Statistics is the science of extracting useful knowledge from experiments and data. It is used for data collection, analysis, and interpretation in many fields of science and business. The word "statistics" originated from terms meaning "political state" and was initially used by rulers to gather information on lands, populations, and commerce. While basic statistical methods have long been used, the field grew significantly in the 20th century with advances in computing power and the development of new statistical techniques and theories by prominent statisticians.
The median is the middlemost score when values are arranged from lowest to highest. It divides the data set into two equal groups, with scores above and below the median. The median is not affected by extreme values and can be used when the mean would be skewed. To find the median of ungrouped data, arrange values from highest to lowest and take the middle value. For grouped data, use the formula Median = Ll + cfb/f, where Ll is the lower limit of the class containing N/2, cfb is the cumulative frequency below the assumed median, and f is the corresponding frequency.
The document provides information about constellations from different perspectives. It discusses how ancient cultures imagined patterns in the stars and gave them names representing animals, objects, and people. It also explains how constellations like Orion were seen differently by various early civilizations. Additionally, it describes how constellations like Gemini were used by the Matigsalug Manobo people of the Philippines to indicate agricultural seasons and activities. Finally, it discusses the current uses of constellations by astronomers for naming and locating stars, and their differing roles in astronomy versus astrology.
This document discusses leadership and defines leaders as individuals who influence and guide the actions and thoughts of others. It provides several definitions of leadership from different authors and describes key characteristics and skills of effective leaders, including interpersonal skills, self-management, influencing others, and goal achievement. The document also outlines methods for identifying leaders, such as sociometric methods, informants' ratings, self-designating techniques, and observation. It concludes by describing early adopters as localities that are more integrated in the community and have more opinion leadership.
(1) Srinivasa Ramanujan was a renowned Indian mathematician who made extraordinary contributions to mathematical analysis, number theory, infinite series, and continued fractions despite having little formal training in pure mathematics.
(2) He was born in 1887 in India and showed an extraordinary aptitude for mathematics from a young age, mastering advanced mathematical concepts including trigonometry at age 13.
(3) Ramanujan received recognition for his genius and was invited to study at Trinity College, Cambridge in England. However, he struggled with the climate and culture in England and his health declined, and he ultimately returned to India where he passed away in 1920 at the young age of 32.
Lesson plan on Evaluating Rational Algebraic ExpressionLorie Jane Letada
This document is a lesson plan for teaching evaluating rational algebraic expressions in Math 8. It outlines the intended learning outcomes, learning content including reference materials, and learning experiences including an interactive game and riddle for students to solve rational expressions. The lesson plan was prepared by Lorie Jane L. Letada and will be observed by Assistant Principal Eleanor D. Gallardo during their class meeting on Google Meet from 2-3 PM on November 24, 2020.
This document summarizes key concepts from an introduction to statistics textbook. It covers types of data (quantitative, qualitative, levels of measurement), sampling (population, sample, randomization), experimental design (observational studies, experiments, controlling variables), and potential misuses of statistics (bad samples, misleading graphs, distorted percentages). The goal is to illustrate how common sense is needed to properly interpret data and statistics.
This document provides an introduction to key statistical concepts and terms. It defines statistics as a branch of mathematics dealing with collecting, organizing, analyzing, and interpreting numerical data. Some key points:
- Data can be quantitative (numerical) or qualitative (descriptive attributes). Population refers to all elements being studied, while a sample is a subset of the population.
- Parameters describe populations and statistics describe samples. Variables differentiate groups within a population or sample.
- Descriptive statistics summarize and present data, while inferential statistics draw conclusions about populations from samples.
- The history of statistics dates back thousands of years to early censuses, though modern statistical theory developed more recently over the 18th-19
This document provides an introduction to statistics. It defines statistics as the scientific methods for collecting, organizing, summarizing, presenting and analyzing data to derive valid conclusions. Statistics is useful across many fields and careers as it helps make informed decisions based on data. The document outlines descriptive and inferential statistics, and notes that descriptive statistics simplifies complexity while inferential statistics allows for conclusions to be drawn. It also discusses types of data sources, including primary data collected directly and secondary data that has already been collected.
