Summarize for Principles of Statistics (ٍStat 500) and it's Lectures for students of Computer Science in Institute of Statistical Studies and Research - Cairo University
Summarize for Principles of Statistics (ٍStat 500) . it's Lectures for students of Computer Science and especially students of graduate studies of the Institute of Statistical Studies and Research - Cairo University
This document discusses statistical hypothesis testing and statistical inferences. It notes that statistical hypothesis testing is one of the most important applications of probability theory in statistics. This allows researchers to make decisions about accepting or rejecting hypotheses based on sample data. The process of decision making through hypothesis testing involves multiple steps, including drawing a representative sample, collecting relevant data, applying statistical rules to test hypotheses, and making a decision based on results. Statistical inferences aim to estimate unknown population parameters through sampling and probability theory plays a key role in this process and in decision making more broadly.
This document discusses blinding techniques in clinical trials. It defines blinding as keeping trial participants, investigators, or assessors unaware of treatment assignments to prevent bias. Single blinding means one group is unaware, while double blinding means participants, investigators, and assessors are all unaware of assignments. Placebos can be used to maintain blinding for subjective outcomes. Descriptions of blinding should state who was blinded and how similarity between treatments was maintained. Assessing success of blinding can involve directly asking groups to guess assignments or looking for disproportionate side effects between groups. Some surgical trials cannot be blinded.
This document discusses statistical hypothesis testing and statistical inferences. It notes that statistical hypothesis testing is one of the most important applications of probability theory in statistics. This allows researchers to make decisions about accepting or rejecting hypotheses based on sample data. The process of decision making through hypothesis testing involves multiple steps, including drawing a representative sample, collecting relevant data, applying statistical rules to test hypotheses, and making a decision based on results. Statistical inferences aim to estimate unknown population parameters through sampling and probability theory plays a key role in this process and in decision making more broadly.
This document discusses blinding techniques in clinical trials. It defines blinding as keeping trial participants, investigators, or assessors unaware of treatment assignments to prevent bias. Single blinding means one group is unaware, while double blinding means participants, investigators, and assessors are all unaware of assignments. Placebos can be used to maintain blinding for subjective outcomes. Descriptions of blinding should state who was blinded and how similarity between treatments was maintained. Assessing success of blinding can involve directly asking groups to guess assignments or looking for disproportionate side effects between groups. Some surgical trials cannot be blinded.
1. Ethical dilemmas in research occur when participants' rights and study demands conflict, requiring codes of ethics to guide researchers.
2. Major codes discussed include the Nuremberg Code, Declaration of Helsinki, and guidelines for nursing and psychology research.
3. Key ethical principles for protecting participants include beneficence, respecting human dignity, justice, and informed consent. Researchers must consider risks of harm, confidentiality, and deception in their studies.
The Declaration of Helsinki is a set of ethical principles regarding human experimentation set forth by the World Medical Association. It was originally adopted in 1964 and aims to provide guidance to physicians and researchers. The Declaration establishes standards to ensure medical research involving human subjects respects their life, health, dignity, integrity, and rights. It requires voluntary informed consent and oversight by research ethics committees. The Declaration has undergone several revisions to update and clarify its guidelines as medical research has advanced. It continues to be recognized as a fundamental document for ethics in human subject research.
Parametric Survival Analysis in Health Economics HTAi Bilbao 2012
This document presents an overview of parametric survival analysis and how it can be used to extrapolate survival data from clinical trials for economic evaluations. It discusses several parametric models including exponential, Weibull, log-normal and Gompertz. It outlines a systematic approach to choosing the best fitting parametric model, including using graphical methods, formal statistical tests of nested models, and information criteria to compare non-nested models. The document applies this process to cardiac patient survival data as a case study and discusses challenges in extrapolating survival curves beyond the observed data.
