•Download as PPTX, PDF•

6 likes•493 views

This document discusses descriptive statistics and summarizing distributions. It covers measures of central tendency including the mean, median, and mode. It also discusses measures of dispersion such as variance and standard deviation. These measures are used to describe the characteristics of frequency distributions and determine where the center is located and how spread out the data is. The choice between measures depends on whether the distribution is normal or skewed.

Report

Share

Report

Share

Measure of Central Tendency (Mean, Median, Mode and Quantiles)

A measure of central tendency is a summary statistic that represents the center point or typical value of a dataset. These measures indicate where most values in a distribution fall and are also referred to as the central location of a distribution. You can think of it as the tendency of data to cluster around a middle value. In statistics, the three most common measures of central tendency are the mean, median, and mode. Each of these measures calculates the location of the central point using a different method.

Measures of dispersion

The document discusses various measures used to describe the dispersion or variability in a data set. It defines dispersion as the extent to which values in a distribution differ from the average. Several measures of dispersion are described, including range, interquartile range, mean deviation, and standard deviation. The document also discusses measures of relative standing like percentiles and quartiles, and how they can locate the position of observations within a data set. The learning objectives are to understand how to describe variability, compare distributions, describe relative standing, and understand the shape of distributions using these measures.

Basic Descriptive statistics

Descriptive statistics is used to describe and summarize key characteristics of a data set. Commonly used measures include central tendency, such as the mean, median, and mode, and measures of dispersion like range, interquartile range, standard deviation, and variance. The mean is the average value calculated by summing all values and dividing by the number of values. The median is the middle value when data is arranged in order. The mode is the most frequently occurring value. Measures of dispersion describe how spread out the data is, such as the difference between highest and lowest values (range) or how close values are to the average (standard deviation).

Measure of Dispersion in statistics

Measure of dispersion has two types Absolute measure and Graphical measure. There are other different types in there.
In this slide the discussed points are:
1. Dispersion & it's types
2. Definition
3. Use
4. Merits
5. Demerits
6. Formula & math
7. Graph and pictures
8. Real life application.

Standard deviation

The document discusses the conceptual definition of standard deviation. Standard deviation represents the root average of the squared deviations of scores from the mean. It explains that to calculate standard deviation, each score's deviation from the mean is squared, those squared deviations are averaged, and then the square root of the average is taken to determine the standard deviation in the original units of measurement.

Math 102- Statistics

The document provides an introduction to statistics and statistical inference. It discusses key definitions such as variables, parameters, populations, samples, and descriptive and inferential statistics. It also covers common measures of central tendency (mean, median, mode), measures of variability, and levels of measurement (nominal, ordinal, interval, ratio). Examples of descriptive and inferential statistics are given.

Descriptive statistics

What are descriptive Statistics, Types of statistics and its implications.
graphs, tables, variation, mean mode median, central tendency,

Lec. biostatistics introduction

The document discusses key concepts in public health methodologies and biostatistics. It defines data as facts that can be processed by computers. Statistics is described as the study of collecting, summarizing, analyzing and interpreting data. Biostatistics applies statistical techniques to health-related fields like medicine. Descriptive statistics refers to methods used to describe data, while inferential statistics are used to draw conclusions from numeric data. Variables, grouped vs. ungrouped data, and types of variables are also outlined.

Standard deviation

Standard deviation measures how dispersed data values are from the average. It is the most reliable measure of dispersion and shows the average distance of each data point from the mean. While it is more difficult to calculate than other measures, standard deviation provides important information about how concentrated or spread out the data is. The presentation defines standard deviation, lists its merits and demerits, and shows how to calculate it for both populations and samples.

Statistics Class 10 CBSE

Powerpoint presentation on the chapter- Statistics from class 10. Includes examples and formulas directly from the textbook

Variability

This document discusses measures of variability used to describe how spread out data values are from the mean or average. It defines and provides formulas for calculating range, variance, standard deviation, sample variance, sample standard deviation, population variance, population standard deviation, estimated population variance, and estimated population standard deviation. These measures are important in statistical analysis to understand the distribution of data values.

Graphical presentation of data

Variables describe attributes that can vary between entities. They can be qualitative (categorical) or quantitative (numeric). Common types of variables include continuous, discrete, ordinal, and nominal variables. Data can be presented graphically through bar charts, pie charts, histograms, box plots, and scatter plots to better understand patterns and trends. Key measures used to summarize data include measures of central tendency (mean, median, mode) and measures of variability (range, standard deviation, interquartile range).

Standard deviation

The document provides objectives and instructions for calculating standard deviation, variance, and student's t-test. It defines standard deviation as the positive square root of the arithmetic mean of the squared deviations from the mean. Standard deviation is considered the most reliable measure of variability. Variance is defined as the square of the standard deviation. Student's t-test is used to compare means of two samples and determine if they are statistically different. The document provides examples of calculating standard deviation, variance, and performing matched pairs and independent samples t-tests on sets of data.

Measures of dispersions

1. The document discusses various measures of dispersion used to quantify how spread out or variable a data set is. It describes measures such as range, mean deviation, variance, and standard deviation.
2. It also discusses relative measures of dispersion like the coefficient of variation, which allows comparison of variability between data sets with different units or averages. The coefficient of variation expresses variability as a percentage of the mean.
3. Additional concepts covered include skewness, which refers to the asymmetry of a distribution, and kurtosis, which measures the peakedness of a distribution compared to a normal distribution. Positive or negative skewness and leptokurtic, mesokurtic, or platykurtic k

1.2 types of data

The document discusses different types of data that can be collected in statistics including categorical vs. quantitative data, discrete vs. continuous data, and different levels of measurement for data including nominal, ordinal, interval, and ratio scales. It also discusses key concepts such as parameters, statistics, populations, and samples. Potential pitfalls in statistical analysis are outlined such as misleading conclusions, nonresponse bias, and issues with survey question wording and order.

Type of data

This document introduces the concept of data classification and levels of measurement in statistics. It explains that data can be either qualitative or quantitative. Qualitative data consists of attributes and labels while quantitative data involves numerical measurements. The document also outlines the four levels of measurement - nominal, ordinal, interval, and ratio - from lowest to highest. Each level allows for different types of statistical calculations, with the ratio level permitting the most complex calculations like ratios of two values.

