This document provides an introduction to biostatistics and key concepts. It defines biostatistics as the development and application of statistical techniques to scientific research relating to human life and health. Some key terms discussed include:
- Population, which is the totality of individuals of interest
- Sample, which is a subset of a population
- Variables, which can be qualitative (non-numerical) or quantitative (numerical)
- Levels of measurement for variables, including nominal, ordinal, interval, and ratio scales
- Descriptive methods for qualitative data, including frequency distributions
Biostatistics plays an important role in modern medicine, including determining disease burden, finding new drug treatments, planning resource allocation, and measuring
These annotated slides will help you interpret an OR or RR in clinical terms. Please download these slides and view them in PowerPoint so you can view the annotations describing each slide.
This presentation will address the issue of sample size determination for social sciences. A simple example is provided for every to understand and explain the sample size determination.
These annotated slides will help you interpret an OR or RR in clinical terms. Please download these slides and view them in PowerPoint so you can view the annotations describing each slide.
This presentation will address the issue of sample size determination for social sciences. A simple example is provided for every to understand and explain the sample size determination.
Presentatie gebruikt tijdens de publieke verdediging van mijn proefschrift getiteld "Facilitating the use of recorded lectures, analysing students' use to understand their navigational needs" op 12 juni 2013 aan de Technische Universiteit Eindhoven.
Voor meer informatie over het proefschrift zie: http://recordedlectures.com/
Presentatie gebruikt tijdens de publieke verdediging van mijn proefschrift getiteld "Facilitating the use of recorded lectures, analysing students' use to understand their navigational needs" op 12 juni 2013 aan de Technische Universiteit Eindhoven.
Voor meer informatie over het proefschrift zie: http://recordedlectures.com/
Understanding how and why students use lecture capturesMatt Cornock
A recap of my ALT-C presentation on the research into students' use of lecture captures from a qualitative and context-centred perspective. Presentation to the TEL Research Group at the University of Liverpool. 6 June 2016.
Evaluation Unit 4
Statistics in the View point of Evaluation
Unit 4 Syllabus-
4.2.1- Measuring Scales- Meaning and Statistical Use
4.2.2- Conversion and interpretation of Test Score
4.2.3- Normal Probability Curve
4.2.4- Central Tendency and its importance in Evaluation.
4.2.5- Dimensions of Deviation
The Unit 4 is all about Statistics…
Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data.
In other words, it is a mathematical discipline to collect, summarize data.
Also, we can say that statistics is a branch of applied mathematics.
Statistics is simply defined as the study and manipulation of data. As we have already discussed in the introduction that statistics deals with the analysis and computation of numerical data.
Projective methods of Evaluation through Statistics-
Measurement is a process of assigning numbers to individuals or their characteristics according to specific rules.” (Eble and Frisbie, 1991, p.25).
This is very common and simple definition of the term ‘measurement’.
You can say that measurement is a quantitative description of one’s performance. Gay (1991) further simplified the term as a process of quantifying the degree to which someone or something possessed a given trait, i.e., quality, characteristics, or features.
Measurement assigns a numeral to quantify certain aspects of human and non-human beings.
It is numerical description of objects, traits, attributes, characteristics or behaviours.
Measurement is not an end in itself but definitely a means to evaluate the abilities of a person in education and other fields as well.
Measurement Scale-
Whenever we measure anything, we assign a numerical value. This numerical value is known as scale of measurement. A scale is a system or scheme for assigning values or scores to the characteristics being measured (Sattler, 1992). Like for measuring any aspect of the human being we assign a numeral to quantify it, further we can provide an order to it if we know the similar type of measurement of other members of the group, we can also make groups considering equal interval scores within the group.
Psychologist Stanley Stevens developed the four common scales of measurement:
Nominal
Ordinal
Interval &
Ratio
Each scale of measurement has properties that determine how to properly analyze the data.
Nominal scale-
In nominal scale, a numeral or label is assigned for characterizing the attribute of the person or thing.
That caters no order to define the attribute as high-low, more-less, big-small, superior-inferior etc.
In nominal scale, assigning a numeral is purely an individual matter.
It is nothing to do with the group scores or group measurement.