This document discusses research design. It begins by defining research design as the arrangement of conditions for collecting and analyzing data to combine relevance to the research purpose with economical procedures. The document then outlines the key parts of research design including sampling, observational, statistical, and operational design. It also discusses important concepts such as independent and dependent variables, extraneous variables, hypotheses, experimental and control groups, and treatments. The document concludes by describing three main types of research design: exploratory, descriptive/diagnostic, and hypothesis-testing designs. It provides examples of methods used for each type of design.
مناهج البحث العلمي - اللقاء الافتراضي الاول
مراجعة الوحدات الأربعة الأولى
ومناقشة عينة من أسئلة السنوات السابقة لمادة النصفي
اعداد: د.حسني عوض
كلية التربية
جامعة القدس المفتوحة
In Hypothesis testing parametric test is very important. in this ppt you can understand all types of parametric test with assumptions which covers Types of parametric, Z-test, T-test, ANOVA, F-test, Chi-Square test, Meaning of parametric, Fisher, one-sample z-test, Two-sample z-test, Analysis of Variance, two-way ANOVA.
Subscribe to Vision Academy for Video assistance
https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw
Bias in research can occur at any stage from study design to publication. There are several types of bias including selection bias, information bias, and confounding bias. Selection bias occurs when the study sample is not representative of the target population. Information bias results from errors in measuring or classifying exposure and outcome variables. Confounding bias is introduced when a third variable is associated with both the exposure and outcome. Researchers should employ techniques like randomization, matching, and restriction to minimize bias.
Research Methodology (M. Pharm, IIIrd Sem.)_UNIT_IV_CPCSEA Guidelines for Lab...RAHUL PAL
CPCSEA guidelines for laboratory animal facility: Goals, veterinary care, quarantine,
surveillance, diagnosis, treatment and control of disease, personal
hygiene, location of animal facilities to laboratories, anesthesia, euthanasia, physical facilities, environment, animal husbandry, record keeping, SOPs, personnel and
training, transport of lab animals.
This document outlines the historical method of research which involves collecting and analyzing primary and secondary sources to study past events and understand how they influence the present. The method has 7 stages: identifying a problem, formulating a hypothesis, collecting data, evaluating data, interpreting findings, reaching a conclusion, and decision making. It discusses tips for effective data collection, source criticism to validate sources, and limitations such as availability of information and potential for bias.
This document provides an overview of qualitative research methods. It discusses that qualitative research aims to understand experiences from the perspective of individuals, using words rather than numbers. Qualitative methods are used to answer questions about processes or experiences. Topics that can be addressed include people's health experiences, attitudes, and how life circumstances affect health. The document reviews sampling techniques in qualitative research, as well as methods for generating data, including individual interviews, group interviews, and collecting contextual information. Interviewing skills like establishing rapport and addressing potential biases are also covered.
This document discusses various types of errors and biases that can occur in epidemiological studies. It defines error as a phenomenon where a study's results do not reflect the true facts. There are two basic types of error: random error, which occurs by chance and makes observed values differ from true values; and systematic error or bias, which is due to factors in the study design that cause results to depart from the truth. Types of bias discussed include selection bias, information bias, and confounding. Strategies for controlling biases such as randomization, restriction, matching, and statistical modeling are also outlined.
This document provides an overview of a research methodology course taught by Farha Hassan at PIMSR. The course covers key topics in research methods including defining a research problem, research design, data collection methods, data analysis techniques, and writing a research report. Reference texts for the course are also listed. The course aims to teach students the relevant concepts and steps involved in conducting research in management.
1. Ethical dilemmas in research occur when participants' rights and study demands conflict, requiring codes of ethics to guide researchers.
2. Major codes discussed include the Nuremberg Code, Declaration of Helsinki, and guidelines for nursing and psychology research.
3. Key ethical principles for protecting participants include beneficence, respecting human dignity, justice, and informed consent. Researchers must consider risks of harm, confidentiality, and deception in their studies.