Standard Deviation.ppt

The document discusses variance and standard deviation. It defines variance as the average squared deviation from the mean of a data set. It provides the step-by-step process to calculate variance which includes finding the mean, deviations from the mean, squaring the deviations, summing the squares, and dividing by the number of data points. Standard deviation is defined as the square root of the variance and measures how spread out numbers are from the mean. Examples are provided to demonstrate calculating variance and standard deviation.

Statistical Methods

1. Statistics is used to analyze data beyond what can be seen in maps and diagrams by using mathematical manipulation, which can reveal patterns that may otherwise go unnoticed.
2. It is important to justify any statistical techniques used and to only use techniques that are appropriate for the type of data.
3. Common methods for summarizing large data sets include calculating the mean, mode, and median. The mean is the average, the mode is the most frequent value, and the median is the middle value when the data is arranged from lowest to highest.

Measures of dispersion

This document defines and compares several common measures of statistical dispersion, or variation within a data set from the average value. It explains that measures of dispersion include range, interquartile range, variance, standard deviation, and others. Each measure is defined and their advantages and disadvantages for describing how spread out numbers are in a data set are discussed. For example, the range is simple to calculate but influenced by outliers, while the standard deviation takes all values into account but can also be impacted by outliers.

Coefficient of variation

The document defines and provides examples for calculating the coefficient of variation, which is a measure used to compare the dispersion of data sets. It gives the formula for coefficient of variation as the standard deviation divided by the mean, expressed as a percentage. Two examples are shown comparing the stability of prices between two cities and production between two manufacturing plants, with the data set having the lower coefficient of variation considered more consistent or stable.

Measure of Central Tendency (Mean, Median, Mode and Quantiles)

Measure of Central Tendency (Mean, Median, Mode and Quantiles)

Measures of dispersion

Measures of dispersion

Basic Descriptive statistics

Basic Descriptive statistics

Measure of Dispersion in statistics

Measure of Dispersion in statistics

Standard deviation

Standard deviation

Math 102- Statistics

Math 102- Statistics

Descriptive statistics

Descriptive statistics

Lec. biostatistics introduction

Lec. biostatistics introduction

Standard deviation

Standard deviation

Statistics Class 10 CBSE

Statistics Class 10 CBSE

Variability

Variability

Graphical presentation of data

Graphical presentation of data

Standard deviation

Standard deviation

Measures of dispersions

Measures of dispersions

1.2 types of data

1.2 types of data

Type of data

Type of data

Standard Deviation.ppt

Standard Deviation.ppt

Statistical Methods

Statistical Methods

Measures of dispersion

Measures of dispersion

Coefficient of variation

Coefficient of variation

Entrepreneurship Development

Entrepreneurship Development

Measure of Central Tendency

The document discusses different measures of central tendency including the mean, median, and mode. The mean is the average value calculated by adding all values and dividing by the total number of values. The median is the middle value when values are arranged from lowest to highest. The mode is the most frequently occurring value in the data set. The document provides examples of calculating each measure and discusses their advantages and disadvantages.

Cardiologia endocardiosis valvular seguimiento

Este documento resume las guías del American College of Veterinary Internal Medicine para el diagnóstico y tratamiento de la enfermedad valvular degenerativa canina. Propone una clasificación en 4 fases (A, B1, B2, C, D) y recomienda pruebas diagnósticas y dietéticas para cada fase. Para las fases iniciales se recomiendan exámenes anuales y controles. Para las fases avanzadas se aconsejan ecocardiografías, análisis de sangre y dietas ricas en calorías y proteín

Cardiologia fisiologia cardiovascular -

El documento describe la fisiología del corazón. El ciclo cardiaco consta de tres etapas: la sístole auricular impulsa la sangre a los ventrículos, la sístole ventricular expulsa la sangre al sistema circulatorio, y la diástole permite la llegada de nueva sangre. El ritmo cardíaco es controlado por el nodo sinusal que coordina la despolarización de las aurículas y los ventrículos a través del nodo AV y el fascículo de His.

RS dc-dc converter 2004

This document summarizes a research paper about a hybrid control algorithm for voltage regulation in DC-DC boost converters. The algorithm uses a hybrid automation representation to model the system's continuous and discrete dynamics. Guard conditions are derived to govern transitions between discrete states for both continuous conduction mode (CCM) and discontinuous conduction mode (DCM) operations. Simulation results show the algorithm effectively regulates output voltage under various load and disturbance conditions while smoothly transitioning between CCM and DCM. Experimental verification with a prototype converter circuit confirms the algorithm's effectiveness.

Programme integral d'entraînement personnel - legacy

Programme d'entraînement intégral et complet. Développement personnel. En bleu jours pairs en rouge jours impairs.

Cardiologia patologias cardiacas-congenitas_exploracion_inicial

Este documento describe las patologías cardiacas congénitas en perros y gatos, incluyendo su detección e investigación inicial. Explica que los defectos cardiacos congénitos pueden estar presentes al nacer o desarrollarse más adelante. Detalla los signos clínicos que pueden indicar una patología cardiaca y los pasos para evaluar a un paciente sospechoso, incluyendo auscultación, pruebas de laboratorio e historia clínica. Además, proporciona información sobre las razas que tienen mayor predisposición a ci

Cardiologia urgencias respiratorias y cardiacas

Este documento describe las urgencias respiratorias y cardiacas en animales. Se detalla que ante una dificultad respiratoria severa, la primera regla es reducir el estrés del paciente y estabilizar su condición antes de realizar pruebas diagnósticas. Luego se describen 8 grupos posibles de causas de dificultad respiratoria y su tratamiento, incluyendo asegurar la vía aérea, oxigenoterapia, establecer una vía venosa e intubar y ventilar si es necesario. Finalmente, se profundiza en el diagn

Nr 222 health promotion project—rua latest 2016 november

This document provides information and requirements for a health promotion project assignment for an NR 222 Health and Wellness course. The assignment aims to apply concepts of health promotion and cultural competency. Students must identify a health issue for a specific cultural population, research the topic using scholarly sources, and develop an educational health promotion project to address the issue. The project proposal must be approved by the instructor. Students will then write a 3-4 page paper following APA style summarizing research on the topic and describing their proposed educational approach. The assignment is worth 100 points and is due in Unit 5.

