Basic of scientific Research 2023-2024 PDF

Faculty of Applied Health Sciences Technology Basic of scientific Research For 2nd year students 2023 - 2024 By Dr. Ghadeer Maher Elsheikh...

Faculty of Applied Health Sciences Technology Basic of scientific Research For 2nd year students 2023 - 2024 By Dr. Ghadeer Maher Elsheikh Assistant professor of public health and community medicine Dr. Nehad Badr Abd Elaty Assistant professor of public health and community medicine  Intended Learned Outcomes (ILOs) I - Knowledge and understanding By the end of this course, students should be able to  Define research and list its components  Define statistics, its functions and describe different types of data  Define sources of data collections and different sampling techniques  Define different methods of data presentation; also describe different shapes of distribution of data II – Skills By the end of this course, students should be able to  Identify different types of data and convert it from type to type  Modulate different types of samples and define its proper use  Acquire the skills to present data in its different forms (tabular, graphical and mathematical)  Identify test of significance appropriate of each type of data  Criticize different research manuscripts III – Attitude By the end of this course, students should be able to  Perceive the importance of research and statistical analysis in practical life.  Contents Research Methodology....................................................................................................................... 5 Epidemiological Study Designs............................................................................................................ 16 Analytic Studies............................................................................................................................ 20 Cross-Sectional Study (Prevalence study)......................................................................................... 20 Retrospective study (Case control study)........................................................................................... 21 Prospective study (Cohort study)...................................................................................................... 23 Interventional studies........................................................................................................................ 26 Medical statistics.................................................................................................................................. 30 Sampling Techniques.................................................................................................................... 36 Non-probability or Non-random........................................................................................................ 36 Probability or Random....................................................................................................................... 37 Methods of presentation of data................................................................................................... 43 References.................................................................................................................................... 59 Contents  ‫فلسفة الكلية والقيم الحاكمة‪:‬‬ ‫‪ ‬االلتزام االجتماعي واألخالقي وترسيخ قيم العدل والمساواة والمثل االنسانية العليا‪.‬‬ ‫‪ ‬االنتماء الوطني الصادق للطلبة والعاملين ووضع المصلحة العامة فوق أي مصالح شخصية‪.‬‬ ‫‪ ‬عدم التمييز بسبب اللون أو النوع أو الدين أو الجنسية ‪.‬‬ ‫‪ ‬الرؤية العالمية والتواصل مع األخر إقليميا ً و عالميا ً‪.‬‬ ‫‪ ‬الشفافية مع عرض اإليجابيات والسلبيات أمالً في التطوير والتحسين المستمر‪.‬‬ ‫‪ ‬الحرية الفكرية واألكاديمية في إطار الثوابت المجتمعية والقيم الجامعية ‪.‬‬ ‫‪ ‬الجودة والتميز مع السعي الدائم لتطوير العملية التعليمية والبحث العلمي‪.‬‬ ‫‪ ‬المشاركة المجتمعية والمساهمة في خدمة المجتمع وتنميته ‪.‬‬ ‫رؤيــة الكليــة‬ ‫كلية رائدة تتميز بتخريج تكنولوجي صحى ذو كفاءة عالية قادر على المنافسة في سوق العمل محليا ً وإقليميا ً‬ ‫لالرتقاء بمستوى الخدمات الصحية‬ ‫رسالــة الكليـة‬ ‫تخريج تكنولوجي صحى‪ ,‬ملتزم باألخالقيات المهنية متقن للمهارات التقنية المتخصصة التى تؤهله للمساعدة فى‬ ‫تقديم رعاية صحية متميزة وأمنة مبنية على االدله والبراهين تخدم مختلف المؤسسات الصحية‪ ,‬وأن يكون الخريج‬ ‫قادر على المشاركة في البحث العلمى وخدمه المجتمع ومهيأ للتعليم المستمر والعمل الجماعى متمتعا بمهارات‬ ‫االدارةمن خالل تقديم برامج متنوعة تلتزم بمعايير الجودة التعليمية‪.‬‬ ‫االهداف االستراتيجية‪:‬‬ ‫‪ ‬اعداد تكنولوجي صحي متميز بمهارات علمية متقدمة الي جانب االهتمام بالمهارات الشخصيه‬ ‫‪ ‬ربط مهارات الخريج ومواصفاته بمتطلبات سوق العمل‬ ‫‪ ‬تأهيل الخريجين وتدريبهم علي سبل التعلم الذاتي والتعلم المستمر‬ ‫‪ ‬االهتمام بالبحث العلمي وربطه بالتقدم التكنولوجي وحاجات سوق العمل‬ ‫‪ ‬التطوير المستمر في برامج الكلية لمواكبة التطور التكنولوجي السريع‬ ‫‪ ‬عقد بروتوكوالت تعاون مع العديد من المؤسسات والشركات التي تخدم تدريب الطالب باألقسام المختلفة‬ ‫‪ ‬التوسع في تطوير المعامل والورش بالكلية‬ ‫‪ ‬تطوير البنية التحتية لتسهيل طرق التعلم االلكتروني والتعلم عن طريق المحاكاة‬ ‫‪ ‬انشاء دبلومات تأهيلية ودراسات عليا لخريجي الكلية‬  Research Methodology Intended Learned Outcomes (ILOs) I - Knowledge and understanding By the end of this course, students should be able to  Define research and list its components II – Skills By the end of this course, students should be able to  How to write a final report  Criticize different research manuscripts III – Attitude By the end of this course, students should be able to  Perceive the importance of proper formulation of final report in documentation of research work.  Research Methodology What is research? Research is the systematic collection, analysis and interpretation of data to answer a certain question or solve a problem. Steps of conducting a health research: A. Prioritizing and selecting a research topic B. Review of literature and other existing information C. Development of a research proposal D. Implementation of study:  Data collection  Data processing and analysis  Interpretation of results  Final report writing  Presenting the results A. Prioritizing and selecting a research topic Criteria for selecting a research topic:- 1. Relevance: The topic you choose should be a priority problem. Questions to be asked include: How large or widespread is the problem? Who is affected? How severe is the problem? 