"The Course Director was excellent and extremely knowledgeable. He made statistics easy and fun. Finally my concept and principle of Statistics are clear, and I will be able to better collaborate with statisticians. Thank you!"
Francis D., SAS Programmer, Novo Nordisk A/S
"This course gave me exactly what I needed to understand the basic statistical principles of variance that applies to my daily work. Although not in the course agenda, the Course Director was able to address questions about process control and other more lab-related data questions. I felt I got everything I needed."
Isabelle R., QC Manager, Pfizer
"The Course Director was absolutely excellent! He made statistics easy to understand and even fun and exciting! His depth of knowledge coupled with his teaching style helps make the class, and I will refer co-workers to attend. Everything covered was relevant for my day job. The Course Director was able to answer all of the questions asked and provided real-left examples. I could not more highly recommend this class to others!"
Laurie. D., Global Medical Director, Novartis Pharmaceuticals
"The Course Material and Instructor were better than other courses I've attended. CFPIE does a much better job in preparing Course Notes than other training providers I've used and has established a new standard in pharmaceutical training"
Jennifer H., Senior Clinical Data Mgr., Sepracor
This 20 hour biostatistics training course will introduce and detail the basic and intermediate statistical concepts that are essential for professionals in a biological, public health or medical environment. The first day will emphasize the principles of descriptive and inferential statistical applications while the second day will focus on actual study examples, problem solving and interpretation of clinical (efficacy and adverse events) results. Throughout the biostatistics training course, participants are encouraged to ask questions and discuss examples relevant to their own work.
The following include but are not limited to topic areas to be discussed:
The final sections of the course will cover more complex issues in research investigations and clinical trials. Topics will include:
This 20 hour biostatistics course is designed as an introduction to the statistical principles that form the basis for the design and analysis of research investigations in pharmaceutical and medical device studies. The focus of topics will benefit individuals within the pharmaceutical, biotech and device industries including R&D managers, medical investigators, basic and clinical research scientists, clinical research associates and those involved in regulatory affairs.
The course will concentrate on the philosophy and understanding of the statistical principles required in conducting sound scientific investigations with an interdisciplinary approach to trial design and analysis. It includes discussion of the topics one considers in the Statistical Analysis Plan (SAP). It will not simply present statistical formulae. Thus, the lectures are oriented toward professionals having little or no formal training in statistics or mathematics.
Those completing this course will have an understanding of the concepts and statistical methods required in biological and health science research. They will be able to interpret results related to design and analysis issues as routinely presented in the scientific literature and clinical trials.
Statistical Concepts and Terminology: Population, sample, nominal, ordinal, continuous data
Statistical Measures and Descriptive Statistics: Central tendency (average or mean, median, mode), dispersion measures such as range, variance, standard deviation, coefficient of variation, unbiased estimate
Graphical Techniques: Histograms, bar charts, box plots.
Distributions: Normal, t-distribution, skewed distribution
Inferential Statistics: Point and interval estimates of the mean and variance of a population. Hypothesis testing for the mean and variance of a population.
Risk Assessment: Relative risk, odds ratio, Bayes risk.
Defining a Sound Scientific Study: Selection criteria to statistical consideration
Single Therapy Protocols: Phase I and Phase II clinical trials, sample size and analyses, simple regression technique
Comparative Studies: Defining appropriate study hypotheses, study objectives, defining efficacy measures and endpoints (response), sample size considerations, quantitative measures, analyses (continuous and discrete data), case control studie
Data Presentation: Interpretation and discussion of results from actual clinical data computer output for categorical and continuous endpoints, p-values, statistical significance, risk measures.
Multiple Treatment Studies: Analysis of Variance (ANOVA), multiple regression Multiple Treatment Clinical Protocols: Phase III protocol sample size and comparative analyses (response and survival techniques)
Equivalence and Non-Inferiority Studies: Point and interval testing for equivalence, Non-inferiority and superiority graphical technique
Meta-Analytic Techniques: Presentation of individual patient vs. literature based meta-analyses, statistical tests of homogeneity and pooled effect size
"The Course Director was great! Very knowledgeable and engaging. I learned a great deal."
Andrea D., CRA, Medtronic
"Very good repetition of basic statistics plus new ideas for my future work. Thanks to everyone at CfPIE!"
