STAT 106 – Biostatistics
COURSE SYLLABUS
| Topics |
- Introduction to Biostatistics.
- Types of data and graphical representation.
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- Descriptive statistics: Measures of Central Tendency - mean, median, mode (Excluding stem plot percentiles).
- Measures of dispersion - range, standard deviation, coefficient of variation. (Excluding stem plot percentiles).
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- Calculating Measures from an Ungrouped Frequency Table
(Excluding stem plot percentiles).
- Basic probability. Conditional probability, Concept of independence, Sensitivity, Specificity.
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- Bayes Theorem for predictive probabilities.
- Some discrete probability distributions: cumulative probability.
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- Binomial, and Poisson - their mean and variance (Excluding the use of binomial and Poisson tables).
- Continuous probability distributions: Normal distribution.
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- Standard normal distribution and t distributions.
- Sampling with and without replacement, sampling distribution of one and two sample means and one and two proportions. (Excluding sampling without replacement)
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- Statistical inference: Point and interval estimation, Type of errors, Concept of P-value. (Excluding Variances not equal)
- Testing hypothesis about one and two samples means and proportions including paired data – different cases under normality. (Excluding Variances not equal)
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Textbook: Foundations of Biostatistics, by M. Ataharul Islam and Abdullah Al-Shiha, Springer (2018).
Grading:
Midterm I: 30% Midterm II: 30% Homework’s: 20% Final Exam: 20%
Homework and exam policy
Collaboration on homework assignments is encouraged. You may consult outside reference materials, other students, the instructor, or anyone else. There is one restriction: you must write, type, or otherwise record your answers yourself, alone, so that your homework reflects your understanding. No late homework or make-up exams without prior approval; penalties may apply.