2. Avoidance of duplication: Before you decide to carry out a study, it is important that you find out whether the suggested topic has been investigated before. B. Literature review Why is it important to review already available information when preparing for a research? - It prevents you from duplicating work that has been done before. - It helps you to find out what others have learned and reported on the problem you want to study. - It should provide you with convincing arguments for why your particular research project is needed. C. Development of a research proposal Contents I. Title of the research II. Introduction: Background information III. Research objectives IV. Methodology V.Work plan VI. References VII.Annexes I. Title of the research  A good title should be short (10-12 words), accurate, and concise.  It should Clearly related to the purpose of the study  It is important to specify what population will be investigated, and where it will be conducted.   Avoid beginning with redundant words such as (A study of ….) II. Introduction (Background information and Statement of the research problem) The purpose of the introduction is to provide background information which is pertinent to the study.The statement of the research question is most important part of the introduction. It needs to be short and concise. The content of the introduction include:  Importance of the topic  What is known about the topic  What is still unknown or problematic  Findings of relevant studies ( past verb tense )  Statement of the research question  What are the questions that are outstanding and need answer? III. Research Goals and Objectives Goals It describes the aim of the work in broad terms Objectives The research objectives should be:  Ordered in a logical sequence  Stated in action verbs that could be evaluated e.g. to describe, to identify, to measure, to compare, etc. SMART Objectives  S ------------ Specific  M ---------- Measurable  A ---------- Achievable  R ---------- Relevant  T ---------- Time-bound IV. Methodology It is necessary to identify the variables that will be involved in the research being designed. Three types of variable are important: Independent (predisposing/risk factors), Dependent(outcome/disease) and Confounding variables. It is also necessary to specify whether these variables are Numerical(continuous/discrete), or Categorical (ordinal/nominal). Definition of variables should be clearly phrased. V. Work plan It should include: 1. The various tasks to be performed 2. When the tasks will be performed 3. Who will perform the tasks VI. References The references in your text can be numbered in the sequence in which they appear in the report and then listed in this order in the list of references (Vancouver system). VII. Annexes These may include: - Interview schedule/ questionnaires (and/or other data collection tools). - Informed consent form - Institutional/Ethical approval for the study D. Final Report Writing Main components of a research report: I. Title or cover page II. Abstract III.Introduction IV.Objectives V. Methodology VI.Research results (findings) VII. Discussion VIII. Conclusions IX. Recommendations X. References XI. Annexes or appendices (data collection tools, tables) I. Title or Cover page Cover page includes: research title, names of the authors with their titles and positions, and the institution that is publishing the report. II. Abstract In very few words (200-300) the abstract should inform about the main aspects of the manuscripts. Characteristics of an abstract - a very brief description of the problem (WHAT) - the main objectives (WHY) - the place of study (WHERE) - the type of study and methods used (HOW) - major findings and conclusions - the major recommendations - no references, tables or figures,no abbreviations. III. Introduction It should certainly contain some relevant background data related to the problem, then the statement of the problem should follow. It should contain an explanation of the fundamental reasons for your research. IV. Researchobjectives The general and specific objectives should be included as stated in the proposal. V. Material and Methods This section is descriptive using the past verb tense. Subheadings should be used. 1. Subjects  Methods of sampling  Sample size estimation  Inclusion and exclusion criteria 2. Variables  Independent, dependent, controlled. 3. Pilot studies 4. Materials  Equipment and measurement tools 5. procedures  Detailed description, in chronological order in exactly what was done and by whom. 6. Ethical considerations 7. Statistical methods (packages, software..) VI. ResearchResults It is important to plan which results are essential for answering question(s) posed in the introduction irrespective of whether or not support the hypothesis. The order of presentation of the results should be either chronological or from the most important. It is important that tables and figures have strong visual impact, are informative and easy to understand. Readers must be able to interpret them when stand alone. The results must not include discussion of the findings, methods of data analysis and citations of references. Tables Express in a tabular way concise results Use tables to highlight individual values. Check your math. Keep lines to a minimum; avoid vertical lines. Use footnotes to clarify points of potential ambiguity. Check heading, labels of rows/columns/axes, and footnotes.  Do not forget the units of the headings.  Do no repeat any information in tables and figures.  The table should contain at least 2 x2, rows x columns. Figures  Figure = figure legend + axes + units + content  Use figures to highlight trends/relationships.  Avoid grids, lines, frames, and legends inside the drawing.  Use common symbols, clear and neat within the traces.  Cite the reference in the figure legend.  The measured variable is labeled on the Y axis while the categorical variable is labeled on the X axis. VII. Discussion Contents of the discussion (present verb tense)  Answer to the question(s) posed in the introduction together with any support and defense of the answers with reference.  