Statistics originated from the Italian word 'stato' meaning state. Initially, kings and governments used statistics to collect information about a state's population, agriculture, wealth, and other areas to understand its administrative requirements. One of the earliest known censuses was carried out in Egypt in 3050 BC. In India, systematic collection of statistics began during the reign of Emperor Chandragupta Maurya in the 3rd century BC under the guidance of Kautilya as described in the Arthashastra text. During Emperor Akbar's rule from 1556-1605, officials like Raja Todar Mal kept detailed records of land and revenue which helped establish a systematic tax collection system. The British government began regular publication
This document provides an introduction to key concepts in statistics. It discusses various statistical measures such as measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation), correlation, and different types of correlation (simple, partial, multiple). It also outlines common statistical methods like scatter diagrams, Karl Pearson's method, and rank correlation method. The role of computer technology in statistics is mentioned.
Statistics are used widely in many areas of real life including weather forecasting, emergency preparedness, disease prediction, education, genetics, politics, quality testing, business, banking, insurance, government administration, astronomy, and the natural and social sciences. Some key examples provided include how weather models use statistics to predict future weather, emergency teams rely on statistics to prepare for danger, disease rates are calculated using statistics, teachers evaluate students' performance statistically, and businesses use statistics to plan production and marketing.
This document defines and discusses quartiles, deciles, and percentiles. Quartiles divide a data set into four equal parts, with the first quartile (Q1) representing the lowest 25% of values. Deciles divide data into ten equal parts. Percentiles indicate the value below which a certain percentage of observations fall. Examples are provided for calculating Q1, Q3, D1 using formulas for grouped and ungrouped data sets. Quartiles, deciles, and percentiles are commonly used to summarize and report on statistical data.
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This document provides an introduction to statistics. It discusses why statistics is important and required for many programs. Reasons include the prevalence of numerical data in daily life, the use of statistical techniques to make decisions that affect people, and the need to understand how data is used to make informed decisions. The document also defines key statistical concepts such as population, parameter, sample, statistic, descriptive statistics, inferential statistics, variables, and different types of variables.
This document discusses measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each measure. The mean is the average and is calculated by summing all values and dividing by the total number of items. The median is the middle value when items are arranged from lowest to highest. The mode is the value that occurs most frequently in a data set. Examples are given to demonstrate calculating each measure using raw data.
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 document discusses measures of central tendency, including the mean, median, and mode. It provides examples of calculating each measure using sample data sets. The mean is the average value calculated by summing all values and dividing by the number of data points. The median is the middle value when data is ordered from lowest to highest. The mode is the most frequently occurring value. Examples are given to demonstrate calculating the mean, median, and mode from sets of numeric 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,
This document provides an overview of basic statistics concepts including:
- Statistics is used to determine the difference between chance and real effects by analyzing numerical data
- Averages can be calculated and presented in different ways (mean, median, mode), which can provide different perspectives on the data
- Statistics is applied in many fields to help with planning, assessing programs, and proving or disproving economic theories
- Common statistical tools include variables, matrices, frequency tables, probability calculations
- Limitations include that statistics deals with aggregates and variability rather than individual accuracy, and numbers can be misused out of context
Basic statistics is the science of collecting, organizing, summarizing, and interpreting data. It allows researchers to gain insights from data through graphical or numerical summaries, regardless of the amount of data. Descriptive statistics can be used to describe single variables through frequencies, percentages, means, and standard deviations. Inferential statistics make inferences about phenomena through hypothesis testing, correlations, and predicting relationships between variables.
Introduction to Statistics - Basic concepts
- How to be a good doctor - A step in Health promotion
- By Ibrahim A. Abdelhaleem - Zagazig Medical Research Society (ZMRS)
Descriptive statistics are methods of describing the characteristics of a data set. It includes calculating things such as the average of the data, its spread and the shape it produces.
This presentation includes an introduction to statistics, introduction to sampling methods, collection of data, classification and tabulation, frequency distribution, graphs and measures of central tendency.
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.
This document provides an overview of basic statistics concepts. It defines statistics as the science of dealing with variability and uncertainty in data to make objective decisions. Key concepts discussed include populations, samples, variables, constants, and common statistical tools. Statistics involves both the mathematical analysis of data as well as the interpretation and presentation of results. The goal of statistics is to make observations about populations based on samples in order to draw accurate conclusions.
