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Biostatistics & Applied Statistics Education in the USA: Practical Considerations & Implications

This article discusses the structures and approaches that lead to a Master's degree in Biostatistics & Applied Statistics in the USA, as well as the role of mathematics education in the curriculum. It also provides insights into the progression of statistics education from kindergarten through high school, culminating in the Advanced Placement Statistics course. The article further explores the courses and skills required for a Master's degree in Biostatistics and the importance of statistical programming packages such as SAS.

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Biostatistics & Applied Statistics Education in the USA: Practical Considerations & Implications

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  1. Biostatistics & Applied Statistics Education in the USA: Practical Considerations & Implications Gleb Haynatzki, PhD Biostatistics Department College of Public Health U of Nebraska Medical Ctr

  2. Main Goals • Description of the structures & approaches that ultimate lead to a Master’s degree in Biostatistics & Applied Statistics in the US • Discussion of the role of mathematics education in the biostatistics master’s curriculum

  3. Background • Biostats & Appl Stats in USA has long tradition • Theoretically, it starts in kindergarden (K) & goes thru high school (12), i.e. K-12, following certain standards by NCTM (National Council of Teachers of Mathematics) • Some well-defined but rudimentary stat skills are sometimes developed in K-5 • In Gr. 6 some recognizable statistics appears: range, mean/median, bar graphs, pie ch, SRS

  4. Background (Cont’d) • Statistics skills are further developed sometimes in science and social studies classes in middle & high school • Science fair projects (on natural phenomena) for middle & high school students are another chance for working on stat & prob ideas • The first & true statistics class available to K-12 students is the AP Statistics (AP = Advanced Placement)

  5. AP Statistics • High school students obtain college credit • Doesn’t have Calculus as a prerequisite • Covers: - measures of central tendency & spread - binomial & normal distributions - simple random samples & distributions, CLT - CIs, 1- & 2-sample tests, ANOVA, nonparam - poptn proportions & contingency tables - sometimes a stat package used (eg Minitab)

  6. Stats Ed after AP Statistics – Master’s • 1) Applied Linear Statistical Models (ALSM) w/ Calculus & Lin/Matrix Algebra as prerequisites • ALSM is the fundament of the Master’s P-m: • 2) Categorical data analysis • 3) Survival data analysis • 4) Correlated/Repeated measures data analysis • 5) Design of medical studies • 6) Elected classes, eg Adv Epidemiology • 7) Capstone project on real data

  7. AP/Beginner’s Stat Calculus Multivar Stat (non-Calc, w/ SPSS) Lin/Matrix Algebra Appl Lin Stat Models (w/ SAS) Non-stat core courses Prob/Math Stat Categorical Data A (w/ SAS) Survival Data A (w/ SAS) Correlated/Repeated Data A (w/ SAS) Stat for Epi Advanced Epi Capstone Project Master of PH in Biostatistics

  8. Stats Ed after AP Statistics (Cont’d) • No Probability/Math Stats course required for Master’s in Biostats, but it helps to get in! • On real datasets/projects, a Master’s biosta-tistician can work alone or w/ a PhD statistician • Excellent skills w/ a stat package indispensable for a Master’s (or any applied) statistician • SAS is the best stat package for the US, not necessarily for Bulgaria – very expensive; try R • The road to PhD in Biostats may or may not go thru Master’s in Biostats • Many PhD in Stats students take Biostat classes

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