Explanation of unexpected findings.  Clinical significance and importance of findings.  The recommendations should follow logically from the findings. VIII. Conclusions This section should comprise a brief statement of the major findings and implications of the study. IX. Recommendations - The recommendations should follow logically from the discussion of the findings. - Recommendations may be summarized according to the groups towards which they are directed, for example: Þ policy-makers Þ health and health-related managers at different levels Þ health and health-related staff who could implement the activities Þ potential clients Þ the community at large Recommendations may involve: Methods, procedures or approaches for solving particular problems, Further work or actions or research to be completed X. References The system of citing reference material in scientific journals varies with the particular journal. The name(s) of the author(s) and year of publication or numerical sequence 1,2are included in the body of the text of your paper. XI. Annexes OR Appendices These may include:- - Interview schedule/ questionnaires (and/or other data collection tools). - Informed consent form - Institutional/Ethical approval for the study Verb tenses Present:Directives, conclusions, generalities, stable conditions. Past: Procedures, results, finished statements.  Research Methodology exercise Describe the basic criteria for the following 1- Research title ………………………………………………………………………………… ………………………………………………………………………………… 2- Abstract of the research ………………………………………………………………………………… ………………………………………………………………………………… ………………………………………………………………………………… 3- Research objectives ………………………………………………………………………… ………………………………………………………………………… …………………………………………………………………………. List groups to which you direct your recommendations ………………………………………………………………………………… ………………………………………………………………………………… ………………………………………………………………………………… ………………………………………………………………………………….  Epidemiological Study Designs Intended Learned Outcomes (ILOs) I - Knowledge and understanding By the end of this course, students should be able to  Describe different types of epidemiological studies  Know assumptions for different studies  Know advantages and disadvantages of different studies II – Skills By the end of this course, students should be able to  Select the appropriate design for different research  Solve problems about study designs III – Attitude By the end of this course, students should be able to  Respect selection of appropriate study designs to get proper answer to research questions  Epidemiological Study Designs Epidemiological studies may be descriptive or analytical; - Descriptive studies look at the distribution of a disease or health problem ina community. - Analytical studies look at the determinants (i.e. factors enhance or inhibit) occurrence of diseases in populations. Types ofepidemiological study design: I- ObservationalStudies: A. Descriptive studies: B. Analytic studies:  Case report Case-control study  Case series Cohort study  Correlation study Cross-sectional study  Cross-sectional study II- Experimental (interventional) Studies  Preventive trials  Clinical trials  Population trials  A. Descriptive Studies Describe general characteristics of distribution in relation to time, place and person (the basic triad of descriptive epidemiology)  Personinclude distribution by age, sex, race, and marital status, and occupation, life style variables as food, smoking and medicine … etc  Placerefer to geographical distribution of disease, urban, rural, countries variation.  Time include secular trend, seasonal variation. It is the first clue for disease determinant in order to formulate hypothesis. a- Case report: is a detailed report of the symptoms, signs, diagnosis, treatment, and follow-up of an individual patient. Case report may contain a demographic profile of the patient, but usually describe an unusual or novel occurrence. b- Case Series: is a type of medical research study that tracks subjects with a known exposure, such as patients who have received a similar treatment, or examines their medical records for exposure and outcome.  B. Analytic Studies 1- Cross sectional study 2-Case control study 3-Cohort study Cross-Sectional Study (Prevalence study) Study which give an answer to the current situation at a given point in time. Cross-sectional study is mainly a descriptive study but may be analytic if the relationship between disease and risk factor is done during analysis and distribution of disease in relation to time, place and person. Both exposure (risk factors) & outcome (diseases) are present. Therefore, we cannot determine if exposure preceded disease or not. It measures prevalence (all cases), not incidence (= new cases) of disease Not suitable for studying rare or highly fatal diseases or a disease with short duration of expression (acute diseases) Subjects and methods: The whole population if confined may be taken or representative sample if the target population is large. No controls are used in cross sectional study. Examples: 1. Census 2. Survey study 3. Screening test Advantages: 1. Measure population sample characteristics 2. Determine disease prevalence. 3. Can study multiple risk factors and multiple diseases at the same time. Disadvantages:Show associations but do not indicate causal relationships. Retrospective study (Case control study) In a retrospective study, persons who diagnosed as having a disease (cases) are compared with persons who do not have the disease (controls); with regard to their past exposure to the possible risk factor of interest. Advantages: 1- The number of subjects can be small. 2- Results can be obtained relatively quickly. 3-Low cost. Disadvantages: 1. Selection bias: error in selection of cases and controls. 2. Information bias:- unavailable or inaccurate records. 3. Recall bias:- inaccurate recall of events in the distant past 4. Confounding bias:- there are variables that increase or decrease the association between the disease and the factor under study. 