This document provides an overview of statistics as a subject. It discusses that statistics has applications in many fields like agriculture, economics, commerce, biology, etc. The word "statistics" is derived from the Latin word "status" meaning state. Statistics involves collecting, organizing, analyzing and interpreting numerical data to make conclusions and decisions. It has various functions like condensation, comparison, forecasting and testing hypotheses. Statistics has limitations as well, as it does not study individuals or qualitative phenomena. The document also discusses topics like scope of statistics, collection of data, classification and tabulation of data.
1. The document discusses the meaning, uses, functions, importance and limitations of statistics. It defines statistics as the collection, presentation, analysis and interpretation of numerical data.
2. Statistics has various uses across different fields such as policy planning, management, education, commerce and accounts. It helps present facts precisely and enables comparison, correlation, formulation and testing of hypotheses, and forecasting.
3. While statistics is important for planning, administration, economics and more, it also has limitations such as only studying aggregates, numerical data, and being an average. Statistics can also be misused if not used carefully by experts.
This document summarizes key concepts from an introduction to statistics textbook. It covers types of data (quantitative, qualitative, levels of measurement), sampling (population, sample, randomization), experimental design (observational studies, experiments, controlling variables), and potential misuses of statistics (bad samples, misleading graphs, distorted percentages). The goal is to illustrate how common sense is needed to properly interpret data and statistics.
This document provides an introduction to key statistical concepts and terms. It defines statistics as a branch of mathematics dealing with collecting, organizing, analyzing, and interpreting numerical data. Some key points:
- Data can be quantitative (numerical) or qualitative (descriptive attributes). Population refers to all elements being studied, while a sample is a subset of the population.
- Parameters describe populations and statistics describe samples. Variables differentiate groups within a population or sample.
- Descriptive statistics summarize and present data, while inferential statistics draw conclusions about populations from samples.
- The history of statistics dates back thousands of years to early censuses, though modern statistical theory developed more recently over the 18th-19
This document provides an introduction to statistics. It defines statistics as the scientific methods for collecting, organizing, summarizing, presenting and analyzing data to derive valid conclusions. Statistics is useful across many fields and careers as it helps make informed decisions based on data. The document outlines descriptive and inferential statistics, and notes that descriptive statistics simplifies complexity while inferential statistics allows for conclusions to be drawn. It also discusses types of data sources, including primary data collected directly and secondary data that has already been collected.
Statistics originated from the Italian word 'stato' meaning state. Initially, kings and governments used statistics to collect information about a state's population, agriculture, wealth, and other areas to understand its administrative requirements. One of the earliest known censuses was carried out in Egypt in 3050 BC. In India, systematic collection of statistics began during the reign of Emperor Chandragupta Maurya in the 3rd century BC under the guidance of Kautilya as described in the Arthashastra text. During Emperor Akbar's rule from 1556-1605, officials like Raja Todar Mal kept detailed records of land and revenue which helped establish a systematic tax collection system. The British government began regular publication
This document provides an introduction to key concepts in statistics. It discusses various statistical measures such as measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation), correlation, and different types of correlation (simple, partial, multiple). It also outlines common statistical methods like scatter diagrams, Karl Pearson's method, and rank correlation method. The role of computer technology in statistics is mentioned.
Statistics are used widely in many areas of real life including weather forecasting, emergency preparedness, disease prediction, education, genetics, politics, quality testing, business, banking, insurance, government administration, astronomy, and the natural and social sciences. Some key examples provided include how weather models use statistics to predict future weather, emergency teams rely on statistics to prepare for danger, disease rates are calculated using statistics, teachers evaluate students' performance statistically, and businesses use statistics to plan production and marketing.
This document defines and discusses quartiles, deciles, and percentiles. Quartiles divide a data set into four equal parts, with the first quartile (Q1) representing the lowest 25% of values. Deciles divide data into ten equal parts. Percentiles indicate the value below which a certain percentage of observations fall. Examples are provided for calculating Q1, Q3, D1 using formulas for grouped and ungrouped data sets. Quartiles, deciles, and percentiles are commonly used to summarize and report on statistical data.