Solitons and boundaries

The document discusses classical and quantum solitons, their scattering properties, and the role of quantum group symmetry.
[1] Classical solitons are localized solutions that maintain their shape after interacting. Integrable models allow exact multi-soliton solutions and preserve scattering properties. [2] At boundaries, solitons can reflect in a way determined by integrable boundary conditions. [3] Quantum solitons exhibit particle-like scattering and binding, described by factorized S-matrices and reflection amplitudes solved from Yang-Baxter and reflection equations.

Tutorial para manejar Audacity

Este documento presenta un tutorial sobre el uso del software de edición de audio gratuito Audacity, enfocado a su aplicación en el ámbito educativo. Explica que Audacity permite la grabación y edición de múltiples pistas de audio de manera gratuita y multiplataforma. Además, detalla los pasos para descargar e instalar Audacity y muestra algunas de sus herramientas básicas como recortar, pegar y unir canciones, lo que puede ser útil en nivel preescolar. El objetivo es que este tutorial sea de ay

Study of Polarization Mode Dispersion in the Optical Digital Connection to Hi...

Polarization Mode Dispersion (PMD) is a factor which limits the bit rate of the optical transmissions. The PMD is such an effect which is time broadening due to the dependence of the group velocity to the signal polarization. The deformation effects of the impulses become considerable from 40 Gb/s. This paper, we reviews the degrade PMD effect in the telecommunications optical connections to high bit rate, due to the evolution of quality factor (Q) according to the fiber length, bit rate and PMD coefficient , well as the impact PMD on the degree of polarization and electrical power, we discuss also the representation of the polarization state and PMD vector on the Poincare sphere.

Raman spectroscopy of carbon-nanotubes

This document presents information about Raman scattering in carbon nanotubes. It discusses the structure of graphene and different types of carbon nanotubes. It then explains the Raman scattering process and different types of Raman scattering like first order, second order, resonance Raman scattering, and surface enhanced Raman scattering. Specific examples of Raman spectra of multi-walled carbon nanotubes and single layer graphene are shown. Finally, the document references phonon dispersion in graphene and carbon nanotubes and provides links for further reading.

La termodinámica y sus principales leyes

La Termodinámica es la rama de la Física que estudia a nivel macroscópico las transformaciones de la energía, y cómo esta energía puede convertirse en trabajo (movimiento).
Históricamente, la Termodinámica nació en el siglo XIX de la necesidad de mejorar el rendimiento de las primeras máquinas térmicas fabricadas por el hombre durante la Revolución Industrial.

İç Kontrol Sistemi

2005 yılında 5018 Sayılı Kamu Mali Yönetim ve Kontrol Kanununun 55 inci maddesine eklenerek tüm kamu kurumlarında zorunlu hale gelmiş iç kontrol uygulamalarına ilişkin; genel bilgi, standartlar ve 6 Adımda iç kontrol çatısı kurulmasına ilişkin bilgiler içermektedir.

17 SONET/SDH

The document discusses SONET (Synchronous Optical Networking) and SDH (Synchronous Digital Hierarchy) architectures and standards. It describes:
- SONET was developed by ANSI and SDH was developed by ITU-T.
- SONET defines four layers of operation: path, line, section, and photonic layer. These correspond to the physical and data link layers.
- A SONET STS-n signal is transmitted at 8000 frames per second, with each frame 125 microseconds long and composed of bytes that can carry digitized voice channels.

Sonet

Synchronous Optical Networking (SONET) and Synchronous Digital Hierarchy (SDH) are standardized protocols that transfer multiple digital bit streams synchronously over optical fiber using lasers or LEDs. SONET was developed to replace earlier asynchronous systems for transporting large amounts of telephone calls and data traffic over fiber without synchronization problems. SONET defines four layers - path, line, section, and photonic - to move signals across the network. It also defines a hierarchy of electrical signaling levels called STSs and corresponding optical signals called OCs. SONET networks can be configured in point-to-point, multipoint, ring or mesh topologies and provide advantages like reduced complexity, protection, bandwidth efficiency

Soliton

This document discusses solitons in optical fiber communication. It begins with an introduction to solitons as pulses that maintain their shape despite dispersion and nonlinearities. The history of discovering solitons in fiber optics is described, including key experiments in the 1980s and 1990s that demonstrated their use for long-distance, high-capacity data transmission. The document outlines how solitons form in fibers due to a balance between dispersion and the Kerr effect. It describes the properties and equations that characterize fundamental and higher-order soliton pulses. Parameters like dispersion length and peak power are also defined. Finally, the document discusses optimizing soliton width and spacing for high bit rates.

Introduction to Analysis of Variance

Chapter 12 Power Points for Essentials of Statistics for the Behavioral Sciences, Gravetter & Wallnau, 8th ed

Measures of Variability

This document discusses measures of variability, which refer to how spread out a set of data is. Variability is measured using the standard deviation and variance. The standard deviation measures how far data points are from the mean, while the variance is the average of the squared deviations from the mean. To calculate the standard deviation, you take the square root of the variance. This provides a measure of variability that is on the same scale as the original data. The standard deviation and variance are widely used statistical measures for quantifying the spread of a data set.

Entrepreneurship Development

Entrepreneurship Development

Measure of Central Tendency

Measure of Central Tendency

Cardiologia endocardiosis valvular seguimiento

Cardiologia endocardiosis valvular seguimiento

Cardiologia fisiologia cardiovascular -

Cardiologia fisiologia cardiovascular -

RS dc-dc converter 2004

RS dc-dc converter 2004

Programme integral d'entraînement personnel - legacy

Programme integral d'entraînement personnel - legacy

Cardiologia patologias cardiacas-congenitas_exploracion_inicial

Cardiologia patologias cardiacas-congenitas_exploracion_inicial

Cardiologia urgencias respiratorias y cardiacas

Cardiologia urgencias respiratorias y cardiacas

Nr 222 health promotion project—rua latest 2016 november

Nr 222 health promotion project—rua latest 2016 november

Solitons and boundaries

Solitons and boundaries

Tutorial para manejar Audacity

Tutorial para manejar Audacity

Study of Polarization Mode Dispersion in the Optical Digital Connection to Hi...

