This document discusses sports medicine, including the concept, aims, scope, common injuries, and injury management. It defines sports medicine as dealing with prevention, diagnosis, and treatment of sports injuries. The document outlines the various types of sports surfaces and environments and their impact on athletes. It also classifies and describes common soft tissue, bone, and joint injuries in sports. Finally, it provides guidance on injury prevention strategies and first aid treatments for different types of common sports injuries.
The document discusses Enterprise Resource Planning (ERP) systems. ERP systems integrate various business functions like manufacturing, sales, inventory, accounting etc into a single system. The document outlines the evolution of ERP from earlier software packages, describes the components and benefits of ERP systems like improved efficiency and information integration. It also discusses challenges in ERP implementation like costs, timelines and resistance to change.
The document discusses different scales of measurement proposed by Stanley Smith Stevens, including nominal, ordinal, interval, and ratio scales. It then examines attitude measurement and different response types for measuring attitudes such as rating scales, ranking scales, categorization, and sorting. Key factors that influence selecting an appropriate measurement scale for attitudes include the research objectives, response types, number of dimensions, and whether responses involve forced or unforced choices.
Growth charts are used to monitor children's physical growth and development over time. They plot weight, height/length, and other anthropometric measurements against age and allow comparisons to reference standards. Monitoring growth helps determine if a child's development is normal or if problems exist that need addressing. Various indicators and classification systems exist to define and assess malnutrition based on anthropometric measurements, including weight-for-age, height-for-age, and weight-for-height. Growth charts first designed by David Morley have been modified over time by organizations like WHO and are an important tool to track children's nutrition and health.
The document discusses the 17 Sustainable Development Goals (SDGs) adopted by the UN in 2015 to be achieved by 2030. The SDGs include goals to end poverty and hunger, ensure health and well-being, provide quality education, achieve gender equality, and promote sustainable industry and infrastructure. Progress will be assessed in 2020, 2025, and 2030. The SDGs replace the Millennium Development Goals and apply universally to all countries.
Correlation and regression analysis are statistical tools used to analyze relationships between variables. Correlation measures the strength and direction of association between two variables on a scale from -1 to 1. Regression analysis uses one variable to predict the value of another variable and draws a best-fit line to represent their relationship. There are always two lines of regression - one showing the regression of x on y and the other showing the regression of y on x. Regression coefficients from these lines indicate the slope and intercept of the lines and can help estimate unknown variable values based on known values.
This document discusses the scope and uses of statistics across various fields such as planning, economics, business, industry, mathematics, science, psychology, education, war, banking, government, sociology, and more. It outlines functions of statistics like presenting facts, testing hypotheses, forecasting, policymaking, enlarging knowledge, measuring uncertainty, simplifying data, deriving valid inferences, and drawing rational conclusions. It also covers characteristics, advantages, and limitations of statistics.
This document discusses the different meanings and definitions of statistics. It explains that statistics has three different meanings: (1) plural sense referring to numerical facts and figures collected systematically, (2) singular sense referring to the science of collecting, analyzing, and presenting numerical data, and (3) plural of the word "statistic" referring to numerical quantities calculated from samples. The document also provides several definitions of statistics from different authors, describing it as the science of collecting, organizing, and interpreting quantitative data.
Descriptive statistics are used to describe and summarize the basic features of data through measures of central tendency like the mean, median, and mode, and measures of variability like range, variance and standard deviation. The mean is the average value and is best for continuous, non-skewed data. The median is less affected by outliers and is best for skewed or ordinal data. The mode is the most frequent value and is used for categorical data. Measures of variability describe how spread out the data is, with higher values indicating more dispersion.
This document discusses statistics and their uses in various fields such as business, health, learning, research, social sciences, and natural resources. It provides examples of how statistics are used in starting businesses, manufacturing, marketing, and engineering. Statistics help decision-makers reduce ambiguity and assess risks. They are used to interpret data and make informed decisions. However, statistics also have limitations as they only show averages and may not apply to individuals.
This document defines correlation and discusses different types of correlation. It states that correlation refers to the relationship between two variables, where their values change together. There can be positive correlation, where variables change in the same direction, or negative correlation, where they change in opposite directions. Correlation can also be linear, nonlinear, simple, multiple, or partial. The degree of correlation is measured by the coefficient of correlation, which ranges from -1 to 1. Graphic and algebraic methods like scatter diagrams and calculating the coefficient can be used to study correlation.
Nature, Scope, Functions and Limitations of StatisticsAsha Dhilip
This document defines statistics and discusses its uses and limitations. Statistics is defined as the collection, organization, analysis, and interpretation of numerical data in a systematic and accurate manner to draw valid inferences. It is used in business and management for marketing, production, finance, banking, investment, purchasing, accounting, and control. While statistics is useful for simplifying complex data and facilitating comparison, it has limitations in that it only examines quantitative aspects on average, not individuals, and statistical results may not be exact.
This slideshow describes about type of data, its tabular and graphical representation by various ways. It is slideshow is useful for bio statisticians and students.