If you happen to like this powerpoint, you may contact me at flippedchannel@gmail.com
I offer some educational services like:
-powerpoint presentation maker
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-content creator
-layout designer
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This document provides an introduction to statistics. It discusses why statistics is important and required for many programs. Reasons include the prevalence of numerical data in daily life, the use of statistical techniques to make decisions that affect people, and the need to understand how data is used to make informed decisions. The document also defines key statistical concepts such as population, parameter, sample, statistic, descriptive statistics, inferential statistics, variables, and different types of variables.
This document discusses measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each measure. The mean is the average and is calculated by summing all values and dividing by the total number of items. The median is the middle value when items are arranged from lowest to highest. The mode is the value that occurs most frequently in a data set. Examples are given to demonstrate calculating each measure using raw data.
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 document discusses measures of central tendency, including the mean, median, and mode. It provides examples of calculating each measure using sample data sets. The mean is the average value calculated by summing all values and dividing by the number of data points. The median is the middle value when data is ordered from lowest to highest. The mode is the most frequently occurring value. Examples are given to demonstrate calculating the mean, median, and mode from sets of numeric 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,
This document provides an overview of basic statistics concepts including:
- Statistics is used to determine the difference between chance and real effects by analyzing numerical data
- Averages can be calculated and presented in different ways (mean, median, mode), which can provide different perspectives on the data
- Statistics is applied in many fields to help with planning, assessing programs, and proving or disproving economic theories
- Common statistical tools include variables, matrices, frequency tables, probability calculations
- Limitations include that statistics deals with aggregates and variability rather than individual accuracy, and numbers can be misused out of context
Basic statistics is the science of collecting, organizing, summarizing, and interpreting data. It allows researchers to gain insights from data through graphical or numerical summaries, regardless of the amount of data. Descriptive statistics can be used to describe single variables through frequencies, percentages, means, and standard deviations. Inferential statistics make inferences about phenomena through hypothesis testing, correlations, and predicting relationships between variables.
Introduction to Statistics - Basic concepts
- How to be a good doctor - A step in Health promotion
- By Ibrahim A. Abdelhaleem - Zagazig Medical Research Society (ZMRS)
Descriptive statistics are methods of describing the characteristics of a data set. It includes calculating things such as the average of the data, its spread and the shape it produces.
This presentation includes an introduction to statistics, introduction to sampling methods, collection of data, classification and tabulation, frequency distribution, graphs and measures of central tendency.
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.
This document provides an overview of basic statistics concepts. It defines statistics as the science of dealing with variability and uncertainty in data to make objective decisions. Key concepts discussed include populations, samples, variables, constants, and common statistical tools. Statistics involves both the mathematical analysis of data as well as the interpretation and presentation of results. The goal of statistics is to make observations about populations based on samples in order to draw accurate conclusions.
This document provides an overview of statistics as a subject. It discusses that statistics has applications in many fields like agriculture, economics, commerce, biology, etc. The word "statistics" is derived from the Latin word "status" meaning state. Statistics involves collecting, organizing, analyzing and interpreting numerical data to make conclusions and decisions. It has various functions like condensation, comparison, forecasting and testing hypotheses. Statistics has limitations as well, as it does not study individuals or qualitative phenomena. The document also discusses topics like scope of statistics, collection of data, classification and tabulation of data.
1. The document discusses the meaning, uses, functions, importance and limitations of statistics. It defines statistics as the collection, presentation, analysis and interpretation of numerical data.
2. Statistics has various uses across different fields such as policy planning, management, education, commerce and accounts. It helps present facts precisely and enables comparison, correlation, formulation and testing of hypotheses, and forecasting.
3. While statistics is important for planning, administration, economics and more, it also has limitations such as only studying aggregates, numerical data, and being an average. Statistics can also be misused if not used carefully by experts.
This document provides information about a statistics course, including:
- The course is taught by Prof. T RAMA KRISHNA RAO and covers 5 units: measures of central tendency, measures of variation, correlation analysis, index numbers, and time series analysis.
- Previous year question papers from 2016-2013 are provided, with questions on topics like defining statistics, classification vs tabulation, and representing data visually.