Tom V., Scientist, GFE Blut GmbH
"The instructor answered questions with great authority which was refreshing. He used great examples which clarified material and reinforces concepts."
Caroline S., Medtronic
"The Course Director was excellent and extremely knowledgeable. He made statistics easy and fun. Finally my concept and principle of Statistics are clear, and I will be able to better collaborate with statisticians. Thank you!"
Francis D., SAS Programmer, Novo Nordisk A/S
"This course gave me exactly what I needed to understand the basic statistical principles of variance that applies to my daily work. Although not in the course agenda, the Course Director was able to address questions about process control and other more lab-related data questions. I felt I got everything I needed."
Isabelle R., QC Manager, Pfizer
"Best course I've ever taken. CfPIE continues to be a leader in pharmaceutical training. The instructor was excellent and the hotel accommodations were very nice. I am excited to use what I have learned!"
James W., Research Associate, Immuno
"The Course Director was absolutely excellent! He made statistics easy to understand and even fun and exciting! His depth of knowledge coupled with his teaching style helps make the class, and I will refer co-workers to attend. Everything covered was relevant for my day job. The Course Director was able to answer all of the questions asked and provided real-left examples. I could not more highly recommend this class to others!"
Laurie. D., Global Medical Director, Novartis Pharmaceuticals
"The Course Drector rocks! I came into this biostatistics course training knowing nothing and I'm leaving with an understanding of biostatistical concepts and methods that will help me to be conversant with my school's research team. Excellent course and instructor!"
Wendy R., Assistant Dean UMDNJ School of Nursing
"This is an excellent course. It will enable me to at least converse with the statisticians of our company and our external collaborators in a more authoritative manner."
Claude R., Scientific Affairs, Zimmer GmbH
"Just great! The Best Biostatistics training available!"
Stewart G., Research Manager, Unilever
"Great course! It explained some of the statistical mystery as it applies to my day to day work."
Souma C., Programmer, Sanofi Aventis
"The course was very helpful in reinforcing my understanding of statistical analysis as it applies to my day-to-day responsibilities in Regulatory. The class was very well organized in terms of content flow. The level of detail covered was just right for the varied audience needs."
Cheryl R., Senior Manager, Regulatory Affairs, Celltech Pharmaceuticals
"This is my first course with CfPIE and I am very pleased. The instructor does a very good job of explaining Biostats and is very easy to follow."
Sofia G., Regulatory Affairs Associate, Genzyme
"It was clear the instructor knew the information and he was genuinely interested that participants got their questions answered. Very well presented!"
Brenda R., Senior Medical Liaison, GSWA
"I definitely learned more statistics than I was expecting to. It was a pleasure listening to such a knowledgeable teacher. He was a true professional and a credit to his field.
James W., Senior Director, Talecris Biotherapeutics
"The Course Material and Instructor were better than other courses I've attended. CFPIE does a much better job in preparing Course Notes than other training providers I've used and has established a new standard in pharmaceutical training"
Jennifer H., Senior Clinical Data Mgr., Sepracor
"The instructor for this course was excellent! I have taken several courses, which include statistics, and this was the first time that I really understood some of the concepts."
Jennifer K., RN, MSN, CCRC, Bayer Diabetics Care
"The Course Director did a fabulous job of breaking down difficult concepts and presented this information in a way that was fun and tangible, and in an environment that encouraged questions from the audience. The course was well-paced and exceeded all of my expectations."
Danielle C., Director, Johnson & Johnson, PRD
"It was an excellent adventure in statistics. An excellent training conductor, great experience, and deep knowledge always gives the best results. Good conversation, good organization, etc. Thanks!"
Otava A., Doctor, Affairs AG Vienna, Austria
Yes. The course offers an overview of what the researcher needs to know to discuss sample size needs for any type of clinical trial whether it be superiority, equivalence or a non-inferiority trial.
All the statistical techniques apply to observational and non-randomized studies as well. This is especially evident when discussing the concepts of prevalence, incidence, retrospective, cross sectional, and prospective and longitudinal studies.
Topics such as multiple and logistic regression, analysis of variance and Cox proportional hazards are introduced. Interpretation of the results are presented in detail. Some prediction procedures are introduced.
There is an extensive section on the types of interim analyses performed with respect to p-value adjustment. A new section on Futility analysis has recently been introduced. Statistical motivation to continue or stop a study is presented. These are all part of the sequential design of trials.
Registrant Information:
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