This document discusses population and sampling concepts for research. It defines a population as the complete set of people or objects with a common characteristic of interest. The target population is the entire group the researcher wishes to generalize to, while the accessible population includes cases that meet criteria and are available. A sample is a representative subset of the target population selected using sampling principles like random selection and large sample sizes to make inferences about the population. The key difference between a population and sample is that a population includes all elements while a sample is a subset used to study characteristics of the larger population.
What is Universe or Population
the term ‘Universe’ refers to the total of the items or units in any field of inquiry.
whereas the term ‘Population’ refers to the total of items about which information is desired.
Example:
Universe : All the Teachers
Population : All primary teachers, all college teachers, all university students etc.
Population Size: The total number of units present in the population
Measures of dispersion
Absolute measure, relative measures
Range of Coe. of Range
Mean deviation and coe. of mean deviation
Quartile deviation IQR, coefficient of QD
Standard deviation and coefficient of variation
The document discusses various measures of central tendency used in statistics. The three most common measures are the mean, median, and mode. The mean is the sum of all values divided by the number of values and is affected by outliers. The median is the middle value when data is arranged from lowest to highest. The mode is the most frequently occurring value in a data set. Each measure has advantages and disadvantages depending on the type of data distribution. The mean is the most reliable while the mode can be undefined. In symmetrical distributions, the mean, median and mode are equal, but the mean is higher than the median for positively skewed data and lower for negatively skewed data.
This presentation covers statistics, its importance, its applications, branches of statistics, basic concepts used in statistics, data sampling, types of sampling,types of data and collection of data.
Introductory Statistics discusses the definition and history of statistics. Statistics deals with quantitative or numerical data and is the scientific method of collecting, organizing, analyzing, and making decisions with quantitative data. Historically, Indian texts from the Mauryan period and Mughal period contained early forms of statistical analysis of topics like agriculture. The typical process of a statistical study involves defining objectives, identifying the population and characteristics, planning data collection, collecting and organizing data, performing statistical analysis, and drawing conclusions. Statistics is useful for simplifying complex data, quantifying uncertainty, discovering patterns to enable forecasting, and testing assumptions. Statistical techniques have various applications in fields like marketing, economics, finance, operations, human resources, information technology,
The document discusses correlation analysis and different types of correlation. It defines correlation as the linear association between two random variables. There are three main types of correlation:
1) Positive vs negative vs no correlation based on the relationship between two variables as one increases or decreases.
2) Linear vs non-linear correlation based on the shape of the relationship when plotted on a graph.
3) Simple vs multiple vs partial correlation based on the number of variables.
The document also discusses methods for studying correlation including scatter plots, Karl Pearson's coefficient of correlation r, and Spearman's rank correlation coefficient. It provides interpretations of the correlation coefficient r and coefficient of determination r2.
This document discusses correlation analysis and its various types. Correlation is the degree of relationship between two or more variables. There are three stages to solve correlation problems: determining the relationship, measuring significance, and establishing causation. Correlation can be positive, negative, simple, partial, or multiple depending on the direction and number of variables. It is used to understand relationships, reduce uncertainty in predictions, and present average relationships. Conditions like probable error and coefficient of determination help interpret correlation values.
The document discusses various sampling techniques used in research including probability and non-probability sampling. It explains key concepts like population, sample, sampling frame, sampling error, systematic error. It describes different probability sampling designs such as simple random sampling, stratified sampling, cluster sampling and multistage sampling. It also discusses non-probability sampling techniques like convenience sampling and quota sampling. The document provides advantages and limitations of different sampling methods and guidelines for selecting an appropriate sampling design.
diagrammatic and graphical representation of dataVarun Prem Varu
This document discusses various types of diagrams and graphs that can be used to summarize statistical data. It describes one-dimensional, two-dimensional, and three-dimensional diagrams, as well as pictograms, cartograms, histograms, frequency polygons, frequency curves, ogives, and Lorenz curves. The key points are that diagrams and graphs make data simple and allow for easy comparison, while saving time over presenting raw numbers or text. Different types of diagrams and graphs are suited for different types of data and purposes. Guidelines are provided for properly constructing different diagrams.
Statistics play an essential role in scientific research by aiding in tasks like determining sample sizes, testing hypotheses, and interpreting large amounts of data. Various statistical analysis methods are used, including descriptive analysis to summarize data, inferential analysis to generalize from samples to populations, and predictive analysis to forecast future events. Common biological tools for statistics include SPSS, R, MATLAB, SAS, and Excel. Statistics help researchers effectively analyze large datasets and draw meaningful conclusions from their experimental findings.
