STAT 104: Section 3 21 Feb, 2008 TF: Daniel Moon.

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Presentation transcript:

STAT 104: Section 3 21 Feb, 2008 TF: Daniel Moon

TF Office hour: Th. PM 1:00-2:00, 6 th Floor, 601

Agenda of Today Review Feedback from Hw #2 Examples from 1 st Mid-term Exam Principles of experimental design Control Randomization Replication Improvements Blocking (Stratification) Placebo Effect

Linear Regression Assumptions Residuals have en expected value 0. Residuals are uncorrelated. Residuals have the same variance. To check these assumptions: Residual plot (residuals vs. X): constant variance Normal Prob. Plot: Normality

Linear Regression Assumptions

Feedback on HW #2 When writing regression equation, don't forget y_hat, if you don't include error term. (Right: "y = a + bx + error" or "y_hat = a + bx") R is unit-free  Problem 4.e. What is r^2? (Y_hat = aX + b) One unit increase in X leads to "a" unit increase in Y. (not clear answer: for every $1 of revenue, the value of t eam goes up $2.59) (--> (It's better say) for every $1 revenue increase, ")

Examples (2007 Midterm 1)

Review Feedback from Hw #2 Examples from 1 st Mid-term Exam Principles of experimental design Control Randomization Replication Improvements Blocking (Stratification) Placebo Effect

Sources of Data Anecdotal Information Available Data Observational Studies Controlled Experiments Randomized Controlled Experiments

Elements of Designing an Experiment Subjects to be tested Observational or Randomized Experimental? How many individuals? How will the individuals selected? What kind of variables measured?

Principles of experimental design

Control

Randomization

Randomization Example

Review Feedback from Hw #2 Examples from 1 st Mid-term Exam Principles of experimental design Control Randomization Replication Improvements Blocking (Stratification) Placebo Effect

Blocking

Blocking Example

Examples (2007 Midterm 1) Physical ActivityBreast Cancer

Examples (2007 Midterm 1) Observational Study Lurking Variables Other good lifestyle habits

Examples (2007 Midterm 1)

Factors that we should consider Sample Size Individuals Experimental Design Individuals Selected Response Variable

Examples (2006 Midterm 1) Breakfast Performance

Examples (2006 Midterm 1)

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