The Declaration of Helsinki is a set of ethical principles regarding human experimentation set forth by the World Medical Association. It was originally adopted in 1964 and aims to provide guidance to physicians and researchers. The Declaration establishes standards to ensure medical research involving human subjects respects their life, health, dignity, integrity, and rights. It requires voluntary informed consent and oversight by research ethics committees. The Declaration has undergone several revisions to update and clarify its guidelines as medical research has advanced. It continues to be recognized as a fundamental document for ethics in human subject research.
Parametric Survival Analysis in Health Economics HTAi Bilbao 2012
This document presents an overview of parametric survival analysis and how it can be used to extrapolate survival data from clinical trials for economic evaluations. It discusses several parametric models including exponential, Weibull, log-normal and Gompertz. It outlines a systematic approach to choosing the best fitting parametric model, including using graphical methods, formal statistical tests of nested models, and information criteria to compare non-nested models. The document applies this process to cardiac patient survival data as a case study and discusses challenges in extrapolating survival curves beyond the observed data.
This document discusses research design. It begins by defining research design as the arrangement of conditions for collecting and analyzing data to combine relevance to the research purpose with economical procedures. The document then outlines the key parts of research design including sampling, observational, statistical, and operational design. It also discusses important concepts such as independent and dependent variables, extraneous variables, hypotheses, experimental and control groups, and treatments. The document concludes by describing three main types of research design: exploratory, descriptive/diagnostic, and hypothesis-testing designs. It provides examples of methods used for each type of design.
مناهج البحث العلمي - اللقاء الافتراضي الاول
مراجعة الوحدات الأربعة الأولى
ومناقشة عينة من أسئلة السنوات السابقة لمادة النصفي
اعداد: د.حسني عوض
كلية التربية
جامعة القدس المفتوحة
In Hypothesis testing parametric test is very important. in this ppt you can understand all types of parametric test with assumptions which covers Types of parametric, Z-test, T-test, ANOVA, F-test, Chi-Square test, Meaning of parametric, Fisher, one-sample z-test, Two-sample z-test, Analysis of Variance, two-way ANOVA.
Subscribe to Vision Academy for Video assistance
https://www.youtube.com/channel/UCjzpit_cXjdnzER_165mIiw
Bias in research can occur at any stage from study design to publication. There are several types of bias including selection bias, information bias, and confounding bias. Selection bias occurs when the study sample is not representative of the target population. Information bias results from errors in measuring or classifying exposure and outcome variables. Confounding bias is introduced when a third variable is associated with both the exposure and outcome. Researchers should employ techniques like randomization, matching, and restriction to minimize bias.
Research Methodology (M. Pharm, IIIrd Sem.)_UNIT_IV_CPCSEA Guidelines for Lab...RAHUL PAL
CPCSEA guidelines for laboratory animal facility: Goals, veterinary care, quarantine,
surveillance, diagnosis, treatment and control of disease, personal
hygiene, location of animal facilities to laboratories, anesthesia, euthanasia, physical facilities, environment, animal husbandry, record keeping, SOPs, personnel and
training, transport of lab animals.
This document outlines the historical method of research which involves collecting and analyzing primary and secondary sources to study past events and understand how they influence the present. The method has 7 stages: identifying a problem, formulating a hypothesis, collecting data, evaluating data, interpreting findings, reaching a conclusion, and decision making. It discusses tips for effective data collection, source criticism to validate sources, and limitations such as availability of information and potential for bias.
This document provides an overview of qualitative research methods. It discusses that qualitative research aims to understand experiences from the perspective of individuals, using words rather than numbers. Qualitative methods are used to answer questions about processes or experiences. Topics that can be addressed include people's health experiences, attitudes, and how life circumstances affect health. The document reviews sampling techniques in qualitative research, as well as methods for generating data, including individual interviews, group interviews, and collecting contextual information. Interviewing skills like establishing rapport and addressing potential biases are also covered.