01 parametric and non parametric statisticsVasant Kothari
Definition of Parametric and Non-parametric Statistics
Assumptions of Parametric and Non-parametric Statistics
Assumptions of Parametric Statistics
Assumptions of Non-parametric Statistics
Advantages of Non-parametric Statistics
Disadvantages of Non-parametric Statistical Tests
Parametric Statistical Tests for Different Samples
Parametric Statistical Measures for Calculating the Difference Between Means
Significance of Difference Between the Means of Two Independent Large and
Small Samples
Significance of the Difference Between the Means of Two Dependent Samples
Significance of the Difference Between the Means of Three or More Samples
Parametric Statistics Measures Related to Pearson’s ‘r’
Non-parametric Tests Used for Inference
This document discusses quantification and statistical techniques in social research. It begins by defining quantification as the act of counting and measuring human observations and experiences to map them to quantities. Quantitative methods emphasize objective measurements and statistical analysis of data from polls, questionnaires, and surveys. The document then discusses how quantification is used in economics and psychology through gathering empirical data and using statistical analysis techniques like regression analysis. It also outlines several statistical techniques used for data analysis, including descriptive, exploratory, inferential, predictive, and causal techniques. Specific statistical methods discussed include mean, standard deviation, regression, sample size determination, and hypothesis testing.
This document discusses the scope and uses of statistics across various fields such as planning, economics, business, industry, mathematics, science, psychology, education, war, banking, government, sociology, and more. It outlines functions of statistics like presenting facts, testing hypotheses, forecasting, policymaking, enlarging knowledge, measuring uncertainty, simplifying data, deriving valid inferences, and drawing rational conclusions. It also covers characteristics, advantages, and limitations of statistics.
This document discusses the different meanings and definitions of statistics. It explains that statistics has three different meanings: (1) plural sense referring to numerical facts and figures collected systematically, (2) singular sense referring to the science of collecting, analyzing, and presenting numerical data, and (3) plural of the word "statistic" referring to numerical quantities calculated from samples. The document also provides several definitions of statistics from different authors, describing it as the science of collecting, organizing, and interpreting quantitative data.
Descriptive statistics are used to describe and summarize the basic features of data through measures of central tendency like the mean, median, and mode, and measures of variability like range, variance and standard deviation. The mean is the average value and is best for continuous, non-skewed data. The median is less affected by outliers and is best for skewed or ordinal data. The mode is the most frequent value and is used for categorical data. Measures of variability describe how spread out the data is, with higher values indicating more dispersion.
This document discusses statistics and their uses in various fields such as business, health, learning, research, social sciences, and natural resources. It provides examples of how statistics are used in starting businesses, manufacturing, marketing, and engineering. Statistics help decision-makers reduce ambiguity and assess risks. They are used to interpret data and make informed decisions. However, statistics also have limitations as they only show averages and may not apply to individuals.
This document defines correlation and discusses different types of correlation. It states that correlation refers to the relationship between two variables, where their values change together. There can be positive correlation, where variables change in the same direction, or negative correlation, where they change in opposite directions. Correlation can also be linear, nonlinear, simple, multiple, or partial. The degree of correlation is measured by the coefficient of correlation, which ranges from -1 to 1. Graphic and algebraic methods like scatter diagrams and calculating the coefficient can be used to study correlation.
Nature, Scope, Functions and Limitations of StatisticsAsha Dhilip
This document defines statistics and discusses its uses and limitations. Statistics is defined as the collection, organization, analysis, and interpretation of numerical data in a systematic and accurate manner to draw valid inferences. It is used in business and management for marketing, production, finance, banking, investment, purchasing, accounting, and control. While statistics is useful for simplifying complex data and facilitating comparison, it has limitations in that it only examines quantitative aspects on average, not individuals, and statistical results may not be exact.
This slideshow describes about type of data, its tabular and graphical representation by various ways. It is slideshow is useful for bio statisticians and students.
This document discusses population and sampling concepts for research. It defines a population as the complete set of people or objects with a common characteristic of interest. The target population is the entire group the researcher wishes to generalize to, while the accessible population includes cases that meet criteria and are available. A sample is a representative subset of the target population selected using sampling principles like random selection and large sample sizes to make inferences about the population. The key difference between a population and sample is that a population includes all elements while a sample is a subset used to study characteristics of the larger population.
What is Universe or Population
the term ‘Universe’ refers to the total of the items or units in any field of inquiry.
whereas the term ‘Population’ refers to the total of items about which information is desired.
Example:
Universe : All the Teachers
Population : All primary teachers, all college teachers, all university students etc.
Population Size: The total number of units present in the population
Measures of dispersion
Absolute measure, relative measures
Range of Coe. of Range
Mean deviation and coe. of mean deviation
Quartile deviation IQR, coefficient of QD
Standard deviation and coefficient of variation
The document discusses various measures of central tendency used in statistics. The three most common measures are the mean, median, and mode. The mean is the sum of all values divided by the number of values and is affected by outliers. The median is the middle value when data is arranged from lowest to highest. The mode is the most frequently occurring value in a data set. Each measure has advantages and disadvantages depending on the type of data distribution. The mean is the most reliable while the mode can be undefined. In symmetrical distributions, the mean, median and mode are equal, but the mean is higher than the median for positively skewed data and lower for negatively skewed data.
This presentation covers statistics, its importance, its applications, branches of statistics, basic concepts used in statistics, data sampling, types of sampling,types of data and collection of data.