Study of Polarization Mode Dispersion in the Optical Digital Connection to Hi...

Raman spectroscopy of carbon-nanotubes

Raman spectroscopy of carbon-nanotubes

La termodinámica y sus principales leyes

La termodinámica y sus principales leyes

İç Kontrol Sistemi

İç Kontrol Sistemi

17 SONET/SDH

17 SONET/SDH

Sonet

Sonet

Soliton

Soliton

Introduction to Analysis of Variance

Introduction to Analysis of Variance

Measures of Variability

Measures of Variability

best for normal distribution.ppt

- The document discusses key concepts in descriptive statistics including types of distributions, measures of central tendency, and measures of dispersion.
- It covers normal, skewed, and other types of distributions. Measures of central tendency discussed are mean, median, and mode. Measures of dispersion covered are variance and standard deviation.
- The document uses examples and explanations to illustrate how to calculate and interpret these important statistical measures.

statical-data-1 to know how to measure.ppt

- The document discusses key concepts in descriptive statistics including types of distributions, measures of central tendency, and measures of dispersion.
- It covers normal, skewed, and other types of distributions. Measures of central tendency discussed are mean, median, and mode. Measures of dispersion covered are variance and standard deviation.
- The document uses examples and explanations to illustrate how to calculate and interpret these important statistical measures.

Sriram seminar on introduction to statistics

The document provides an introduction to statistics concepts including central tendency, dispersion, probability, and random variables. It discusses different measures of central tendency like mean, median and mode. It also covers dispersion concepts like variance and standard deviation. The document introduces key probability concepts such as experiments, sample spaces, events, and conditional probability. It defines random variables and discusses discrete and continuous random variables.

Describing quantitative data with numbers

1. Quantitative data can be summarized using measures of center (mean, median), spread (range, IQR, standard deviation), and position (quartiles, percentiles, z-scores).
2. The mean is more affected by outliers than the median. The median is more resistant to outliers and a better measure of center for skewed data.
3. Additional summaries like the five-number summary and boxplots provide a graphical view of the distribution and identify potential outliers.

Measures of Dispersion.pptx

The document discusses measures of dispersion, which describe how varied or spread out a data set is around the average value. It defines several measures of dispersion, including range, interquartile range, mean deviation, and standard deviation. The standard deviation is described as the most important measure, as it takes into account all values in the data set and is not overly influenced by outliers. The document provides a detailed example of calculating the standard deviation, which involves finding the differences from the mean, squaring those values, summing them, and taking the square root.

21.StatsLecture.07.ppt

Descriptive statistics are used to organize, simplify and describe data distributions. They involve determining the shape, central tendency (e.g. mean, median, mode), and variability or spread of data. Common measures of central tendency indicate the center of the distribution, while measures of variability like standard deviation quantify how far values are from the mean. Descriptive statistics provide essential information about data and are the first step in statistical analysis before making inferences about populations.

statistics

This document provides an introduction to inferential statistics and statistical significance. It discusses key concepts like standard error of the mean, confidence intervals, and comparing means from two samples using a t-test. The document explains how inferential statistics allow researchers to make inferences about populations based on samples and determine if observed differences are likely due to chance or a real effect.

CABT Math 8 measures of central tendency and dispersion

This document provides an introduction to statistics. It discusses what statistics is, the two main branches of statistics (descriptive and inferential), and the different types of data. It then describes several key measures used in statistics, including measures of central tendency (mean, median, mode) and measures of dispersion (range, mean deviation, standard deviation). The mean is the average value, the median is the middle value, and the mode is the most frequent value. The range is the difference between highest and lowest values, the mean deviation is the average distance from the mean, and the standard deviation measures how spread out values are from the mean. Examples are provided to demonstrate how to calculate each measure.

QT1 - 03 - Measures of Central Tendency

This document discusses measures of central tendency and dispersion used to analyze and summarize data. It defines key terms like mean, median, mode, range, variance, and standard deviation. It explains how to calculate these measures both mathematically and using grouped or sample data, and the importance of understanding the central tendency and dispersion of data distributions.

QT1 - 03 - Measures of Central Tendency

This document discusses measures of central tendency and dispersion used to analyze and summarize data. It defines key terms like mean, median, mode, range, variance, and standard deviation. It explains how to calculate these measures both mathematically and using grouped or sample data, and the importance of understanding the distribution, central tendency and dispersion of data.

Bio statistics

1. The document discusses key concepts in biostatistics including measures of central tendency, dispersion, correlation, regression, and sampling.
2. Measures of central tendency described are the mean, median, and mode. Measures of dispersion include range, standard deviation, and quartile deviation.
3. The importance of statistical analysis for living organisms in areas like medicine, biology and public health is highlighted. Examples are provided to demonstrate calculation of statistical measures.

Answer the questions in one paragraph 4-5 sentences. · Why did t.docx

Answer the questions in one paragraph 4-5 sentences.
· Why did the class collectively sign a blank check? Was this a wise decision; why or why not? we took a decision all the class without hesitation
· What is something that I said individuals should always do; what is it; why wasn't it done this time? Which mitigation strategies were used; what other strategies could have been used/considered? individuals should always participate in one group and take one decision
SAMPLING MEAN:
DEFINITION:
The term sampling mean is a statistical term used to describe the properties of statistical distributions. In statistical terms, the sample meanfrom a group of observations is an estimate of the population mean. Given a sample of size n, consider n independent random variables X1, X2... Xn, each corresponding to one randomly selected observation. Each of these variables has the distribution of the population, with mean and standard deviation. The sample mean is defined to be
WHAT IT IS USED FOR:
It is also used to measure central tendency of the numbers in a database. It can also be said that it is nothing more than a balance point between the number and the low numbers.
HOW TO CALCULATE IT:
To calculate this, just add up all the numbers, then divide by how many numbers there are.
Example: what is the mean of 2, 7, and 9?
Add the numbers: 2 + 7 + 9 = 18
Divide by how many numbers (i.e., we added 3 numbers): 18 ÷ 3 = 6
So the Mean is 6
SAMPLE VARIANCE:
DEFINITION:
The sample variance, s2, is used to calculate how varied a sample is. A sample is a select number of items taken from a population. For example, if you are measuring American people’s weights, it wouldn’t be feasible (from either a time or a monetary standpoint) for you to measure the weights of every person in the population. The solution is to take a sample of the population, say 1000 people, and use that sample size to estimate the actual weights of the whole population.
WHAT IT IS USED FOR:
The sample variance helps you to figure out the spread out in the data you have collected or are going to analyze. In statistical terminology, it can be defined as the average of the squared differences from the mean.
HOW TO CALCULATE IT:
Given below are steps of how a sample variance is calculated:
· Determine the mean
· Then for each number: subtract the Mean and square the result
· Then work out the mean of those squared differences.
To work out the mean, add up all the values then divide by the number of data points.
First add up all the values from the previous step.
But how do we say "add them all up" in mathematics? We use the Roman letter Sigma: Σ
The handy Sigma Notation says to sum up as many terms as we want.
· Next we need to divide by the number of data points, which is simply done by multiplying by "1/N":
Statistically it can be stated by the following:
·
· This value is the variance
EXAMPLE:
Sam has 20 Rose Bushes.
The number of flowers on each b.

polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh

This document discusses various measures of central tendency and variability used in statistics. It describes the three main measures of central tendency as the mode, median, and mean. For measures of variability, it defines concepts like range, variance, and standard deviation. The range is described as the highest score minus the lowest score and provides a simple measure of variation. Variance is defined as the mean of the squared deviations from the mean and standard deviation is the square root of the variance, providing a measure of how data points cluster around the mean. Examples are provided to demonstrate calculating each of these statistical measures.

Measures of Central Tendency

Measures of Central Tendency: Mean, Median and Mode
Reference: Statistics in Psychology and Education/ by Henry E. Garrett

Measures of dispersion

This document discusses measures of dispersion, which indicate how spread out or variable a set of data is. There are three main measures: the range, which is the difference between the highest and lowest values; the semi-interquartile range (SIR), which is the difference between the first and third quartiles divided by two; and variance/standard deviation. Variance is the average of the squared deviations from the mean, while standard deviation is the square root of the variance. These measures provide summaries of how concentrated or dispersed the observed values are from the average or expected value.

Descriptive Statistics.pptx

This document defines and explains various measures of central tendency, dispersion, and distribution used in descriptive statistics. It discusses modes, medians, means, percentiles, quartiles, range, interquartile range, standard deviation, z-scores, and other key statistical concepts. These metrics are used to summarize and describe the central position and variability of data in distributions.

Measures of Dispersion .pptx

This document discusses various measures of dispersion used to describe the spread or variability in a data set. It describes absolute measures of dispersion, such as range and mean deviation, which indicate the amount of variation, and relative measures like the coefficient of variation, which indicate the degree of variation accounting for different scales. Common measures discussed include range, variance, standard deviation, coefficient of variation, skewness and kurtosis. Formulas are provided for calculating many of these dispersion statistics.

Lecture. Introduction to Statistics (Measures of Dispersion).pptx

1) The document discusses various measures of dispersion used to quantify how spread out or varied a set of data values are from the average.
2) There are two types of dispersion - absolute dispersion measures how varied data values are in the original units, while relative dispersion compares variability between datasets with different units.
3) Common measures of absolute dispersion include range, variance, and standard deviation. Range is the difference between highest and lowest values, while variance and standard deviation take into account how far all values are from the mean.

SAMPLING MEANDEFINITIONThe term sampling mean is a stati.docx

The document defines key statistical terms and concepts including:
- Sampling mean is an estimate of the population mean based on a sample. It is calculated by adding all values and dividing by the sample size.
- Sample variance measures the variation or spread of values in a sample. It is calculated by finding the mean of squared differences from the sample mean.
- Standard deviation is the square root of the variance, providing a measure of dispersion from the mean.
- Hypothesis testing uses sample data to determine the validity of claims about a population. The null hypothesis is tested against an alternative using statistical significance.
- Decision trees visually represent decision problems by showing possible choices, outcomes, and probabilities to

SAMPLING MEANDEFINITIONThe term sampling mean is a stati.docx

SAMPLING MEAN:
DEFINITION:
The term sampling mean is a statistical term used to describe the properties of statistical distributions. In statistical terms, the sample meanfrom a group of observations is an estimate of the population mean. Given a sample of size n, consider n independent random variables X1, X2... Xn, each corresponding to one randomly selected observation. Each of these variables has the distribution of the population, with mean and standard deviation. The sample mean is defined to be
WHAT IT IS USED FOR:
It is also used to measure central tendency of the numbers in a database. It can also be said that it is nothing more than a balance point between the number and the low numbers.
HOW TO CALCULATE IT:
To calculate this, just add up all the numbers, then divide by how many numbers there are.
Example: what is the mean of 2, 7, and 9?
Add the numbers: 2 + 7 + 9 = 18
Divide by how many numbers (i.e., we added 3 numbers): 18 ÷ 3 = 6
So the Mean is 6
SAMPLE VARIANCE:
DEFINITION:
The sample variance, s2, is used to calculate how varied a sample is. A sample is a select number of items taken from a population. For example, if you are measuring American people’s weights, it wouldn’t be feasible (from either a time or a monetary standpoint) for you to measure the weights of every person in the population. The solution is to take a sample of the population, say 1000 people, and use that sample size to estimate the actual weights of the whole population.
WHAT IT IS USED FOR:
The sample variance helps you to figure out the spread out in the data you have collected or are going to analyze. In statistical terminology, it can be defined as the average of the squared differences from the mean.
HOW TO CALCULATE IT:
Given below are steps of how a sample variance is calculated:
· Determine the mean
· Then for each number: subtract the Mean and square the result
· Then work out the mean of those squared differences.
To work out the mean, add up all the values then divide by the number of data points.
First add up all the values from the previous step.
But how do we say "add them all up" in mathematics? We use the Roman letter Sigma: Σ
The handy Sigma Notation says to sum up as many terms as we want.
· Next we need to divide by the number of data points, which is simply done by multiplying by "1/N":
Statistically it can be stated by the following:
·
· This value is the variance
EXAMPLE:
Sam has 20 Rose Bushes.
The number of flowers on each bush is
9, 2, 5, 4, 12, 7, 8, 11, 9, 3, 7, 4, 12, 5, 4, 10, 9, 6, 9, 4
Work out the sample variance
Step 1. Work out the mean
In the formula above, μ (the Greek letter "mu") is the mean of all our values.
For this example, the data points are: 9, 2, 5, 4, 12, 7, 8, 11, 9, 3, 7, 4, 12, 5, 4, 10, 9, 6, 9, 4
The mean is:
(9+2+5+4+12+7+8+11+9+3+7+4+12+5+4+10+9+6+9+4) / 20 = 140/20 = 7
So:
μ = 7
Step 2. Then for each number: subtract the Mean and square the result
This is t.

