 for the Excel Part, which means Do not turn in Excel file, the hard copy will ask more detailed questions to incorporate step-to-step calculation Format of Final Exam

3. Course evaluation Course Evaluation www.courseevalum.umd.edu Teaching theater evaluation www.oit.umd.edu/tt/st_fdbck.htm

4. Concepts to grasp (1) Population / sample Population –Cdf (prob(var<x)) –Pdf (first derivative of cdf) –population mean, population std. dev. Sample –Histogram, quartiles, percentiles, sample mean, sample std. dev. Population  sample –Central limit theorem xbar~N(µ, σ/sqrt(n)) Sample  Population –Xbar is a proxy of µ with noise

5. Concepts to grasp (2) Inference –Type I error, Type II error –Confidence level α –Confidence interval –Hypothesis testing H0 H1 Accept/reject? One-tail, two-tail test

6. Technical stuff Excel – midterm review SAS – notes, old exams

7. Summary of Excel (1) Basic excel –open, save and close files –cut, paste and paste special –change format for cell, row or columns –sort data by one or two variables –chart wizard –freeze panes –drag cells –use excel functions

8. Summary of Excel (2) Data description –mean, median, trimmed mean –standard deviation, variance –quartiles –mode, skewness, kurtosis –histogram (absolute frequency) –relative frequency polygon

9. Summary of Excel (3) Probability theory –PDF, CDF –mean and standard deviation –bernoulli, binomial –uniform, normal –how to simulate them in Excel? –Central limit theorem –how to see central limit theorem in excel?

10. Summary of Excel (4) Estimation and Hypothesis testing –use sample mean to estimate population mean –confidence interval –type I error and type II error –null hypothesis (H0) and alternative hypothesis (H1) –one-tail vs. two-tail –t-statistics, critical value, p-value –one-sample test –two-sample test (independent) –two-sample test (matched pair)

11. Summary of Excel (5) Linear regression –model one variable on the right hand side more than one variables on the right hand side create and use binary variables –fit of the model R square F test scatter plot correlation coefficient –coefficient estimates point estimate hypothesis testing omitted variable bias

12. Summary of SAS (1) Why do we need Excel and SAS? –What is the advantage of SAS? –What is the advantage of Excel?.sas,.log,.lst –How to edit, save, and run.sas in your machine? What commands need change? –How to generate and read.log in your machine? –How to generate and read.lst in your machine? –How to define library? What does “work” library mean? –How to find and use datasets in your library? Data newdata; set mydata; …; run; Proc … data=mydata;..; run;

13. Summary of SAS (2) How to generate summary statistics in SAS? –Proc means (for the full sample, or by groups?) –Proc univariate –Proc means with output written in a data file –Proc freq –Proc chart –Proc plot How to conduct mean comparison? –Two groups –More than two groups

14. Summary of SAS (3) How to run and read regressions in SAS? –Proc reg –Proc glm –Regressions with fixed effects? –Compare different regressions?

15. Final words Warning #1: –“Now I can use fancy and sophisticated statistics everywhere!” –Excel and SAS are tools that may be useful for your research question. Their usage should be driven by your research question, not the other way around.

16. Final words Warning #2: –“Now I am a master of statistics!” –Materials taught in this class are at most a starting point for future learning and application of statistics. –Be aware of the limitations of basic statistics. For example, a typical OLS regression requires a set of strong assumptions. Every time when you apply an OLS regression, think hard why you choose to run the regression in this way.

17. Final words Is economic statistics an art or a science? –there might be multiple interpretations for a simple statistics. Be aware of how the numbers are created and what assumptions have been made between the pure numbers and their economic meanings. –Some answers are definitely wrong, especially those that jump to the conclusion!