Introductory Statistics discusses the definition and history of statistics. Statistics deals with quantitative or numerical data and is the scientific method of collecting, organizing, analyzing, and making decisions with quantitative data. Historically, Indian texts from the Mauryan period and Mughal period contained early forms of statistical analysis of topics like agriculture. The typical process of a statistical study involves defining objectives, identifying the population and characteristics, planning data collection, collecting and organizing data, performing statistical analysis, and drawing conclusions. Statistics is useful for simplifying complex data, quantifying uncertainty, discovering patterns to enable forecasting, and testing assumptions. Statistical techniques have various applications in fields like marketing, economics, finance, operations, human resources, information technology,
The document discusses correlation analysis and different types of correlation. It defines correlation as the linear association between two random variables. There are three main types of correlation:
1) Positive vs negative vs no correlation based on the relationship between two variables as one increases or decreases.
2) Linear vs non-linear correlation based on the shape of the relationship when plotted on a graph.
3) Simple vs multiple vs partial correlation based on the number of variables.
The document also discusses methods for studying correlation including scatter plots, Karl Pearson's coefficient of correlation r, and Spearman's rank correlation coefficient. It provides interpretations of the correlation coefficient r and coefficient of determination r2.
This document discusses correlation analysis and its various types. Correlation is the degree of relationship between two or more variables. There are three stages to solve correlation problems: determining the relationship, measuring significance, and establishing causation. Correlation can be positive, negative, simple, partial, or multiple depending on the direction and number of variables. It is used to understand relationships, reduce uncertainty in predictions, and present average relationships. Conditions like probable error and coefficient of determination help interpret correlation values.
The document discusses various sampling techniques used in research including probability and non-probability sampling. It explains key concepts like population, sample, sampling frame, sampling error, systematic error. It describes different probability sampling designs such as simple random sampling, stratified sampling, cluster sampling and multistage sampling. It also discusses non-probability sampling techniques like convenience sampling and quota sampling. The document provides advantages and limitations of different sampling methods and guidelines for selecting an appropriate sampling design.
diagrammatic and graphical representation of dataVarun Prem Varu
This document discusses various types of diagrams and graphs that can be used to summarize statistical data. It describes one-dimensional, two-dimensional, and three-dimensional diagrams, as well as pictograms, cartograms, histograms, frequency polygons, frequency curves, ogives, and Lorenz curves. The key points are that diagrams and graphs make data simple and allow for easy comparison, while saving time over presenting raw numbers or text. Different types of diagrams and graphs are suited for different types of data and purposes. Guidelines are provided for properly constructing different diagrams.
Statistics play an essential role in scientific research by aiding in tasks like determining sample sizes, testing hypotheses, and interpreting large amounts of data. Various statistical analysis methods are used, including descriptive analysis to summarize data, inferential analysis to generalize from samples to populations, and predictive analysis to forecast future events. Common biological tools for statistics include SPSS, R, MATLAB, SAS, and Excel. Statistics help researchers effectively analyze large datasets and draw meaningful conclusions from their experimental findings.
01 parametric and non parametric statisticsVasant Kothari
Definition of Parametric and Non-parametric Statistics
Assumptions of Parametric and Non-parametric Statistics
Assumptions of Parametric Statistics
Assumptions of Non-parametric Statistics
Advantages of Non-parametric Statistics
Disadvantages of Non-parametric Statistical Tests
Parametric Statistical Tests for Different Samples
Parametric Statistical Measures for Calculating the Difference Between Means
Significance of Difference Between the Means of Two Independent Large and
Small Samples
Significance of the Difference Between the Means of Two Dependent Samples
Significance of the Difference Between the Means of Three or More Samples
Parametric Statistics Measures Related to Pearson’s ‘r’
Non-parametric Tests Used for Inference
This document discusses quantification and statistical techniques in social research. It begins by defining quantification as the act of counting and measuring human observations and experiences to map them to quantities. Quantitative methods emphasize objective measurements and statistical analysis of data from polls, questionnaires, and surveys. The document then discusses how quantification is used in economics and psychology through gathering empirical data and using statistical analysis techniques like regression analysis. It also outlines several statistical techniques used for data analysis, including descriptive, exploratory, inferential, predictive, and causal techniques. Specific statistical methods discussed include mean, standard deviation, regression, sample size determination, and hypothesis testing.
Please think of an employment occupation that utilizes theoretical p.pdfajaycosmeticslg
Please think of an employment occupation that utilizes theoretical probability; and please write
in detail.
Thank you!
Solution
Statisticians: The profession exists in both the public and private sectors.
Statisticians work with theoretical or applied statistics. The field shares much common history
with positivist social science, but often with a greater emphasis on advanced mathematical
methods. For example, in engineering statisticians collect and analyze mathematical data to solve
problems. In manufacturing (they often are employed to support managerial decisions or to
supervise quality control in manufacturing). In government, science and public health,
statisticians make predictions on future such as forecasts on population growth, economic
conditions and the outcome of elections; the core of that work is to measure, interpret, and
describe the world and human activity patterns within it. Using statistical techniques, statisticians
can make some statisticians work to develop the theories on which statistical techniques are
based Thus, they apply their knowledge to many different fields..