- Key concepts from the first unit on statistics are defined, like data, characteristics of statistics, importance and scope of statistics, and limitations of statistics. Data sources like primary and secondary data are also mentioned.
Statistics is a basic and important tool for professionals in all fields all over the worlds. This document provides the importance and scope of Statistics in major fields of study like a business, management, planning etc.
This document provides an overview of statistics as a field of study. It defines statistics as both the plural and singular form, describing aggregates of numerical data and the science dealing with collecting, organizing, and interpreting numerical data. The two main branches of statistics are described as descriptive statistics, which describes what is occurring in a data set, and inferential statistics, which allows making generalizations about a larger population based on a sample. Key terms like data, variables, population, sample, and parameter are also defined. The stages of a statistical investigation and applications, uses, and limitations of statistics are summarized.
This document provides definitions, scope and limitations of statistics. It defines statistics as the science of collecting, organizing, summarizing, presenting and analyzing data to derive valid conclusions. Statistics has applications in many fields including industry, commerce, agriculture, economics, education, planning and medicine. While statistics is a useful tool, it also has limitations such as not being suitable for qualitative phenomena, not studying individuals, statistical laws being approximations rather than exact, and potential for misuse if not applied properly by experts.
Basics of Research Types of Data ClassificationHarshit Pandey
This document provides an introduction and overview of research methods and statistics. It begins by outlining the origins and early contributors to statistics as a field, including its use in state administration starting in the 17th century. Key concepts in statistics such as variables, populations, samples, and levels of measurement are then defined. The document distinguishes between descriptive and inferential statistics, outlining common techniques for each. It concludes by discussing the scope and limitations of statistics as a scientific discipline.
Statistics is the science of collecting, analyzing, and interpreting numerical data. It has evolved from early uses by governments to understand populations for taxation and military purposes. Modern statistics developed in the 18th-19th centuries and saw rapid growth in the 20th century with advances in computing. Statistics has two main branches - descriptive statistics which involves data presentation and inference statistics which uses data analysis to make estimates and test hypotheses. Statistics is widely used across many fields including business, economics, mathematics, and banking to facilitate decision making.
This document provides an introduction to business statistics. It defines statistics as the science of collecting, organizing, analyzing, and interpreting numerical data. The document notes that statistics can refer to both quantitative information and the methods used to analyze that information. It describes the key stages of a statistical analysis: data collection, organization, presentation, analysis, and interpretation. The document also discusses whether statistics is a science or an art and the important functions of statistics like providing definiteness, enabling comparison, and aiding in prediction.
Definition, functions, scope, limitations of statistics; diagrams and graphs; basic definitions and rules for probability, conditional probability and independence of events.
Statistics From Wikipedia, the free encyclopedia Jump to navigation.pdfARYAN20071
Statistics From Wikipedia, the free encyclopedia Jump to: navigation, search This article is
about the discipline. For other uses, see Statistics (disambiguation). Statistics is the study of the
collection, organization, analysis, interpretation and presentation of data.[1][2] It deals with all
aspects of this, including the planning of data collection in terms of the design of surveys and
experiments.[1] A statistician is someone who is particularly well-versed in the ways of thinking
necessary for the successful application of statistical analysis. Such people have often gained
experience through working in any of a wide number of fields. There is also a discipline called
mathematical statistics that studies statistics mathematically. The word statistics, when referring
to the scientific discipline, is singular, as in \"Statistics is an art.\"[3] This should not be confused
with the word statistic, referring to a quantity (such as mean or median) calculated from a set of
data,[4] whose plural is statistics (\"this statistic seems wrong\" or \"these statistics are
misleading\"). More probability density will be found the closer one gets to the expected (mean)
value in a normal distribution. Statistics used in standardized testing assessment are shown. The
scales include standard deviations, cumulative percentages, percentile equivalents, Z-scores, T-
scores, standard nines, and percentages in standard nines. Contents 1 Scope 2 History 3
Overview 4 Statistical methods 4.1 Experimental and observational studies 4.2 Levels of
measurement 4.3 Key terms used in statistics 4.4 Examples 5 Specialized disciplines 6 Statistical
computing 7 Misuse 8 Statistics applied to mathematics or the arts 9 See also 10 References
Scope Some consider statistics to be a mathematical body of science pertaining to the collection,
analysis, interpretation or explanation, and presentation of data,[5] while others consider it a
branch of mathematics[6] concerned with collecting and interpreting data. Because of its
empirical roots and its focus on applications, statistics is usually considered to be a distinct
mathematical science rather than a branch of mathematics.[7][8] Much of statistics is non-
mathematical: ensuring that data collection is undertaken in a way that allows valid conclusions
to be drawn; coding and archiving of data so that information is retained and made useful for
international comparisons of official statistics; reporting of results and summarised data (tables
and graphs) in ways that are comprehensible to those who need to make use of them;
implementing procedures that ensure the privacy of census information. Statisticians improve
the quality of data by coming up with a specific design of experiments and survey sampling.