best for normal distribution.ppt

best for normal distribution.ppt

statical-data-1 to know how to measure.ppt

statical-data-1 to know how to measure.ppt

Sriram seminar on introduction to statistics

Sriram seminar on introduction to statistics

Describing quantitative data with numbers

Describing quantitative data with numbers

Measures of Dispersion.pptx

Measures of Dispersion.pptx

21.StatsLecture.07.ppt

21.StatsLecture.07.ppt

statistics

statistics

CABT Math 8 measures of central tendency and dispersion

CABT Math 8 measures of central tendency and dispersion

QT1 - 03 - Measures of Central Tendency

QT1 - 03 - Measures of Central Tendency

QT1 - 03 - Measures of Central Tendency

QT1 - 03 - Measures of Central Tendency

Bio statistics

Bio statistics

Answer the questions in one paragraph 4-5 sentences. · Why did t.docx

Answer the questions in one paragraph 4-5 sentences. · Why did t.docx

polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh

polar pojhjgfnbhggnbh hnhghgnhbhnhbjnhhhhhh

Measures of Central Tendency

Measures of Central Tendency

Measures of dispersion

Measures of dispersion

Descriptive Statistics.pptx

Descriptive Statistics.pptx

Measures of Dispersion .pptx

Measures of Dispersion .pptx

Lecture. Introduction to Statistics (Measures of Dispersion).pptx

Lecture. Introduction to Statistics (Measures of Dispersion).pptx

SAMPLING MEANDEFINITIONThe term sampling mean is a stati.docx

SAMPLING MEANDEFINITIONThe term sampling mean is a stati.docx

SAMPLING MEANDEFINITIONThe term sampling mean is a stati.docx

SAMPLING MEANDEFINITIONThe term sampling mean is a stati.docx

Accounting concepts & conventions

This document discusses key accounting concepts and conventions. The main concepts covered are: business entity, going concern, money measurement, accounting period, cost, dual aspect, and realization. Key conventions include materiality, full disclosure, conservatism, and consistency. Accounting concepts provide the theoretical foundation for how transactions are recorded and presented, while conventions establish common practices to ensure financial statements can be understood and compared over time.

Change management

Change management is an approach to transitioning individuals, teams, and organizations from their current state to a desired future state. It involves managing the people-side of change using processes, tools, and techniques to achieve business goals. The typical change management process contains three phases - preparing for change, managing change through implementation, and reinforcing change to ensure it takes hold. This case study will examine how Toyota used change management for the first launch of one of their new vehicle models.

Watson analysis on social media

The document compares Audi, Jaguar, and Mercedes based on social media reviews. It recommends getting the best of the three brands, Audi, and leaving the rest. A group labeled 3 is analyzing social media reviews related to Jaguar.

HR in Textile Industry

Raymond is an Indian textile company established in 1925 that produces suiting fabrics and owns several apparel brands. It has a production capacity of 31 million meters annually. Gautam Singhania is the chairman. Raymond operates over 700 retail stores across India and overseas selling its brands like Raymond, Raymond Premium Apparel, and Park Avenue. The company was the first to introduce polywool blends in India and has received several awards for its products and talent management practices.

Shares and debenture

This document provides an introduction to shares, share capital, debentures, and the differences between them. It discusses key terms like IPO, FPO, equity shares, preference shares, debentures, and issuing shares. The main types of each are outlined, along with their advantages and disadvantages. Shares represent ownership in a company and allow shareholders to share in profits as dividends, while debentures are like loans that pay interest but do not provide ownership. This introduction covers the basic concepts for investors regarding the capital structure of companies.

Latest trends in production and operational management

The document discusses recent trends in production and operational management, including global competition, supply chain management, business process reengineering, total quality management, lean manufacturing, worker involvement, and cycle time reduction. Companies go global to reduce costs, improve supply chains, access international markets, and respond to demand changes. Supply chain management oversees materials, information, and finance as they move from supplier to manufacturer. Business process reengineering and total quality management aim to improve processes, products, services, and company culture. Lean manufacturing works to eliminate waste from production. Worker involvement and cycle time reduction can help companies gain competitive advantages.

Accounting concepts & conventions

Accounting concepts & conventions

Change management

Change management

Watson analysis on social media

Watson analysis on social media

HR in Textile Industry

HR in Textile Industry

Shares and debenture

Shares and debenture

Latest trends in production and operational management

Latest trends in production and operational management

Sustainable-Development-Goals-presentation-by-Office-of-National-Statistics.ppt

sustainable development goals for 10 tn class students

How to Mitigate Transition and Physical Risks in the Financial Sector

How to Mitigate Transition and Physical Risks in the Financial Sector

Girls Call Marine lines 9910780858 Provide Best And Top Girl Service And No1 ...

Girls Call Marine lines 9910780858 Provide Best And Top Girl Service And No1 in City

Girls Call DN Nagar 9910780858 Provide Best And Top Girl Service And No1 in City

Girls Call DN Nagar 9910780858 Provide Best And Top Girl Service And No1 in City

05 BBA 20 23 Sem IV POM Forecasting Methods.pptx

pom forecasting

Hamster kombat withdrawal date - what you need to know!