Statistics is the collection and analysis of data. There are two main branches: descriptive statistics, which organizes and summarizes data, and inferential statistics, which uses descriptive statistics to make predictions. Statistics starts with a question and uses data to provide information to help make decisions. It is widely used in business, health, education, research, social sciences, and natural resources.
Two main branches of statistics are described: descriptive statistics and inferential statistics. Descriptive statistics focuses on collecting, summarizing, and presenting data, while inferential statistics analyzes sample data to draw conclusions about the overall population. Statistics has many applications including actuarial science, biostatistics, business analytics, demography, econometrics, environmental statistics, epidemiology, geostatistics, operations research, population ecology, psychology, quality control, and various fields of physics.
This document discusses statistical analysis and provides definitions and examples. It defines statistical analysis as the process of collecting and analyzing large volumes of data to identify trends and develop insights. It then describes different types of statistical analysis, including descriptive analysis, inferential analysis, prescriptive analysis, predictive analysis, and causal analysis. The document emphasizes the importance of statistical analysis for businesses, researchers, politicians and more. It concludes by explaining some commonly used statistical analysis methods like standard deviation, hypothesis testing, mean, regression, and sample size determination.
Notes of BBA /B.Com as well as BCA. It will help average students to learn Business Statistics. It will help MBA and PGDM students in Quantitative Analysis.
Statisticians help collect, analyze, and interpret numerical data to solve problems and make predictions. The steps of statistical analysis involve collecting information, evaluating it, and drawing conclusions. Statisticians work in a variety of fields such as medicine, government, education, business, and more. They help determine sampling methods, process data, and advise on the strengths and limitations of statistical results.
This document provides an introduction to statistics. It defines statistics as the science of collecting, organizing, analyzing, and drawing conclusions from data. Data is defined as facts or figures collected for a specific purpose. The document outlines the characteristics of statistics and discusses the functions, scope and limitations of statistics. It also distinguishes between primary and secondary data, discrete and continuous data, and descriptive and inferential statistics.
Statistics plays a vital role in many aspects of human life by helping collect, analyze, and interpret crucial data for decision making. In economics, statistics helps measure growth, forecast trends, and evaluate policies to inform decisions around investments, pricing, and resource allocation. It also helps identify economic inequalities to develop targeted policies that reduce poverty and promote development. Understanding basic statistical concepts, making predictions from data, and critical thinking are important skills for interpreting statistics across fields like business, science, and medicine.
1. The document discusses the introduction to statistics, providing definitions and explaining key concepts. It describes how statistics is used in various fields like education, business, medical research, and agriculture.
2. Statistics is defined as the science of collecting, organizing, summarizing, presenting, analyzing, and interpreting data. It can be used as both a science and an art. Statistics has various applications in fields like administration, business, education, and medical and agricultural research.
3. The document outlines the basic terminology used in statistics, including data, variables, observations, quantitative and qualitative data, continuous and discrete variables. It distinguishes between primary and secondary data and their characteristics.
This document discusses the role and importance of statistics in scientific research. It begins by defining statistics as the science of learning from data and communicating uncertainty. Statistics are important for summarizing, analyzing, and drawing inferences from data in research studies. They also allow researchers to effectively present their findings and support their conclusions. The document then describes how statistics are used and are important in many fields of scientific research like biology, economics, physics, and more. It also provides examples of statistical terms commonly used in research studies and some common misuses of statistics.
- Descriptive statistics are used to describe and summarize key characteristics of a data set.
- They include measures such as counts, means, ranges, and standard deviations.
- Descriptive statistics provide simple summaries about the sample and the measures, but do not make any claims about the population.
- The document provides examples of how descriptive statistics could be used to summarize caseload data from public defender offices.
Statistical software has various applications in fields like medical research, education, business, healthcare, food science, and more. It helps analyze large amounts of data, draw reasonable inferences, and make accurate decisions. In medical research, statistical tools help handle data collection, organization, analysis and interpretation efficiently. In education, software like STATA and SPSS are used for statistical analysis and creating graphs in economics and other social science courses. Statistical software also helps analyze business data across departments to make informed decisions. It allows exploring relationships in clinical trials and quality of patient care in healthcare.
Understanding the importance of statistics transcends mere numbers; it’s a cornerstone in various facets of life, particularly in the dynamic realm of business. Statistics is more than just crunching data; it’s the compass that guides decision-making, unveils patterns, and empowers informed choices within the business landscape. Statistics serves as the language that deciphers the story within data. It helps in interpreting information, spotting trends, and drawing conclusions vital for informed decision-making.
This document provides an overview of statistics used in business management. It defines descriptive and inferential statistics, and notes some common applications like marketing, production, finance, and accounting. Statistics is important for planning, economics, industry, science, education, and war. The document outlines limitations of statistics and provides references for further reading.