Statistics itself also provides tools for prediction and forecasting the use of data and statistical
models. Statistics is applicable to a wide variety of academic disciplines, including natural and
social sciences, government.
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.
Unit 1 Introduction to Statistics with history (1).pptxDrSJayashree
This document provides an overview of an introductory statistics course, outlining 6 units of study and their associated hours. Unit 1 covers basic concepts for 5 hours. Unit 2 covers diagrams and graphs for 7 hours. Unit 3 covers measures of central tendency, like mean, median and mode, for 15 hours. Unit 4 covers measures of dispersion like range and standard deviation for 13 hours. Unit 5 covers correlation and regression analysis for 10 hours. Unit 6 covers time series analysis for 10 hours.
This document provides an overview of descriptive statistics as taught in a statistics course (STS 102) at Crescent University, Nigeria. It covers topics like statistical data collection methods, presentation of data through tables and graphs, measures of central tendency and dispersion. The key objectives of descriptive statistics are to summarize and describe characteristics of data through measures, charts and diagrams. Inferential statistics is also introduced as a way to make inferences about populations based on samples.
For the last few centuries, statistics has remained a part of mathematics as the original
work was done by mathematicians like Pascal (1623-1662), James Bernoulli (1654-1705),
De Moivre (1667-1754), Laplace (1749-1827), Gauss (1777-1855), Lagrange, Bayes,
Markoff, Euler etc. These mathematicians were mainly interested in the development of
the theory of probability as applied to the theory of games and other chance phenomena.
Till early nineteenth century, statistics was mainly concerned with official statistics needed
for the collection of information on revenue, population and area of land under cultivation
etc. of a state or kingdom.
The science of statistics developed gradually and its field of application widened day
by day. Hence, it is difficult to give an exact definition of statistics. The definition changed
from time to time depending upon its use and application. Numerous definitions have
been coined by different people. These definitions reflect the statistical angle and field of
activity.
Happy May and Taurus Season.
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How to Configure Public Holidays & Mandatory Days in Odoo 18Celine George
In this slide, we’ll explore the steps to set up and manage Public Holidays and Mandatory Days in Odoo 18 effectively. Managing Public Holidays and Mandatory Days is essential for maintaining an organized and compliant work schedule in any organization.
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.
Lecture 1 Introduction history and institutes of entomology_1.pptxArshad Shaikh
*Entomology* is the scientific study of insects, including their behavior, ecology, evolution, classification, and management.
Entomology continues to evolve, incorporating new technologies and approaches to understand and manage insect populations.
How to Clean Your Contacts Using the Deduplication Menu in Odoo 18Celine George
In this slide, we’ll discuss on how to clean your contacts using the Deduplication Menu in Odoo 18. Maintaining a clean and organized contact database is essential for effective business operations.
This slide is an exercise for the inquisitive students preparing for the competitive examinations of the undergraduate and postgraduate students. An attempt is being made to present the slide keeping in mind the New Education Policy (NEP). An attempt has been made to give the references of the facts at the end of the slide. If new facts are discovered in the near future, this slide will be revised.
This presentation is related to the brief History of Kashmir (Part-I) with special reference to Karkota Dynasty. In the seventh century a person named Durlabhvardhan founded the Karkot dynasty in Kashmir. He was a functionary of Baladitya, the last king of the Gonanda dynasty. This dynasty ruled Kashmir before the Karkot dynasty. He was a powerful king. Huansang tells us that in his time Taxila, Singhpur, Ursha, Punch and Rajputana were parts of the Kashmir state.
