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In oncology research and in biostatistics in general, data lies at the center of what one does. Data is the information gathered to answer a specific research question. The data one collects typically describes the subject, the intervention, or the outcome and is either quantitative or qualitative in nature. One often summarizes the data from a population or sample based on the center of the distribution. When summarizing data from a population or sample, one also needs to know how spread out observations are. Measures of dispersion help us understand the spread of data. Another aspect that is just as important for understanding data is the visualization of the data. Seeing the data visually represented in graph form can provide new understanding and perspective, as well as provide further details for analyzing that data. This chapter explores some common types of graphs such as histograms, box plot, and scatter plot.
This book is a study guide/self-evaluation tool to prepare for the ABPN exam and MOC exam in vascular neurology. It is representative of the areas tested on the exam, including the standard clinical and basic science of stroke and some of the esoterica that appear on the exam. The book serves as a study guide for any neurologist, internist, or family practitioner interested in expanding his or her knowledge in this important field. The practice exam question-and-answer format is an effective and engaging study method, as opposed to a didactic review or summary reader. It is useful also to identify areas of weakness that require further study. The book has over 600 questions divided across fifteen sections. The fifteen sections are as follows: Basic Science; Vascular and Brain Anatomy; Clinical Pathology; Pharmacology and Pharmacokinetics; Epidemiology, Genetics, Primary Prevention; Ischemic Disease of the Brain and Spinal Cord; Hemorrhagic Disease of the Brain and Spinal Cord; Neuro-Ophthalmology; Cardiovascular Disease; Hematology; Pediatric Cerebrovascular Disease; Neurovascular Imaging; Clinical Trials and Ethics; Recovery and Rehabilitation; and Case Studies in Cerebrovascular Disease. The questions include cytotoxic edema following cerebral ischemia, internal carotid artery; cavernous malformations; thiazide diuretics; fibromuscular dysplasia; transient global amnesia; spinal epidural hematomas; ischemic optic neuropathy; atrial fibrillation; Von Willebrand disease; Perinatal ischemic stroke; cerebral microbleeds; modified Rankin scale; botulinum toxin and so on. Explanatory answers with appropriate references are included to facilitate learning. Most of the references are relatively recent, but for certain topics, the classic references, such as Niels Lassen’s work on incomplete cerebral ischemia and Anthony Furlan’s classic description of retinal ischemia presenting as visual change in bright light have been included.
The purpose of research and data analysis is to study and make conclusions about a population. Examples of populations in oncology include patients with stage III lung cancer, patients with metastatic breast cancer, or patients who receive a new chemotherapeutic agent or radiotherapy with a novel technique. Because it is often inconvenient, impractical, or impossible to study an entire population, a sample typically has to be chosen to represent the population. This representative sample is the group that will be studied to make determinations about an entire population. If the sample appropriately typifies a population, conclusions drawn about the sample may be directly applied to the population at large. The most scientifically appropriate sample is a simple random sample. Other sampling methods include probability sampling such as systematic sampling, stratified sampling, probability-proportional-to-size sampling, cluster sampling, quota sampling, minimax sampling, accidental sampling, line-intercept sampling, panel sampling, snowball sampling, or theoretic sampling.