This document discusses various types of errors and biases that can occur in epidemiological studies. It defines error as a phenomenon where a study's results do not reflect the true facts. There are two basic types of error: random error, which occurs by chance and makes observed values differ from true values; and systematic error or bias, which is due to factors in the study design that cause results to depart from the truth. Types of bias discussed include selection bias, information bias, and confounding. Strategies for controlling biases such as randomization, restriction, matching, and statistical modeling are also outlined.
This document provides an overview of a research methodology course taught by Farha Hassan at PIMSR. The course covers key topics in research methods including defining a research problem, research design, data collection methods, data analysis techniques, and writing a research report. Reference texts for the course are also listed. The course aims to teach students the relevant concepts and steps involved in conducting research in management.
Statistics involves collecting, organizing, analyzing, and interpreting data. Descriptive statistics describe characteristics of a data set through measures like central tendency and variability. Inferential statistics draw conclusions about a population based on a sample. Key terms include population, sample, parameter, statistic, data types, levels of measurement, and sampling techniques like simple random sampling. Common data gathering methods are interviews, questionnaires, and registration records. Data can be presented textually, in tables, or graphically through charts, graphs, and maps.
This document discusses several definitions of economics provided by prominent economists over time. It begins by summarizing Adam Smith's definition from 1776 that viewed economics as the science of wealth. It then discusses Alfred Marshall's 1890 definition that considered economics the study of mankind in business. Next, it outlines Lionel Robbins' 1932 definition that defined economics as studying human behavior related to scarce means and alternative uses. Finally, it provides Paul Samuelson's modern definition from 1948 that viewed economics as concerning how society employs its resources. The document then briefly discusses the main divisions of economics as consumption, production, exchange, distribution, and public finance.
This document provides a teaching guide for a Statistics and Probability course for senior high school students. It begins with an introduction that discusses the importance of statistics and data analysis. It then outlines the structure and goals of the teaching guide, which includes sections on introduction, instruction, practice, enrichment, and evaluation. The guide is meant to help teachers facilitate student understanding, mastery of concepts, and a sense of ownership over their learning. It also discusses aligning the guide with DepEd and CHED standards to prepare students for college. The preface provides additional context on statistics as a discipline and its growing importance.
Statistics can be defined in both a singular and plural sense. In the singular sense, it refers to statistical methods for collecting, analyzing, and interpreting numerical data. In the plural sense, it refers to the actual numerical facts or data collected. Statistics involves systematically collecting, organizing, presenting, analyzing, and interpreting numerical data to describe features and characteristics. It allows for comparing facts, establishing relationships, and facilitating policymaking and decision making. However, statistics only studies aggregates and averages, not individual cases, and results are true only on average. It also requires properly contextualizing and referencing results.
Statistics is the science of dealing with numbers.
It is used for collection, summarization, presentation and analysis of data.
Statistics provides a way of organizing data to get information on a wider and more formal (objective) basis than relying on personal experience (subjective).
Introduction to statistics...ppt rahulRahul Dhaker
This document provides an introduction to statistics and biostatistics. It discusses key concepts including:
- The definitions and origins of statistics and biostatistics. Biostatistics applies statistical methods to biological and medical data.
- The four main scales of measurement: nominal, ordinal, interval, and ratio scales. Nominal scales classify data into categories while ratio scales allow for comparisons of magnitudes and ratios.
- Descriptive statistics which organize and summarize data through methods like frequency distributions, measures of central tendency, and graphs. Frequency distributions condense data into tables and charts. Measures of central tendency include the mean, median, and mode.
Part 1 spss dr.hany atef احصاء سياحي وفندقي Hany Atef
يبحث علم الإحصاء في طرائق جمع البيانات وتحليلها وتفسيرها من خلال مجموعة من الطرائق الرياضية أو البيانية. وتهدف هذه العملية إلى وصف متغير أو مجموعة من المتغيرات من خلال مجموعة من البيانات (العينة) والتوصل بالتالي إلى قرارات مناسبة تعمم على المجتمع الذي أخذت منه هذه العينة. ومن المعروف أن جمع المعلومات من جميع أفراد المجتمع أمر شاق يصعب تحقيقه في كثير من الأحيان، فذلك يحتاج إلى وقت وجهد ومال كثير، أما أخذ عينة عشوائية وممثلة من هذا المجتمع فعملية اسهل وتحتاج إلى جهد ووقت ومال اقل.
