Welcome Message

Welcome to the CoursePlus Web site for METHODS IN BIOSTATISTICS II (140.652.01), a course offered by the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health.

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Course Description

Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations.

See the posted syllabus.

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Course Learning Objectives

Upon successfully completing this course, students will be able to:

• Discuss core applied statistical concepts and methods
• Discuss the display and communication of statistical data
• Describe the distinctions between the fundamental paradigms underlying statistical methodology
• List the basics of maximum likelihood
• List the basics of frequentist methods: hypothesis testing, confidence intervals
• Identify basic Bayesian techniques, interpretation and prior specification
• Discuss the creation and interpretation of P values
• Describe estimation, testing and interpretation for single group summaries such as means, medians, variances, correlations and rates
• Describe estimation, testing and interpretation for two group comparisons such as odds ratios, relative risks and risk differences
• Describe the basic concepts of ANOVA

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Course Time

Tue Thu   10:30 AM to 11:50 AM

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Course Faculty
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Prerequisites

140.651

Or, documented permission from Professor Louis.

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Intended Audience

Biostatistics master's students and quantitatively-oriented students from other depts

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Course Topics

See the posted syllabus.

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Grading Policy: Student evaluation based on several problem sets and one exam each term.

• See the information files.
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Textbooks Required

Lavine M (2010). Introduction to Statistical Thought

Free, on the course website and also available at:

http://www.math.umass.edu/~lavine/Book/book.html

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