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.
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
The insect cuticle is a tough, external exoskeleton composed of chitin and proteins, providing protection and support. However, as insects grow, they need to shed this cuticle periodically through a process called moulting. During moulting, a new cuticle is prepared underneath, and the old one is shed, allowing the insect to grow, repair damaged cuticle, and change form. This process is crucial for insect development and growth, enabling them to transition from one stage to another, such as from larva to pupa or adult.
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Created by: Prof. Ishika Ghosh,
Faculty.
📩 For queries or feedback: ishikaghosh9@gmail.com
2. INTRODUCTION
In the modern world of computers and information
technology, the importance of statistics is very well
recognized by all the disciplines. Statistics has
originated as a science of statehood and found
applications slowly and steadily in Agriculture,
Economics, Commerce, Biology, Medicine, Industry,
planning, education and so on. As on date there is no
other human walk of life, where statistics cannot be
applied.
3. ORIGIN AND GROWTH OF STATISTICS
The word ‘ Statistics’ and ‘ Statistical’ are all derived
from the Latin word Status, means a political state.
The theory of statistics as a distinct branch of
scientific method is of comparatively recent growth.
Research particularly into the mathematical theory of
statistics is rapidly proceeding and fresh discoveries
are being made all over the world.
4. MEANING OF STATISTICS
Statistics is concerned with scientific methods for
collecting, organizing, summarizing, presenting and
analyzing data as well as deriving valid conclusions
and making reasonable decisions on the basis of this
analysis. Statistics is concerned with the systematic
collection of numerical data and its interpretation. The
word ‘ statistic’ is used to refer to
1. Numerical facts, such as the number of people
living in particular area.
2. The study of ways of collecting, analyzing and
interpreting the facts.
5. DEFINITIONS
Statistics is defined differently by different authors
over a period of time. In the olden days statistics was
confined to only state affairs but in modern days it
embraces almost every sphere of human activity.
Therefore a number of old definitions, which was
confined to narrow field of enquiry were replaced by
more definitions, which are much more
comprehensive and exhaustive. Secondly, statistics
has been defined in two different ways Statistical data
and statistical methods. The following are some of the
definitions of statistics as numerical data.
6. CONT..
1. Statistics are the classified facts representing
the conditions of people in a state. In
particular they are the facts, which can
be stated in numbers or in tables of
numbers or in any tabular or classified
arrangement.
2. Statistics are measurements, enumerations or
estimates of natural phenomenon usually
systematically arranged, analyzed and
presented as to exhibit important
interrelationships among them.
7. DEFINITIONS BY A.L. BOWLEY
Statistics are numerical statement of facts in any
department of enquiry placed in relation to each
other. - A.L. Bowley Statistics may be called the
science of counting in one of the departments due to
Bowley, obviously this is an incomplete definition as it
takes into account only the aspect of collection and
ignores other aspects such as analysis, presentation
and interpretation.
8. CONT.…
Bowley gives another definition for statistics, which
states‘ statistics may be rightly called the scheme of
averages’ . This definition is also incomplete, as
averages play an important role in understanding and
comparing data and statistics provide more
measures.
9. DEFINITION BY CROXTON AND COWDEN
Statistics may be defined as the science of collection,
presentation analysis and interpretation of numerical
data from the logical analysis. It is clear that the
definition of statistics by Croxton and Cowden is the
most scientific and realistic one. According to this
definition there are four stages:
10. COLLECTION OF DATA
It is the first step and this is the foundation upon
which the entire data set. Careful planning is
essential before collecting the data. There are
different methods of collection of data such as
census, sampling, primary, secondary, etc., and the
investigator should make use of correct method.
11. PRESENTATION OF DATA
The mass data collected should be presented in a
suitable, concise form for further analysis. The
collected data may be presented in the form of
tabular or diagrammatic or graphic form.
12. ANALYSIS OF DATA:
The data presented should be carefully analyzed for
making inference from the presented data such as
measures of central tendencies, dispersion,
correlation, regression etc.,
13. INTERPRETATION OF DATA
The final step is drawing conclusion from the data
collected. A valid conclusion must be drawn on the
basis of analysis. A high degree of skill and
experience is necessary for the interpretation.