The field of statistics is the study of learning from data. Statistical learning causes you to utilize the best possible strategies to gather the information, utilize the right investigations, and adequately present the outcomes
Data science can be applied to public policy in several ways:
1. It can provide evidence from large datasets to support evidence-based policymaking rather than intuition.
2. Predictive modeling using historical data can estimate the impacts of policies on outcomes like the economy or disease.
3. Performance evaluation using pre- and post-policy data can determine if policies are achieving their goals and identify areas for improvement.
Data science uses statistical and computational methods to extract insights from data. In public health, data science is being used to improve disease surveillance, predict outbreaks, and develop targeted interventions. It enables identification of health disparities and data-driven decision making. Machine learning algorithms analyze datasets to identify patterns and develop predictive models for outbreaks and at-risk populations. The future of data science in public health is promising but challenges around privacy, security, and access need to be addressed.
Minimizing the Impact of Forecast Error on Government Monetary and Fiscal Pol...Editor IJCATR
Forecasting is an important part of governments’ monetary and fiscal policies. Every forward-looking government uses economic forecasting as a necessary prerequisite for the success of its monetary and fiscal policies. Though economic forecasts are necessary, as they are essential underlying features of governments’ monetary and fiscal policies, economic forecasting is a difficult task. The difficulty in economic forecasting arises from the interplay of variables which certainly produces forecast errors. This study focused on minimizing the impact of forecast error on government monetary and fiscal policies through the use of suitable forecasting software. Hence in this study, forecasting software are examined as necessary tools for minimizing the impact of forecast errors on governments’ monetary and fiscal policies. Data is collected from both primary and secondary sources to elicit useful information from stakeholders in Forecasting Industry. The result of the study shows that there is a positive relationship between the use of forecasting software and minimizing the impact of forecast error on governments’ monetary and fiscal policies. The study revealed that the use of sound software, devoid of mathematical errors and inappropriate methods, will minimize the impact of forecast error on governments’ monetary and fiscal policies. The study also revealed that the major way to ensure an effective forecasting process and reduce forecast errors is to make use of intelligent forecast software that raises forecast accuracy.
This page include the short and precise overview about geography. It contains all touched knowledge about geography including definition, history and types,
This file contains some amount of information about the waggle dance in honey bees. In this, it is told that how to they communicate with each other to get food from long distances.
Modern method of apiculture - Apiculture - BeekeepingMuhammad Yousaf
The document discusses the modern methods of apiculture (beekeeping). It describes five key parts: 1) the typical movable hive, which allows beekeeping in different locations; 2) the queen excluder, which prevents the queen from entering the honey storage area; 3) the honey extractor, which uses centrifugal force to remove honey from combs without damage; 4) the uncapping knife, which removes wax seals from honey-filled combs; and 5) other equipment like protective gear for safe bee handling. The typical hive framework includes a stand, bottom board, brood chamber for larvae, supers for extra space, inner cover for ventilation, and a top cover for protection from rain.
This file contains detail study of the complement system of immunology. This document includes the introduction to complement system, different pathways including classical pathway, alternative pathway and lectin pathway and also the functions of complement system.
This document contain all of the relative information for apiculture which is also known as Beekeeping.
This document contain mostly related topics such as history, taxonomical classification, types of bees, production of honey and structure of hives.
Introduction to zoogeography and types of distributionMuhammad Yousaf
This document contain smart definitions about zoogeography and tells about the distribution and its types. This is studied in Master classes of zoology in AWKUM.
Multiple Choice Questions of Animal physiologyMuhammad Yousaf
Here are some multiple choice questions about central themes of animal physiology and the membrane potential. This file have 44 MCQs about animal physiology.
Regulation of Respiration - Animal PhysiologyMuhammad Yousaf
This document contain detailed study about The Regulation of Respiration and it covers all of the aspects of terms and topics related to regulation of respiration.
Here are some of the MCQs which will help you while studying and preparing exams of Evolution. This file contain 220 MCQs which will revise your complete study of evolution.
Orthogenesis is the theory that organisms evolve in a definite direction due to some internal mechanism, rejecting natural selection. Allometry describes the relationship between an organism's size and its body parts, such as brain size increasing with body size. Adaptive radiations occur when environmental changes open new niches, causing rapid speciation and phenotypic adaptation in a relatively short time, as seen with Hawaiian honeycreepers adapting to different island environments.
Here is detailed description of pituitary gland, its hormone and its functions in human body. Pituitary gland is also called master gland. This assignment will tell you about the location, size, principle, weight and different lobes of hormones. The study is taken from different internet sources and published paper. Hope it will help you and will give you the knowledge which you want.
This document discusses the concepts and history of systematic zoology and taxonomy. It defines taxonomy as the classification of living things and systematics as the scientific study of diversity and relationships among organisms. It outlines the contributions of taxonomy in fields like epidemiology and wildlife management. The document then discusses the scope of taxonomy, problems in taxonomy, and provides a history of taxonomy from Aristotle to modern molecular systematics approaches.