Statistics such as frequencies, percentages, mode, and chi-square tests are used in nominal measurement.
Examples include gender (male, female), colors (red, blue, green), or types of fruit (apple, banana, orange).
Ordinal scale-
Ordinal scale is synonymous to ranking or g
The material is consolidated from different sources on the basic concepts of Statistics which could be used for the Visualization an Prediction requirements of Analytics.
I deeply acknowledge the sources which helped me consolidate the material for my students.
types of variables in research, Dependent independent, moderator,quantitative qualitative,continuous discontinuous,demographic,extraneous, confounding,intervening, control
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
Ozempic: Preoperative Management of Patients on GLP-1 Receptor Agonists Saeid Safari
Preoperative Management of Patients on GLP-1 Receptor Agonists like Ozempic and Semiglutide
ASA GUIDELINE
NYSORA Guideline
2 Case Reports of Gastric Ultrasound
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
2. INTRODUCTION TO BIOSTATISTICS
Learning Objectives
By the end of this session students should be able to:
• Define terms used in Biostatistics
• Explain the significance for studying biostatistics in
medical field
• Mention the application of statistics
• Describe descriptive methods for qualitative data
3. INTRODUCTION
Biostatistics
• Development and application of statistical
techniques to scientific research relating to life
(Human, plant and Animal).
• But here the focus is on human life and health
– Pharmacology
– Medicine
– Epidemiology
– Anatomy and physiology, etc.
4. Statistics
• Branch of mathematics concerned
with collection, classification, analysis, and
interpretation of numerical facts or data,
for drawing inferences on the basis of
their quantifiable likelihood (probability).
• Statistics can interpret aggregates of data too
large to be intelligible by ordinary observation
because such data tend to behave in regular,
predictable manner
INTRODUCTION
5. Statistics
• A field which examines the collection,
organization, summarization and analysis of
data, and draws inferences regarding that
data for a population through observation of a
sample.
INTRODUCTION
6. Data
• A representation of facts, concepts or
instructions in a formalised manner suitable for
communication, interpretation, or processing by
humans or by automatic means. (Hicks [1993:
668] quoted by Checkland and Holwell [1998])
• The raw material of statistics, consisting of
numbers of measurement or counting of a
population sample.
INTRODUCTION
7. Population
• The totality of individuals or units of interest.
For example, there could be a population of
blood samples collected in a year. If the
interest is restricted to only suspected cases
of liver diseases, the population comprises
blood samples of such cases only. If the
interest is further restricted to the cases
attending OPD in a group of hospitals, the
population is also accordingly restricted.
INTRODUCTION
8. Sample
• A set of data collected and/or selected from
a statistical population. It is therefore a part
of a population obtained by a defined
procedure.
INTRODUCTION
9. Parameter
• A summary measure for any characteristic in
the target population, for example,
percentage of cirrhosis patients with high
Aspartate Aminotransferase, or rate of
increase of systolic blood pressure in healthy
subjects per year of age. The parameter
pertains to the entire population of interest
and not to the sample.
• A descriptive measure calculated from the
data of a population.
INTRODUCTION
10. Variable
• A characteristic that varies from person to
person, or from situation to situation. For
example, Platelet count in different persons is
variable but number of eyes or number of
fingers is not a variable.
• There are two main types of variable
– Qualitative variable
– Quantitative variable
INTRODUCTION
11. Qualitative variable
• Data that is not given numerically, e.g place of
birth, gender/sex, favorite of food, level of
education etc
Quantitative variable
• Given numerically. Subdivided into two types
– Discrete variable —Take specific numeric value or
number of possible values, for example, Parity for
a woman, number of patients are discrete
variables.
INTRODUCTION
12. – Continuous variable — A variable that can
theoretically have infinite number of possible
values within a short range. Age is continuous
since within 8 and 12, it can be 8.17, 10.874, 9.756
years, etc. Age can be measured in terms of days,
hours and minutes, although practically there is
no need to do this. Blood pressure is a continuous
variable but measured in integers for
convenience. Parity is not a continuous variable
because there is no possibility of it being 2.75 or
1.6.