Hamster Kombat Coin Listing Date
The official roadmap of Hamster Kombat indicates that access to the exchanges is planned for July 2024. This aligns with the game’s rapid growth and the development team’s strategy to expand its reach within the crypto ecosystem.
How to Prepare for the Listing
Stay Informed: Keep an eye on official announcements from Hamster Kombat and TON for the latest updates.
Check Eligibility: Players should check their eligibility for the HMSTR supplying pool to participate in the token distribution.
Link Wallets: Ensure your TON wallet is linked and ready for the upcoming listing.
"Meanwhile, if you feel Hamster Kombat 🐹 will not launch July 2024, there's an even bigger opportunity you don't want to MISS...🔥 you can literally profit right now!...💯 and the best part is that it's not a crypto airdrop, mining or anything that requires you tapping or investing your time, energy and money.
It's a straight forward process and you can do it within minutes and get your own piece of the cake...💰
It's a secret crypto giveaway "NO" one is talking about.
I got $200 worth of BNB token From this crypto giveaway update in less than 24hrs here is how you can participate and earn today.
Go over to your browser now! and search 🔍 for "dailytrend247.com", it’s a legit crypto blog that is currently doing a secret crypto giveaway, Go check it out trust me, it’s 💯 legit and very easy to Join. 🏃🏃🏃
Immediately you enter the website click the "Learn>>>" button at the top of the first page
you'll be directed to the giveaway section.
Here is a 4 step process you can follow to successfully benefit.
Step 1: put your BNB wallet address, in other to receive the BNB reward.
Step 2: share to 5 friends, you need to invite your friends to join the giveaway 🎁
Step 3: Withdraw BNB 💰, at this point for you to get the free BNB you must "verify" by completing a simple survey or a sign up it depends on your region, the purpose of doing this is to actually know if you’re a human or robot, once done successfully you will get the BNB reward instantly to your crypto wallet.
BONUS TIP
To increase your chance getting the BNB reward I advise you should also join their community.
Also note the BNB reward may take a while before it arrive 👌
Thanks for reading...🙏

SOLUTIONMANUALInternational Financial Management, 9th Edition By Cheol Eun, B...

SOLUTIONMANUALInternational Financial Management, 9th Edition By Cheol Eun, B...rightmanforbloodline

SOLUTIONMANUALInternational Financial Management, 9th Edition By Cheol Eun, Bruce G. Resnick,.
SOLUTIONMANUALInternational Financial Management, 9th Edition By Cheol Eun, Bruce G. Resnick,.
SOLUTIONMANUALInternational Financial Management, 9th Edition By Cheol Eun, Bruce G. Resnick,.Cornell University degree offer diploma Transcript

按照原版制作【微信：176555708】【康奈尔大学毕业证（Cornell毕业证）成绩单offer】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：176555708】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理康奈尔大学毕业证（Cornell毕业证【微信：176555708】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理康奈尔大学毕业证（Cornell毕业证【微信：176555708】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理康奈尔大学毕业证（Cornell毕业证【微信：176555708】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理康奈尔大学毕业证（Cornell毕业证【微信：176555708 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

how do I sell hamster kombat at exchange price!

Can I truly profit from hamster kombat 🐹
To make money in Hamster Kombat, focus on completing the daily challenges. Also, watch for unique in-game events and daily login bonuses to maximize your earnings. According to the developers, you will be able to withdraw your money in July 2024.
How to Prepare for the Listing
Stay Informed: Keep an eye on official announcements from Hamster Kombat and TON for the latest updates.
Check Eligibility: Players should check their eligibility for the HMSTR supplying pool to participate in the token distribution.
Link Wallets: Ensure your TON wallet is linked and ready for the upcoming listing.
"Meanwhile, if you feel Hamster Kombat 🐹 will not launch July 2024, there's an even bigger opportunity you don't want to MISS...🔥 you can literally profit right now!...💯 and the best part is that it's not a crypto airdrop, mining or anything that requires you tapping or investing your time, energy and money.
It's a straight forward process and you can do it within minutes and get your own piece of the cake...💰
It's a secret crypto giveaway "NO" one is talking about.
I got $200 worth of BNB token From this crypto giveaway update in less than 24hrs here is how you can participate and earn today.
Go over to your browser now! and search 🔍 for "dailytrend247.com", it’s a legit crypto blog that is currently doing a secret crypto giveaway, Go check it out trust me, it’s 💯 legit and very easy to Join. 🏃🏃🏃
Immediately you enter the website click the "Learn>>>" button at the top of the first page
you'll be directed to the giveaway section.
Here is a 4 step process you can follow to successfully benefit.
Step 1: put your BNB wallet address, in other to receive the BNB reward.
Step 2: share to 5 friends, you need to invite your friends to join the giveaway 🎁
Step 3: Withdraw BNB 💰, at this point for you to get the free BNB you must "verify" by completing a simple survey or a sign up it depends on your region, the purpose of doing this is to actually know if you’re a human or robot, once done successfully you will get the BNB reward instantly to your crypto wallet.
BONUS TIP
To increase your chance getting the BNB reward I advise you should also join their community.
Also note the BNB reward may take a while before it arrive 👌
Thanks for reading...🙏

ppt on Review of literature 1720335948098.pptx

Descriptive and detailed study ppt on review of literature.

How do I sell my Hamster kombat currency?

Hopefully I will work you through a short process to follow in other to ensure the safety of your hamster token's 🐹
Step 1: Earn money on Hamster Kombat
Step 2: Accumulate money
Step 3: Verify your account on the crypto exchange that is already connected with Hamster Kombat
Step 4: Navigate to the withdrawal section on the exchange (only after listing HMSTR here)
Step 5: Choose your withdrawal method
Step 6: Enter withdrawal details
Step 7: Confirm withdrawal request
Step 8: Wait for processing
"Meanwhile, if you don't have the patience to wait for Hamster Kombat's official launch...🐹, there's an even bigger opportunity you don't want to MISS...🔥 you can literally profit right now!...💯 and the best part is that it's not a crypto airdrop, mining or anything that requires you tapping or investing your time, energy and money.
It's a straight forward process and you can do it within minutes and get your own piece of the cake...💰
It's a secret crypto giveaway "NO" one is talking about.
I got $200 worth of BNB token From this crypto giveaway update in less than 24hrs here is how you can participate and earn today.
Go over to your browser now! and search 🔍 for "dailytrend247.com", it’s a legit crypto blog that is currently doing a secret crypto giveaway, Go check it out trust me, it’s 💯 legit and very easy to Join. 🏃🏃🏃
Immediately you enter the website click the "Learn>>>" button at the top of the first page you'll be directed to the giveaway section.
Here is a 4 step process you can follow to successfully benefit.
Step 1: put your BNB wallet address, in other to receive the BNB reward.
Step 2: share to 5 friends, you need to invite your friends to join the giveaway 🎁
Step 3: Withdraw BNB 💰, at this point for you to get the free BNB you must "verify" by completing a simple survey or a sign up it depends on your region, the purpose of doing this is to actually know if you’re a human or robot, once done successfully you will get the BNB reward instantly to your crypto wallet.
BONUS TIP
To increase your chance getting the BNB reward I advise you should also join their community.
Also note the BNB reward may take a while before it arrive 👌
Thanks for reading...🙏

Economic Risk Factor Update: July 2024 [SlideShare]

Service sector confidence fell in June, bringing the index into contractionary territory, said Sam Millette, director of fixed income, in his latest Economic Risk Factor Update.
For more market updates, subscribe to The Independent Market Observer at https://blog.commonwealth.com/independent-market-observer.