لذا نستعرض
الاحصاء والبيانات و طرق اختيار العينة ومقدمة في النظام الإحصائي SPSS و عملية إدخال البيانات في SPSS . كما نستعرض العمليات الحسابية واختيار الحالات
أهمية تعليم البرمجة للأطفال في العصر الرقمي.pdfelmadrasah8
في العصر الرقمي الحالي، أصبحت البرمجة مهارة أساسية تتجاوز كونها مجرد أداة تقنية، بل تعد مفتاحًا لفهم العالم المتصل بالإنترنت والتفاعل معه. تعليم البرمجة للأطفال ليس مجرد تعلم لغة البرمجة، بل هو تطوير لمجموعة واسعة من المهارات الأساسية التي يمكن أن تساعدهم في المستقبل.
تعزيز التفكير المنطقي وحل المشكلات
البرمجة تتطلب التفكير المنطقي وحل المشكلات بطرق منهجية. عند تعلم البرمجة، يتعلم الأطفال كيفية تحليل المشكلات وتقسيمها إلى أجزاء أصغر يمكن إدارتها. هذه المهارات ليست مفيدة فقط في مجال التكنولوجيا، بل تمتد إلى مختلف جوانب الحياة الأكاديمية والمهنية.
تحفيز الإبداع والابتكار
من خلال البرمجة، يمكن للأطفال تحويل أفكارهم إلى واقع ملموس. سواء كان ذلك بإنشاء لعبة، أو تطوير تطبيق، أو تصميم موقع ويب، يتيح لهم البرمجة التعبير عن إبداعهم بشكل فريد. هذا يحفز الأطفال على التفكير خارج الصندوق وتطوير حلول مبتكرة للتحديات التي يواجهونها.
توفير فرص مستقبلية
مع تزايد الاعتماد على التكنولوجيا في جميع القطاعات، ستكون مهارات البرمجة من بين الأكثر طلبًا في سوق العمل المستقبلي. تعلم البرمجة من سن مبكرة يمنح الأطفال ميزة تنافسية كبيرة في سوق العمل ويزيد من فرصهم في الحصول على وظائف متميزة في المستقبل.
تنمية مهارات العمل الجماعي والتواصل
تعلم البرمجة غالبًا ما يتضمن العمل في فرق ومشاركة الأفكار والمشاريع مع الآخرين. هذا يساهم في تنمية مهارات العمل الجماعي والتواصل الفعّال لدى الأطفال. كما يساعدهم على تعلم كيفية التعاون والتفاعل مع الآخرين لتحقيق أهداف مشتركة.
فهم أفضل للتكنولوجيا
تعلم البرمجة يساعد الأطفال على فهم كيفية عمل التكنولوجيا من حولهم. بدلاً من أن يكونوا مجرد مستخدمين للتكنولوجيا، يصبحون قادرين على تحليلها وفهم الأساسيات التي تقوم عليها. هذا الفهم العميق يمنحهم القدرة على التفاعل مع التكنولوجيا بطرق أكثر فعالية وكفاءة.
تعليم البرمجة للأطفال في العصر الرقمي ليس رفاهية، بل ضرورة لتأهيلهم لمستقبل مشرق. من خلال تطوير مهارات التفكير المنطقي، الإبداع، والتواصل، يتم إعداد الأطفال ليكونوا مبتكرين وقادة في العالم الرقمي المتطور. البرمجة تفتح لهم أبوابًا واسعة من الفرص والتحديات التي يمكنهم تجاوزها بمهاراتهم ومعرفتهم المتقدمة.