INTRODUCTION
13. Levels of Variable Measurement
• Four levels of measurement have been
identified. These levels differ in how closely
they approach the structure of the number
system we use.
• Understanding the level of measurement of
variables used in research is important
because the level of measurement determines
the types of statistical analyses that can be
conducted.
14. • The conclusions that can be drawn from research
depend on the statistical analysis used.
• Nominal level measurement uses symbols to
classify observations into mutually exclusive and
exhaustive categories.
– Mutually exclusive means the categories must be
distinct so that no observation falls into more than
one category.
– Exhaustive means sufficient categories must exist so
that all observations fall into some category.
Levels of Variable Measurement
15. Levels of Measurement: Nominal
• This is the most basic level of measurement.
• At this level we can determine only whether
two observations are alike or different.
• Example: In a survey of teachers, sex was
determined by a question. Observations were
sorted into two mutually exclusive and
exhaustive categories, male and female.
Observations could be labeled with the letters
M and F, or the numerals 0 and 1.
16. • In the same survey the variable of marital status
could be measured by two categories, married
and unmarried.
• But, these categories must each be defined so
that all possible observations will fit into one
category but no more than one: legally married,
common-law marriage, religious marriage, civil
marriage, living together, never married,
divorced, informally separated, legally
separated, widowed, etc
Levels of Measurement: Nominal
17. • In nominal measurement, all observations in
one category are alike on some property and
differ from the members in the other category
on that property (e.g., sex, martial status).
• On ordering of categories exists. We cannot
say one category is better or worse, or more
or less than another.
Levels of Measurement: Nominal
18. • Ordinal level of measurement uses symbols to
classify observations into categories that are
not only mutually exclusive and exhaustive. In
addition, the categories have some explicit
relationship among them.
• Observations may be classified into categories
such as taller and shorter, greater and lesser,
faster and slower, harder and easier, and so
forth.
• The categories must be exhaustive and
mutually exclusive.
Levels of Measurement: Ordinal
19. • Most questionnaires use Likert type items. For
example, we may ask teachers about their job
satisfaction.
• Asking whether a teachers is very satisfied,
satisfied, neutral, dissatisfied, or very
dissatisfied is using an ordinal scale of
measurement.
Levels of Measurement: Ordinal
20. Level of Measurement: Interval
• The interval level of measurement classifies
observations into mutually exclusive and
exhaustive categories that have some explicit
relationship among them, and the relationship
between the categories is known and exact.
This is the first quantitative application of
numbers.
21. • In the interval level of measurement, a
common and constant unit of measurement is
established between the categories. For
example, measures of temperature are
interval scales.
• A temperature of 75° is one degree cooler
than a temperature of 76°; likewise, a
temperature of 32° is one degree warmer
than a temperature of 31°.
Level of Measurement: Interval
22. • Numbers may be assigned to observations
because the relationship between any two
categories is assumed to be the same as the
relationship between numbers in the number
system. For example, 76-1=75 and 31+1=32.
• Intervals between categories are equal but
they originate from some arbitrary point of
origin. No meaningful zero point exists.
Level of Measurement: Interval
23. Levels of Measurement: Ratio
• The ratio level is the same as the interval level
with the addition of a meaningful and non-
arbitrary zero point.
• Examples: Weight, area, speed, velocity. In
education, budgets and number of students
are measured on ratio scales.
24. Descriptive Methods for Qualitative
DataFrequency distribution
• A statistical distribution of subjects that displays
the number of subjects with different levels of
measurement, e.g., how many have diastolic
blood pressure <70 mmHg, how many between
70-74, 75-79, etc.
• It gives a picture of the shape of the distribution
of the data.
25. Unimodal, Bimodal and Multimodal Distribution
• Distributions of data can have few or many
peaks. Distributions with one clear peak are
called unimodal, and distributions with two
clear peaks are called bimodal. That with
more than two peaks is called multimoda data
• Frequency distribution can be displayed as a
table, bar chart, histogram or pie chat
26. What is the Role of Biostatistics in
Modern Medicine?
• Helps to determine disease burden in the
population
• Finding new drug treatment for diseases
• Planning and allocation of resources
• Used in research projects
• Used in Quality Improvement programs
• Used to measure performance outcome