Download Summer 2015 statistics syllabus

PHOP 6372 (Summer 2015)
Quantitative Methods in Vision Science
Instructors:
E-mail:
Location:
Time:
Grades:
Julia Benoit, PhD and Han Cheng, OD, PhD
[email protected], [email protected]
JDA room 2321
May 19 to July 21, 2015; Tues 9:00 – 12:00 PM.
Based on average homework grades:
A (≥90), B (80-90), C (70-80), D (60 -70), F (<60)
Course description: This course introduces basic statistical reasoning and methods in analyzing
biological data. Topics include data description, elements of probability, distribution of random
variables, application of the binomial and normal distribution, estimation and confidence intervals,
hypothesis testing, contingency tables, regression, and analysis of variance. Additional topics include
introduction to statistical computing and data management using Stata 14, and distribution free statistical
methods.
Textbook: Moore and McCabe Introduction to the Practice of Statistics, 4 th edition (MM); Rosner
Fundamentals of Biostatistics 7th Edition (R).
Statistical software: Stata 14
Learning objectives:
The learning objective of this course is to understand the basic of statistical concepts and methods for
summarization and elementary analysis of biometric data. Specifically:
1. to recognize different types of observations and to summarize data using a variety of approaches,
including table and summary statistics, and to present data using various types of graphics;
2. to be able to formulate statistical problems in the terminology of probability, understand random
variables, Binomial, Poisson and Normal distributions, expectation and variance of both discrete
and continuous random variables;
3. to understand the distribution of the mean, confidence interval for one sample and computation
of sample size;
4. to be able to formulate statistical hypotheses and basic hypothesis testing, and be able to conduct
one-sided and two sided tests about the mean;
5. to understand one-way analysis of variance;
6. to know how to do simple linear regression, analysis of correlation, and ANCOVA;
7. to be able to carry out most statistical analyses discussed in the course with Stata.
Course Schedule
Week 1 (May 19). R Ch 2; MM Ch 1
Data distributions, descriptive statistics, Introduction to Stata.
Measures of location: mean v. median; Measures of spread (scale). Sample variance, standard deviation;
choosing descriptive; graphical displays of shape: stem-and-leaf, box plots
Week 2 (May 26). R Ch 3; MM Ch 4
Probability
Sample space, probability definitions and axioms, assignments of probability, law of total probability,
Bayes’ rule, screening, sensitivity/specificity, risk ratio, predictive value
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Week 3 (June 2). R Ch 4; MM Ch 4, 5
Random variables, discrete random variables and probability distributions, Binomial distribution, Poisson
distribution, CDF
Expected value and variance of binomial and Poisson, parameters versus estimates of parameters,
Week 4 (June 9). R Ch 5; MM Ch 4, 5
Random variables, normal and standard normal distributions, probabilities from Normal distribution
Convert from normal to standard normal (z-scores)
Week 5 (June 16). R Ch 6; MM Ch 5
Sampling distribution
Sampling distribution of the mean, standard error, interval estimation, Confidence Intervals (CI), CI to
evaluate hypothesis.
Week 6 (June 23). R Ch 7
Hypothesis Testing-One Sample Inference
One sample t-test, power, sample size
June 22: Midterm Exam
Week 7 (June 30). R Ch 8, 12
Paired t-test, two sample t-test, Multi-sample: Analysis of Variance (ANOVA),
Interval estimation for comparison of means, two sample t-tests for independent samples with equal
variances and unequal variances, sample size/power calculations for two-sample comparison of means.
Week 8 (July 7). R Ch 11
Linear correlation, Spearman correlation, simple linear regression (SLR)
Scatter plots, Pearson’s v. Spearman correlation, SLR assumptions, residuals, predictions and forecasts
Week9 (July 14). R Ch 9, 11, 12
Two-way ANOVA, ANCOVA. Multiple regression, Non-parametric statistics
Regression diagnostics, Wilcoxon signed rank test, Wilcoxon rank sum test; categorical data methods
Week 10 (July 21)
Final Take-home exam due
SPECIAL ACCOMMODATIONS:
The American with Disabilities Act (ADA) of 1990 requires the University to make reasonable
accommodation to persons with disabilities, as defined in the act. Students who feel they need assistance
under the ADA guidelines should approach the instructor to discuss such consideration.
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