Lecture S1: Sample Lecture. Overview. Lecture T4: What is an algorithm? Turing machine Which problems can be solved on a computer? Not the halting problem. Here’s a question for the student to fill in the answer. Here’s the secret answer. The Main Question. P = NP. NP. P. If P NP.

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Lecture S1: Sample Lecture. Overview. Lecture T4: What is an algorithm? Turing machine Which problems can be solved on a computer? Not the halting problem. Here’s a question for the student to fill in the answer. Here’s the secret answer. The Main Question. P = NP. NP. P. If P NP.

Sample Theory Lecture. Focuses on Temporal Logics A specification language for describing properties of reactive systems Describes syntax and semantics with examples and intuition Exercises are given during lecture. Slides 16-17, 28-31. Clears common misconceptions among students.

Sample Lecture Critique (Fictitious). Introductory Lecture (#1) Prepared by R Guile King Loved the PowerPoint slides, the sounds (though they need to be louder) and the cheesy clipart.

Lecture 6 Sample Preparation. Solid Phase Extraction (Exhaustive Extraction). Analyte either ad sorps or ab sorbs to a solid support. Advantages. Large concentrations possible Limited use of solvents Very effective clean-up technique. Disadvantages. Time consuming

See Harris Ch. 28. Lecture 5 Sample preparation. Making a fine powder is often necessary before digestion of extraction. Sample digestion. All organic compounds are destroyed Toxic elements determined via atomic spectra. Harris Chapter 28. High-pressure digestion (microwave is possible!).

Lecture 6 Sample preparation. Blood Samples:. Blood: arterial capillary venous. Composition of blood plasma. Blood serum is blood plasma without fibrinogen or the other clotting factors (i.e., whole blood minus both the cells and the clotting factors). Blood Samples:.

Lecture 4 Sample size determination. 4.1 Criteria for sample size determination 4.2 Finding the sample size 4.3 Some simple variations 4.4 Further considerations. 4.1 Criteria for sample size determination.

Univariate 2-sample comparisons The biological rationale for multivariate comparisons Why not multiple univariate comparisons?. Comparison of multivariate means Evaluating assumptions Comparison of multivariate variances