5. Yields:- only an approximation of relative risk (odds ratio) but can not measure incidence (no population base). Uses: Particularly useful for etiologic study of rare diseases (high exposure) First select Past exposure Cases Controls Exposed A B Not exposed C D Total a+c b+d The proportion of exposed among cases (a/a+c) and among controls (b/b+d) are calculated and compared for statistical analysis. Odds ratio: Odds Ratio = odd of exposure among cases / odd of exposure among controls Odds Ratio = a/c / b/d = ad/bc Interpretation of the odds Ratio (OR): OR = 1 indicate that there is no association between exposure and disease development. OR > 1 indicates that the exposure is risky. OR < 1 indicate that the exposure is protective. Prospective study (Cohort study) A cohort study starts with 2 groups of people (cohort) free of the disease under study, one group is exposed to a risk factor and the other one is not. Both groups of cohort are followed over time to determine differences in the rates of disease development (or rate of death from disease). A cohort is a group of persons who share a common attribute (feature or experience) e.g. a birth cohort are person born in the same year in same period of years. Types of cohort study:- a. Concurrent prospective cohort study. b. Non- Concurrent prospective cohort study or historical study or retrospective cohort study: - in this study, exposure has been started in the past and documented in records. This type of design is used to reduce the duration of the study. Exposure is detected in the past and measurement of development or non-development of disease is ascertained at the time when study begins or followed longitudinally from time of start of research for more time in the future. Advantages: 1. Lack of bias in ascertaining the exposure, since cohort is classified as to the state of exposure before the disease develops. 2. Permits calculation of incidence rates, thus both relative risk and attributable risk can be calculated. 3. Permit observation of development of additional diseases as by product e.g effects of Chernobyl nuclear explosion. Disadvantages: 1. Require large number of subjects.  2. Long follow up period. 3. Attrition: - (loss of subjects from follow up) because of disinterest, migration, or death from other causes or potential loss of staff and/or funding. 4. Potential change of exposure status of subjects over time. 5. Changes in diagnostic criteria and methods over time with advances in technology. 6. Very costly. Uses: Particularly useful to study outcome when exposure is rare, but incidence among exposed is high. See the illustrated table to clarify the sequence of events in the prospective study: Current exposure Disease No disease First select Exposed A b Not exposed C d Total a+c b+d  Interventional studies 1- Clinical trial Clinical trial It is an experimental study that is designed to compare the therapeutic benefit of two or more treatments (testing for new treatment or vaccine). The purpose of clinical trial is to compare a new agent, drug or vaccine with a traditional one with regard to its:- 1. Effectiveness. 2. Safety (toxicity and side effects). 3. Cost-effectiveness. The clinical trial is a prospective study with two differences:- Prospective study Clinical trial 1. Subjects select themselves for 1. Randomization:- The investigator exposure or non-exposure to randomly determines who will be the factor exposed (treated) or not 2. No blinding is applied 2. Blinding is applied Blinding should be applied whenever possible since lack of blinding could influence perception of outcome and reduce confidence in the study result. Blinding may be: 1. Subject under investigation...........................single blind 2. Subject and data collector............................. double blind 3. Subject + investigator+ data analysts.............. triple blind Blindness can be achieved by using a similar shape or color and taste…or using placebo. Problems encountered include: 1) Ethical issues 2) Non participation, attrition or non-compliance. 3) Correctly defining inclusion and exclusion criteria. 4) Sample size. 5) Expenses. 6) Long period of follow up  Study design exercise Best study design for calculating the following: -Incidence………………………………………………….. -Prevalence…………………………….…………………… -Rare disease………………………….……………………. -Rare exposure…………………………………………….. In a survey of 2000 persons during the month of march 2010 in Menoufia governorate, a total number of 250 persons showed +ve results of hepatitis C by blood investigations. 1- What is the type of this study? ………………………………………………………………………. 2- Can you calculate the prevalence? ………………………………………………………………………. In a study congenital hypothyroidism in 2009, all the mothers of 50 children aged 1-5 years were interviewed in Quiesna and Berket El-sabaa. A control group of mothers of 100 children were chosen from the same regions. Patients Control Total Medical History of the (n=50) (n=100) (n=150) mother No % No % No % Gestational Diabetes mellitus Yes 6 12.0 3 3.0 9 6.0 No 44 88.0 97 97.0 141 94.0 1- What is the type of this study? ………………………………………………………………………. 2- Which one of the measurement of risks you can calculate? ……………………………………………………………………….  In a study of 1000 persons in 2003 working in Menoufia governorate hospitals, radiology department, for early detection of cancer, they were free at that time. Another group of 1000 persons were chosen from the other departments then both groups were followed up until 2010. A total number of 25 persons showed +ve results of cancer by investigations in radiology department opposite 5 persons from the other departments. 1- What is the type of this study? ………………………………………………………………………. 3- Can you calculate the incidence rate? …………………………………………………………………………. 