Presentation on theme: "STATISTICS FOR MANAGERS LECTURE 1: INTRODUCTION BASICS OBJECTIVES."— Presentation transcript:
STATISTICS FOR MANAGERS LECTURE 1: INTRODUCTION BASICS OBJECTIVES
INTRODUCTION Statistical thinking Logical reasoning Data needed and proxies How to get the data Statistical tools Numerology
INTRODUCTION Good managers and directors get impress by intelligent comments (you can fool mediocre managers by appealing to his/her ego!!!) Grading in class: good comments and group work is also rewarded. I try to measure everything!!!
BASIC PROBLEM I Endogeneity Circularity Egg and chicken Causality and correlation: two very different concepts!!
BASIC PROBLEM I Interpretation of any graph/table implies many assumptions. However, these assumptions are almost never explicit. Assumptions for the interpretation of the previous graph? Direction Omission
BASICS II 1936 US presidential election Sampling list: mail out ballot cards to residential telephone subscribers and owners of cars. Result of the poll: Landon (republican) will win with 57% of the vote over Roosevelt (democract).
BASICS II Outcome of the election: Roosevelt won with 62.5% of the votes (523 of the 531 electoral votes!!) What happened? GROUP EXERCISE
BASICS PROBLEM II Sample selection problem. Training courses for employees. GROUP WORK
BASICS PROBLEM II Therapy of hormonal replacement for women with menopause. Does it work? Possible problem. Solution. Why did the result with observational data was wrong? GROUP EXERCISE
SOLUTION if possible Randomized experiment. Example. In business this alternative is NEVER AVAILABLE. Look for other designs: “clever” regression.
IMPORTANT!! Statistical methods are never wrong! It is their application by clumsy, un- experienced or careless researchers that makes the results wrong. Remember: if you get the design /assumptions /data right the results will always be right.
OBJECTIVES Logical thinking using statistical facts. Proper interpretation of statistical results Posing hypothesis and checking their likelihood. Sources of data.