Lecture 2 CLASSIFICATION OF PHYLUM ARTHROPODA UPTO CLASSES & POSITION OF_1.pptxArshad Shaikh
*Phylum Arthropoda* includes animals with jointed appendages, segmented bodies, and exoskeletons. It's divided into subphyla like Chelicerata (spiders), Crustacea (crabs), Hexapoda (insects), and Myriapoda (millipedes, centipedes). This phylum is one of the most diverse groups of animals.
Title: A Quick and Illustrated Guide to APA Style Referencing (7th Edition)
This visual and beginner-friendly guide simplifies the APA referencing style (7th edition) for academic writing. Designed especially for commerce students and research beginners, it includes:
✅ Real examples from original research papers
✅ Color-coded diagrams for clarity
✅ Key rules for in-text citation and reference list formatting
✅ Free citation tools like Mendeley & Zotero explained
Whether you're writing a college assignment, dissertation, or academic article, this guide will help you cite your sources correctly, confidently, and consistent.
Created by: Prof. Ishika Ghosh,
Faculty.
📩 For queries or feedback: ishikaghosh9@gmail.com
Redesigning Education as a Cognitive Ecosystem: Practical Insights into Emerg...Leonel Morgado
Slides used at the Invited Talk at the Harvard - Education University of Hong Kong - Stanford Joint Symposium, "Emerging Technologies and Future Talents", 2025-05-10, Hong Kong, China.
What is the Philosophy of Statistics? (and how I was drawn to it)jemille6
What is the Philosophy of Statistics? (and how I was drawn to it)
Deborah G Mayo
At Dept of Philosophy, Virginia Tech
April 30, 2025
ABSTRACT: I give an introductory discussion of two key philosophical controversies in statistics in relation to today’s "replication crisis" in science: the role of probability, and the nature of evidence, in error-prone inference. I begin with a simple principle: We don’t have evidence for a claim C if little, if anything, has been done that would have found C false (or specifically flawed), even if it is. Along the way, I’ll sprinkle in some autobiographical reflections.
Form View Attributes in Odoo 18 - Odoo SlidesCeline George
Odoo is a versatile and powerful open-source business management software, allows users to customize their interfaces for an enhanced user experience. A key element of this customization is the utilization of Form View attributes.
Happy May and Taurus Season.
♥☽✷♥We have a large viewing audience for Presentations. So far my Free Workshop Presentations are doing excellent on views. I just started weeks ago within May. I am also sponsoring Alison within my blog and courses upcoming. See our Temple office for ongoing weekly updates.
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♥☽About: I am Adult EDU Vocational, Ordained, Certified and Experienced. Course genres are personal development for holistic health, healing, and self care/self serve.
What makes space feel generous, and how architecture address this generosity in terms of atmosphere, metrics, and the implications of its scale? This edition of #Untagged explores these and other questions in its presentation of the 2024 edition of the Master in Collective Housing. The Master of Architecture in Collective Housing, MCH, is a postgraduate full-time international professional program of advanced architecture design in collective housing presented by Universidad Politécnica of Madrid (UPM) and Swiss Federal Institute of Technology (ETH).
Yearbook MCH 2024. Master in Advanced Studies in Collective Housing UPM - ETH
Computer crime and Legal issues Computer crime and Legal issuesAbhijit Bodhe
• Computer crime and Legal issues: Intellectual property.
• privacy issues.
• Criminal Justice system for forensic.
• audit/investigative.
• situations and digital crime procedure/standards for extraction,
preservation, and deposition of legal evidence in a court of law.
A measles outbreak originating in West Texas has been linked to confirmed cases in New Mexico, with additional cases reported in Oklahoma and Kansas. The current case count is 817 from Texas, New Mexico, Oklahoma, and Kansas. 97 individuals have required hospitalization, and 3 deaths, 2 children in Texas and one adult in New Mexico. These fatalities mark the first measles-related deaths in the United States since 2015 and the first pediatric measles death since 2003.
The YSPH Virtual Medical Operations Center Briefs (VMOC) were created as a service-learning project by faculty and graduate students at the Yale School of Public Health in response to the 2010 Haiti Earthquake. Each year, the VMOC Briefs are produced by students enrolled in Environmental Health Science Course 581 - Public Health Emergencies: Disaster Planning and Response. These briefs compile diverse information sources – including status reports, maps, news articles, and web content– into a single, easily digestible document that can be widely shared and used interactively. Key features of this report include:
- Comprehensive Overview: Provides situation updates, maps, relevant news, and web resources.
- Accessibility: Designed for easy reading, wide distribution, and interactive use.
- Collaboration: The “unlocked" format enables other responders to share, copy, and adapt seamlessly. The students learn by doing, quickly discovering how and where to find critical information and presenting it in an easily understood manner.
CURRENT CASE COUNT: 817 (As of 05/3/2025)
• Texas: 688 (+20)(62% of these cases are in Gaines County).