2- Which one of the measurement of risks you can calculate? ………………………………………………………………………. - Calculating odds ratio from the following table: Smoking Lung cancer cases Controls Smokers 16 8 Non-smokers 2 24 Total 18 32 Odds Ratio=--------------------------------------------------------------------------------- ------------------------------------------------------------------------------------------------ - Your interpretation ------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------  Medical statistics Intended Learned Outcomes (ILOs) I - Knowledge and understanding By the end of this course, students should be able to  Define statistics, its functions and describe different types of data  Define sources of data collections  Define different methods of data presentation; also describe different shapes of distribution of data II – Skills By the end of this course, students should be able to  Identify different types of data and convert it from type to type  Acquire the skills to present data in its different forms (tabular, graphical and mathematical) III – Attitude By the end of this course, students should be able to  Perceive the importance of statistical analysis in research work.  Medical statistics Medical statistics is the science of collecting, presenting, analyzing and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. Functions of Statistics: 1. Presentation of data in a definite and simpleform. 2. Comparison of health status: - of different localities, and in one locality at different times. 3. Diagnosis of a health problem in the community 4. Evaluation of any health program: e.g. vaccination programs. DATA Definition: Set of values of one or more variables recorded in one or more observational units or numerical description of quantitative or qualitative aspects of things. Types of data 1- Constant: Observation which does not varies from one person to another, E.g. number of chromosomes in a gene. 2- Variables: Observation which vary from one person to another. Variables 1. Quantitative variables:are expressed in numbers. They are either continuous or discontinuous. 2. Qualitative variables Also known as categorical variables, qualitative variables are variables with no natural sense of ordering. They are therefore measured on a nominal scale.  For instance, hair color (Black, Brown, Gray, Red, and Yellow) is a qualitative variable, as is name (Mohamed, Ali, Adam, Mona, ….). - Qualitative variables may be divided in to: nominal or ordinal. Continuous quantitative variable Discrete or discontinuous quantitative variable a. Always obtained by measurement a. Always obtained by numeration. b. The values may take the integer b. The values take the form of figures or fractions e.g.: weight, height, integer figure (no fractions): e.g. blood sugar, urea, blood cholesterol, blood cells, number of microbes /cc, Hb %. respiratory rate, number of beds in a hospital. Nominal Ordinal / rank Variables whose categories cannot be put Variables whose categories could be in any order e.g.: arranged in a definite order: e.g 1. Sex: male or female 1- Educational level: 2. Marital status: single, married, divorced, a. illiterate, widowed. b. basic education, 3. Blood groups: A, B, AB, O c. secondary, 4. Color of skin d. university 5. Color of the eye 2- Socioeconomic status: 6. Religion. *high *middle *low. - Sometimes, quantitative variables could be transformed into qualitative one: 1. Blood pressure could be expressed in numbers as: Quantitative qualitative ones  100/60............................... hypotension  120/80............................... normotension  180/100............................. hypertension. Data collection Data collection is the process of gathering and measuring information on targeted variables in an established systematic fashion, which then enables one to answer relevant questions and evaluate outcomes. Methods of data collection: 1. Historical records: e.g. a. Censuses b. Vital statistics records c. Epidemiological records d. Scientific journals and textbooks 2. Experimental. 3. Conducting surveys: a. Comprehensive surveys b. Sample surveys A- Comprehensive Surveys: The data are collected from every member in the community. This method is used for a small community e.g. a school, a village or a factory. B- Sample survey: - The sample must be representative. In this method, the sample is collected from the population and the required data are collected from the sample members. Then, the results can be generalized over the whole population. - Characteristics of the sample: 1. The sample must be well chosen to be representative to the parent population. 2. The sample must be sufficiently large.  Exercise Define: Statistics………………………………………………………………………… ……………………………………………………………………… …………………………………………………………………………… …………………………………………………………………………… Data……………………………………………………………………………… …………………………………………………………………… …………………………………………………………………………… …………………………………………………………………………… Types of data …………………………………………………………………………… …………………………………………………………………………… …………………………………………………………………………… …………………………………………………………………………… Complete: 1. Gender is.............................................. data 2. Socioeconomic level is......................... data 3. RBCs count is...................................... data 4. Age is.................................................. data 5. Urea and Creatinine are….................... data  Sampling Techniques Intended Learned Outcomes (ILOs) I - Knowledge and understanding By the end of this course, students should be able to  Define different sampling techniques  Describe advantages and disadvantages of different sampling techniques II – Skills By the end of this course, students should be able to  Modulate different types of samples and define its proper use  Select proper sampling techniquesfor different situations III – Attitude By the end of this course, students should be able to  Perceive the importance sampling in research field.  Sampling Techniques Sample: - a part of a population, generally selected so as to be representative of the population in the variable(s) under study. Sampling: - is a mandatory in researches as comprehensive studied are generally impractical. - Advantages of sampling over a comprehensive survey: 1. Lower cost 2. Greater speed 3. Greater information 4. Sometimes the sampling is imperative when the comprehensive survey is impossible; e.g. collection of data about fish, animals, nomadic population; data collection in testing the quality of certain industrial products e.g. matches lamps. Another example is the examination of blood of patients. Types: I. Non-Probability OR Non-Random samples II. Probability OR Random samples Non-probability or Non-random Types a. Purposive samples: They are chosen according to one's own judgment: i.e. not chosen in a random way and thus one can not generalize their results. b. Pre-test or pilot study: It is used in pre testing the studies so as to avoid missing of important parameters and to exclude any unnecessary variables from the start, and thus saving time, money and personnel. c. Quota sample: It is used in especially in the U.S.A by Gallup Institute prior to voting. The investigator is asked to obtain the required information from a number of specific individuals (classified in different groups). This method of sampling is of no use in community medicine or clinical practice.  