STAT 110 A, Probability & Statistics for Engineers I

UCLA Statistics, Spring 2003

Ivo D. Dinov, Ph.D.
Assistant Professor in Statistics,
Research Scientist, Department of Neurology,
UCLA School of Medicine
Teaching Assistan(s):
  • C. Chang  E-mail:

  • Textbook:  Probability and Statistics for Engineering and the Sciences, Jay Devore, Duxbury, 5th edition (2000).
      Tentative schedule of topics to be covered
    1. Introduction: What is Statistics? Population vs. Sample, Collection of data, random samples
    2. Descriptive Statistics: Stem and leaf displays, Dotplots, Histograms, Numerical measures for center of distributions
    3. Descriptive Statistics: Numerical measures for spread, Boxplot
    4. Probability: Events, Axioms, Properties
    5. Probability: Product Rules, Permutations, Combinations, Conditional probability, Independence, Bayes theorem
    6. Discrete random variables: Probability distributions, Binomial, Negative Binomial, Hypergeometric, Poisson
    7. Continuous random variables: Probability density function, Normal distribution
    8. Continuous random variables: Normal approximation to the binomial, Exponential distribution
    9. Two random variables: Joint, marginal and conditional distribution
    10. Sampling: Simple random sampling, Sampling distribution, Central Limit Theorem (CLT)
    11. Point estimation: Bias, Efficiency
    12. Confidence intervals: CI for means and proportions on a single sample

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    Ivo D. Dinov, Ph.D., Departments of Statistics and Neurology, UCLA School of Medicine