• New Mexico: 67 (+1 )(92.4% of the cases are from Eddy County)
• Oklahoma: 16 (+1)
• Kansas: 46 (32% of the cases are from Gray County)
HOSPITALIZATIONS: 97 (+2)
• Texas: 89 (+2) - This is 13.02% of all TX cases.
• New Mexico: 7 - This is 10.6% of all NM cases.
• Kansas: 1 - This is 2.7% of all KS cases.
DEATHS: 3
• Texas: 2 – This is 0.31% of all cases
• New Mexico: 1 – This is 1.54% of all cases
US NATIONAL CASE COUNT: 967 (Confirmed and suspected):
INTERNATIONAL SPREAD (As of 4/2/2025)
• Mexico – 865 (+58)
‒Chihuahua, Mexico: 844 (+58) cases, 3 hospitalizations, 1 fatality
• Canada: 1531 (+270) (This reflects Ontario's Outbreak, which began 11/24)
‒Ontario, Canada – 1243 (+223) cases, 84 hospitalizations.
• Europe: 6,814
In this concise presentation, Dr. G.S. Virdi (Former Chief Scientist, CSIR-CEERI, Pilani) introduces the Junction Field-Effect Transistor (JFET)—a cornerstone of modern analog electronics. You’ll discover:
Why JFETs? Learn how their high input impedance and low noise solve the drawbacks of bipolar transistors.
JFET vs. MOSFET: Understand the core differences between JFET and MOSFET devices.
Internal Structure: See how source, drain, gate, and the depletion region form a controllable semiconductor channel.
Real-World Applications: Explore where JFETs power amplifiers, sensors, and precision circuits.
Perfect for electronics students, hobbyists, and practicing engineers looking for a clear, practical guide to JFET technology.
Rock Art As a Source of Ancient Indian HistoryVirag Sontakke
This Presentation is prepared for Graduate Students. A presentation that provides basic information about the topic. Students should seek further information from the recommended books and articles. This presentation is only for students and purely for academic purposes. I took/copied the pictures/maps included in the presentation are from the internet. The presenter is thankful to them and herewith courtesy is given to all. This presentation is only for academic purposes.
Rock Art As a Source of Ancient Indian HistoryVirag Sontakke
SCOPE, IMPORTANCE & USES OF STATISTICS
1. SCOPE, IMPORTANCE & USES
OF STATISTICS
yousaf rafique
Yousaf1438@gmail.com
Written by:
Muhammad Yousaf
2. Importance, Scope & uses
of Statistics
Importance
Statistics plays a vital role in every field of human activity. Statistics helps in determining the
existing position of per capita income, unemployment, population growth rates, housing,
schooling medical facilities, etc., in a country.
It helps in summarizing the larger sets of data in a form that is easily understandable
and play a role in the efficient design of laboratory and field experiments as well as
surveys.
Statistical techniques act as powerful tools for analyzing numerical data, used in
genetics, agronomy, anthropometry, astronomy, physics, geology etc.
Statistics play a role in business, economics, mathematics, banking, state
management, accounting and auditing, natural and social sciences and astronomy.
Statistics is useful subject in many areas such as business, economics, engineering,
health, accounting and social as well as natural, so statistics is applied in every
human activity.
Statistics tells us any trends in what happened in the past and can be useful in
predicting what may happen in future.
Scope
Statistics and planning: Statistics in indispensable into planning in the modern age
which is termed as “the age of planning”. Almost all over the world the governments
are re-storing to planning for economic development.
Statistics and economics: Statistical data and techniques of statistical analysis have
to immensely useful involving economical problem. Such as wages, price, time series
analysis, demand analysis.
Statistics and business: Statistics is an irresponsible tool of production control.
Business executive are relying more and more on statistical techniques for studying
the much and desire of the valued customers.
Statistics and industry: In industry statistics is widely used inequality control. In
production engineering to find out whether the product is confirming to the
specifications or not. Statistical tools, such as inspection plan, control chart etc.
Statistics and mathematics: Statistics are intimately related recent advancements in
statistical technique are the outcome of wide applications of mathematics.
Statistics and modern science: In medical science the statistical tools for collection,
presentation and analysis of observed facts relating to causes and incidence of
dieses and the result of application various drugs and medicine are of great
importance.
Statistics, psychology and education: In education and physiology statistics has
found wide application such as, determining or to determine the reliability and validity
to a test, factor analysis etc.
3. Uses of Statistics
Statistics is widely employed in government, business and natural and social sciences.
Statistical methods are applied in al fields that involve decision making, for making accurate
inferences from a collated body of data and for making decisions in the face of uncertainty
based on statistical methodology.
The use of modern computers has expedited large scale statistical computations, and also
made possible new methods that are impractical to perform manually.
Statistics continues to be an area of active research, for example on the problem of how to
analyze big data.
In marketing, statistical methods help in forecasting sales, market share and demand for
various types of industrial products.
Statistics helps in understanding the nature and pattern of variability of a phenomenon
through quantitative observations.
Statistics helps in presenting complex data in a suitable tabular, diagrammaticand
graphic form for easy and clear comprehension of the data.