d. Convenience sample is one of the main types of non-probability sampling methods. A convenience sample is made up of people who are easy to reach. Disadvantages of non-probability samples: 1. Probability of selection cannot be determined 2. The standard error of the sample mean cannot be estimated 3. The sampling results cannot be generalized Probability or Random Characteristics: 1. The probability of selection of an individual from the population can be determined. 2. The standard error of the sample result can be computed. 3. Generalization of the sample results over the total population can be made. Types of probability samples: 1. Simple random sample 2. Systematic random sample 3. Stratified random sample 4. Multi-stage random sample 5. Cluster sample 1. Simple random sample Methods of selection: 1. Method of ideal bowl: Serial no. Name 1 2 3 - We make a frame as shown in this figure. - Use a number of paper cards equal to the population size. - Each of these papers will bear a serial number taken from the frame. - All these papers must be similar in every respect in order to avoid bias. - All these papers must be folded in the same manner and put in the ideal bowl, then thoroughly mixed before selection. 2. Tossing a coin. 3. Taking random balls: each of which represents a member of the population, out of a container after proper mixing. 4. Computer: by generating random numbers. Advantages Simple random sample: 1. It is considered the basic type of probability samples. 2. Every member of the population has an equal chance or probability of being selected. Disadvantages Simple random sample: 1. Construction of the frame may be difficult, especially when the population size is large. 2. The sample members may be concentrated in a certain sector of the population e.g. all members may be females. 3. It is not suitable for population of great variability [as the standard deviation is high and the degree of precision is low 2. Systematic random sample Methods of selection: If we have a population of 100 individuals and we want a sample of 10, we can select any number between 0 and 10 at random, say 4. Then we go on taking individuals of numbers 4, 14, 24, 34, 44, 54, 64, 74, 84, 94. This will constitute the sample. Advantages: 1. Ease of selection. 2. It is well distributed over various populations. 3. The degree of precision of its results is better than simple random sample. Disadvantages: 1. Difficulty in constructing the frame if the population is large. 2. Sometimes, we cannot obtain the required sample size, which may be smaller than the required e.g. if the population size = 11 and the sample size = 4: if the first chosen number is number 2, we can obtain the required sample size [2,5,8,11]. But, if the first number is number 4, the sample size will be 3 instead of 4 [4, 7, 10]. 3. Stratifiedrandom sample  This is the best type of probability sample, particularly if there is a great variability among the population members i.e. if the value of the SD is high. Where population divided into a number of distinct categories, the frame can be organized into separate "strata." Each stratum is then sampled as an independent sub-population, out of which individual elements can be randomly selected. Advantages: 1. Every unit in a stratum has same chance of being selected. 2. Using same sampling fraction for all strata ensures proportionate representation in the sample. 3. Adequate representation of minority subgroups of interest can be ensured by stratification. The general principle is to divide the population into a number of strata fulfilling two conditions: a) Each stratum should be homogeneous as possible.  b) Each stratum should be exclusively sharply defined. - Examples of Bases of stratification of population: Socioeconomic standard According to occupation According to educational level - High - Professional - Illiterate - Middle - Semi-professional - Read and write - Low - Skilled workers - Basic education - Semi-skilled workers - Secondary - Unskilled workers - Higher education Disadvantage: 1. sampling frame of entire population has to be prepared separately for each stratum 2. Second, when examining multiple criteria, stratifying variables may be related to some, but not to others, further complicating the design, and potentially reducing the utility of the strata. 3. In some cases (such as designs with a large number of strata, or those with a specified minimum sample size per group), stratified sampling can potentially require a larger sample than would other methods. 4. Multistage random sample We use this type of sample if there is a very large population. Method  First stage: A list for all the governorates is made.  Second stage: select a sample of two governorates by simple random method.  Third stage: select random number of districts chosen in all states.  Forth stage: select random number of talukas, villages.  Fifth stage: units will be houses. — All ultimate units (houses, for instance) selected at last step are surveyed. Advantages: 1. Construction of the frame is always very easy unlike the previous three types of samples. 2. It is the most suitable sample type to be used for selecting a sample representing the whole country e.g. for choosing a representative sample from the Egyptian population. 