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Topics for Final Exam Biostatistics 2016
Basics:
Know the meaning of standard deviation, variance, median, mode and mean.
Probability:
1. Know the addition and multiplication rules for probabilities
2. Know the formula for combinations and permutations
3. Able to do simple permutation and combination calculations
4. Understand what random variable is
Discrete Probability Distributions:
1. Know the difference between d PDF/PMF and a CDF
2. Be able to describe of the discrete distributions: Bernoulli, Binomial, Geometric and Poisson
3. Be able to give examples of processes that exhibit Binomial and Poisson distributions.
Continuous Distributions:
1. Describe four continuous distributions: Normal, Cho Square, F Distribution and t Distribution
2. Know the four basic properties of a Normal distribution
4. Be able to compute z scores
5. Be able to read off probabilities from a z score table
6. Know where the 68%, 95% and 99% are with respect to the z score and what these
percentages represent.
7. Read the paper on “Errors bars in experimental biology”
Confidence Limits and Samples:
1. Be able to define population, parameter, sample and statistic
2. Understand what the standard error measures?
4. Compute z score for a sample
5. Compute a confidence limit for a sample mean
6. Understand when to use the t distribution
7. Be able to read t distribution tables and compute confidence limits for small samples
8. Have an intuitive understanding of the central limit theorem
Hypothesis Testing:
1. Understand the basis of hypothesis testing
2. Describe what null and alternative hypotheses are
3. Understand one tailed and two tailed test
4. Carry out simple hypothesis testing on a sample mean
5. Explain what a p-value is
6. Explain what the dangers are in this type of hypothesis testing?
Other Tests:
1. Be able to compare means of paired and unpaired situations
2. Be able to carry out a simple one way analysis of variance
3. Be able to carry out a simple goodness-of-fit chi square test.
Error Propagation:
1, Know the error propagation formula
2. Be able to prove the standard error formula based on error propagation
3. Know the error propagation rules for addition, subtraction, multiplication and division
4. Compute the degree of error propagation in a given expression
Linear Regression:
1. Understand the basic principles why linear regression works
2. Know the sums of square formula (slide 30 of ppts notes)
3. Know the basic assumptions when doing unweighted linear regression
4. Know how to compute the sums of square deviations and square (slide 38)
5. Know what the SSE and MSE are
6. Know the uncertainty formula for slope and intercept (slide 52)
7. Know how to do hypothesis testing on the slope
8. Understand the meaning of covariance and correlation
9. Compute the correlation for a simple 3 data point example.
10. State the normal equation of multiple regression
11. Slide 9 in nonlinear regression slides