3. Cost and speed that the survey can be done in 4. Convenience of finding the survey sample 5. Normally more accurate than cluster sampling for the same size sample Disadvantages: 1. Not as accurate as Simple Random Sampleif the sample is the same size. 5- Cluster sample When all population in any stage of multistage random sample were chosen en toto (including all ages ، sexes, socioeconomic classes) the sample then is called cluster sample. Cluster sampling is an example of 'two-stage sampling'. First stage a sample of areas is chosen; Second stage a sample of respondents within those areas is selected. Population divided into clusters of homogeneous units, usually based on geographical contiguity.Sampling units are groups rather than individuals.A sample of such clusters is thenselected.All units from the selected clusters are studied. Advantages: 1. Cuts down on the cost of preparing a sampling frame. 2. Can reduce travel and other administrative costs. Disadvantages: 1. Sampling error is higher for a simple random sample of same size. — Often used to evaluate vaccination coverage in EPI  Exercise Define Sample: ……………………………………………………………………………… ……………………………………………………………………………… Types of sample: ……………………………………….. ……………………………………….. Types of Non-probability or Non-random sample: ………………………………………………………………………………… ………………………………………………………………………………… ………………………………………………………… Types of probability or random sample: ………………………………………………………………………………… ………………………………………………………………………………… ………………………………………………………… ………………………………………………………………………………… …………………………………………………………………  Methods of presentation of data Intended Learned Outcomes (ILOs) I - Knowledge and understanding By the end of this course, students should be able to  Define different methods of data presentation; also describe different shapes of distribution of data II – Skills By the end of this course, students should be able to  Acquire the skills to present data in its different forms (tabular, graphical and mathematical) III – Attitude By the end of this course, students should be able to  Perceive the importance of data presentation in simplifying and interpretation of data.  Methods of presentation of data 1. Tabular presentation In which data are presented in the form of tables: 1- The table should be as simple as possible and should be self explanatory. 2- The table should include a space for certain notes. 3- The title of the table: a. Should be on the top. It should answer what, from where and how the data were taken? b. Should be clear and separated from the head of the table by lines or spaces. 4- If the largest number is not a round figure, e.g. 52, it should be considered to the nearest round figure (55). Types: 1- Simple frequency distribution table: Problem: 85, 85, 65, 65, 67, 50, 100, 90, 105, 80, 60, 82, 85. The above observations are the weights of students attending the teaching class in the 4th year in Menoufiya Faculty of medicine 2009. Represent these data in a suitable table. The most suitable table is Table (1):The simple frequency distribution table. Weight in Kg Frequency 50 – 60 (kg) 60 – 70 (kg) 70 – 80 (kg) 80 – 90 (kg) Total 2- Percent or relative frequency distribution table: Table (2): Number and percent frequency distribution of blood haemoglobin in grams for 15 patients Weight in Kg Frequency Percent (relative frequency) 50 – 60 (kg) 60 – 70 (kg) 70 – 80 (kg) 80 – 90 (kg) Total 3 - Cumulative relative frequency distribution table:- - Table (3) Weight in Percent (relative Cum. Relative Frequency Kg frequency) frequency 50 – 60 (kg) 60 – 70 (kg) 70 – 80 (kg) 80 – 90 (kg) Total  4 - Complex tables: - Table(4) Male Female Total Weight in Kg Frequency Percent Frequency Percent Frequency Percent 50 – 60 (kg) 60 – 70 (kg) 70 – 80 (kg) 80 – 90 (kg) Total 5 - (r)(c) complex table: - Table(5) Weight Male Female Total in Kg Married Unmarried Married Unmarried Married Unmarried 50 – 60 (kg) 60 – 70 (kg) 70 – 80 (kg) 80 – 90 (kg) Total  6 – [2X2] contingency table: - Table (6) Smoking status Lung cancer Total Positive Negative Smokers 8 6 14 Non smokers 2 4 6 Total 10 10 20 2- Graphical presentation Graphical presentation: represents techniques for illustrating, interpreting, and analyzing numerical facts by means of points, lines, areas, and other geometric forms and symbols. Benefits 1. Graphic techniques are valuable in presenting quantitative data in a simple, clear, and effective manner. 2. Facilitate comparisons of values, trends, and relationships. 3. The comprehensive pictures they provide can bring out hidden facts and relationships and contribute to a more balanced understanding of a problem. Types of graphes  Bar chart: it includes (simple, complex and component bar)  Histogram  Pie chart  Line graph Bar graph: A bar graph is a way of illustrating a set of categorical data. It displays the data using a number of rectangles, of the same width, each of which represents a particular category. Bar graphs can be displayed horizontally or vertically and they are usually drawn with a gap between the bars (rectangles). 1) Simple Bar Chart 1. Gender: nominal qualitative variable. 2. The best graphical representation? (Simple bar chart). 2) Complex Bar Chart:  Complex frequency distribution table  Rat strain and sex qualitative nominal variables.  The best graphical presentation of this table? Complex bar chart:- 60 50 40 30 male female 20 10 0 A B C 3) Component Bar Chart: - Component bar chart is the best chart used to represent the percent frequency of qualitative nominal variables, especially in comparison  betweencountries. Leading cause of death among under 5 children infections Cancer Accidents Others 120 100 5 20 80 50 Percent 60 30 40 20 20 45 25 0 5 Developing country Developed country Histogram:A histogram is a way of illustrating data that are measured on an interval scale (either discrete or continuous). It is the best type of graphical presentation for continuous quantitative variables e.g. weight, height, blood pressure, blood sugar.  Pie chart:A pie chart is used to display a set of categorical data. It is a circle, which is divided into segments. Each segment represents a particular category. The area of each segment is proportional to the number of cases in that category. Line graph:A line graph is particularly useful when we want to show the trend of a variable over time. Time is displayed on the horizontal axis (x-axis) and the variable is displayed on the vertical axis (y- axis). 3. Mathematical presentation of data It is the presentation of data in mathematical form Types of mathematical calculation of data A. Measures of central tendencies, location or average:- [One figure to represent a group of figures] 1. Mean (X) 2. Median 3. Mode (Mo) 4. Mid-range B. Measures of dispersion, scatter or deviation: - 1. Range (R) 2. Standard deviation (SD) A) Measures of central tendencies, location or average I. Mean: a. Arithmetic mean: X: It is considered as the balance point of a distribution. Calculation of the mean Example: Compute the mean from the following observations: 1, 2, 3, 4, 5 and 6 The mean = (∑ Xi)/n = summation of observations/ number of observations Where ∑ = sum of: - Xi = individual observations n = number of observation  II. Median: It is the middle observation after ranking the observations in an ascending or a descending manner. - It is a measure of position and is that point above and below which one half of the scores fall. In other words, the middle most position. Calculation of median Example: The weight in kg of 7 individuals was 21, 22, 45, 30, 25, 21 and 32. Compute the median. The answer:- Firstly, we should rank these observations in an ascending or a descending manner: 21, 21, 22, 25, 30, 32 and 45. n+1 8 - The location is determined as follows: —— = =4 2 2 In this example, the median will be at 4th observation =25 N.B In even observations, the median is equal to the average of the middle 2 observations. (Examples in practical book) III. The mode: The most frequent observation - Compute the mode from the following observations: 2, 3, 4, 4, and 6. - The mode is the most frequent observation = 4 - Sometimes, no mode is present; two modes may be present (bimodal), or three modes (tri-modal). IV. The mid-range: The smallest observation + the largest observation The mid-range = 2 Calculation of the mid-range: - The following are heights in cm: 180, 170,160, 150, and 180. Compute the mid- range. Answer:  180 + 150 - The mid-range = ————— = 165 mg 2 B. Measures of dispersion, scatter or deviation It gives an idea about the variability and deviation of observations around the mean. I. Range: The range = the difference between the highest and lowest scores 1. The variance and standard deviation: The variance:The average of the squared differences from the Mean..Advantages: 1. It uses every observation. 2. It is mathematically manageable. Disadvantages: Its dimensionality is that of the square of the original observations. The standard deviation: (SD) It is a measure which describes how much individual measurements differ, on the average, from the mean. The variance and standard deviation measure variation within a set of data. The larger they are, the greater the variation or heterogeneity. They have similar computation. Standard deviation (SD) = the root square of the variance = ±√ Variance  Exercise Types of presentation of data: …………………………………………………………………………………… ……………………………………………………………… ………………………………………………………………………… Types of graphs: …………………………………………………………………………………… ……………………………………………………………… …………………………………………………………………………………… ……………………………………………………………… Types of tables: …………………………………………………………………………………… ……………………………………………………………… …………………………………………………………………………………… ……………………………………………………………… …………………………………………………………………………………… ……………………………………………………………… ……………………………………………………………………….. Criteria of best graph: …………………………………………………………………………………… ……………………………………………………………… …………………………………………………………………………………… ……………………………………………………………… Criteria of best table: …………………………………………………………………………………… ……………………………………………………………… What is the kind of this graph? 60 …………………………………… male female 50 …………………………………… 40 30 20 10 0 A B C What is the type of the table? …………………………………………………………………………………………… …………………………………………………………………………… Rat strain Males Females Total (n=100) (n=100) (n=200) No % No % no % A 20 20.0 15 15.0 35 17.5 B 30 30.0 10 10.0 40 20.0 C 50 50.0 75 75.0 125 62.5 The best graphical presentation of this table is ……………………………………………………………………………………… ……………………………………………………………………… Draw the best chart:- Demonstrate types of these graphs and their uses: ……………………………………………………………………… …………………………………………………………… ……………………………………………………………………… …………………………………………………………… ……………………………………………………………………… …………………………………………………………… ……………………………………………………………………… …………………………………………………………… From the following data:-[5 –2 - 7-8 –5 –4 -4-3] Compute: Arithmetic mean =…………………………………………………….. ………………………………………………………………………… Mode =………………………………………………………………… ………………………………………………………………………… Median =……………………………………………………………… ………………………………………………………………………… Mid-range =…………………………………………………………… ………………………………………………………………………… Range =……………………………………………………………….. ………………………………………………………………………… SD =…………………………………………………………………… ……………………………………………………………………….. Compute: [21 – 24 – 42 – 33 – 22 – 24 – 42] Arithmetic mean =…………………………………………………….. ………………………………………………………………………… Mode =………………………………………………………………… ………………………………………………………………………… Median =……………………………………………………………… ………………………………………………………………………… Mid-range =…………………………………………………………… ………………………………………………………………………… Range =……………………………………………………………….. SD =…………………………………………………………………… ……………………………………………………………………  References  Balcázar J, Dai Y, Watanabe O. A random sampling technique for training support vector machines. InInternational Conference on Algorithmic Learning Theory 2001 Nov 25 (pp. 119-134). Springer, Berlin, Heidelberg.  Goddard W, Melville S. Research methodology: An introduction. Juta and Company Ltd; 2004.  Newman I, Covrig DM. Building consistency between title, problem statement, purpose, & research questions to improve the quality of research plans and reports. New Horizons in Adult Education and Human Resource Development. 2013 Dec;25(1):70-9.  Rudzki PJ, Biecek P, Kaza M. Comprehensive graphical presentation of data from incurred sample reanalysis. Bioanalysis. 2017 Jun;9(12):947-56.  Spokoiny V, Dickhaus T. Basics of modern mathematical statistics. Heidelberg: Springer; 2015.  Taherdoost H. Sampling methods in research methodology; how to choose a sampling technique for research. How to Choose a Sampling Technique for Research (April 10, 2016). 2016 Apr 10.  Thiese MS. Observational and interventional study design types; an overview. Biochemia medica. 2014 Jun 15;24(2):199-21 