Introduction to trading Solana Memecoins.docx

Memecoins, born from viral phenomena and internet culture, have captured the attention of investors due to their whimsical nature and significant potential. Solana, a blockchain known for its high speed and low fees, has emerged as an ideal ecosystem for these coins. This ebook provides a comprehensive guide to trading memecoins on Solana, covering everything from basic concepts to advanced strategies, equipping readers with the necessary knowledge to navigate this dynamic and opportunity-filled market. Here, we teach the reader how to choose the "best" memecoins.

Introduction to Islamic Banking and Finance.Part2

This is part two of introduction to Islamic Banking and Finance

Northeastern University degree offer diploma Transcript

学历定制【微信号:95270640】《(NEU毕业证书)东北大学毕业证》【微信号:95270640】《毕业证、成绩单、外壳、雅思、offer、真实留信官方学历认证（永久存档/真实可查）》采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【关于学历材料质量】
我们承诺采用的是学校原版纸张（原版纸质、底色、纹路）我们工厂拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有成品以及工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信号95270640】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信号95270640】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
留信网服务项目：
1、留学生专业人才库服务（留信分析）
2、国（境）学习人员提供就业推荐信服务
3、留学人员区块链存储服务
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

Most Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...

Most Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And No1 in City

Solution Manual For Fundamentals of Financial Accounting, 8th Edition 2024 by...

Solution Manual For Fundamentals of Financial Accounting, 8th Edition 2024 by...rightmanforbloodline

Solution Manual For Fundamentals of Financial Accounting, 8th Edition 2024 by Fred Phillips, Robert Libby, Verified Chapters 1 - 13, Complete.
Solution Manual For Fundamentals of Financial Accounting, 8th Edition 2024 by Fred Phillips, Robert Libby, Verified Chapters 1 - 13, Complete.
Solution Manual For Fundamentals of Financial Accounting, 8th Edition 2024 by Fred Phillips, Robert Libby, Verified Chapters 1 - 13, Complete.Chapter 1 Introduction to Management.pdf

Management and organization behavior

Bangalore Girls Call Bangalore 0X0000000X Payment On Delevery Cash Hot Premiu...

Bangalore Girls Call Bangalore 0X0000000X Payment On Delevery Cash Hot Premium Genuine High Profile Model College Girl
Contect For Ad Post:- puneetsing251@gmail.com

University of California, Irvine degree offer diploma Transcript

按照原版制作【微信：176555708】【加利福尼亚大学尔湾分校毕业证（UCI毕业证）成绩单offer】【微信：176555708】（留信学历认证永久存档查询）采用学校原版纸张（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：176555708】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：176555708】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：176555708】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理加利福尼亚大学尔湾分校毕业证（UCI毕业证【微信：176555708】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理加利福尼亚大学尔湾分校毕业证（UCI毕业证【微信：176555708】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理加利福尼亚大学尔湾分校毕业证（UCI毕业证【微信：176555708】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理加利福尼亚大学尔湾分校毕业证（UCI毕业证【微信：176555708 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。

Sustainable-Development-Goals-presentation-by-Office-of-National-Statistics.ppt

Sustainable-Development-Goals-presentation-by-Office-of-National-Statistics.ppt

How to Mitigate Transition and Physical Risks in the Financial Sector

How to Mitigate Transition and Physical Risks in the Financial Sector

Girls Call Marine lines 9910780858 Provide Best And Top Girl Service And No1 ...

Girls Call Marine lines 9910780858 Provide Best And Top Girl Service And No1 ...

Girls Call DN Nagar 9910780858 Provide Best And Top Girl Service And No1 in City

Girls Call DN Nagar 9910780858 Provide Best And Top Girl Service And No1 in City

05 BBA 20 23 Sem IV POM Forecasting Methods.pptx

05 BBA 20 23 Sem IV POM Forecasting Methods.pptx

Hamster kombat withdrawal date - what you need to know!

Hamster kombat withdrawal date - what you need to know!

SOLUTIONMANUALInternational Financial Management, 9th Edition By Cheol Eun, B...

SOLUTIONMANUALInternational Financial Management, 9th Edition By Cheol Eun, B...

Cornell University degree offer diploma Transcript

Cornell University degree offer diploma Transcript

how do I sell hamster kombat at exchange price!

how do I sell hamster kombat at exchange price!

ppt on Review of literature 1720335948098.pptx

ppt on Review of literature 1720335948098.pptx

How do I sell my Hamster kombat currency?

How do I sell my Hamster kombat currency?

Economic Risk Factor Update: July 2024 [SlideShare]

Economic Risk Factor Update: July 2024 [SlideShare]

Introduction to trading Solana Memecoins.docx

Introduction to trading Solana Memecoins.docx

Introduction to Islamic Banking and Finance.Part2

Introduction to Islamic Banking and Finance.Part2

Northeastern University degree offer diploma Transcript

Northeastern University degree offer diploma Transcript

Most Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...

Most Girls Call Navi Mumbai 9930245274 Provide Best And Top Girl Service And ...

Solution Manual For Fundamentals of Financial Accounting, 8th Edition 2024 by...

Solution Manual For Fundamentals of Financial Accounting, 8th Edition 2024 by...

Chapter 1 Introduction to Management.pdf

Chapter 1 Introduction to Management.pdf

Bangalore Girls Call Bangalore 0X0000000X Payment On Delevery Cash Hot Premiu...

Bangalore Girls Call Bangalore 0X0000000X Payment On Delevery Cash Hot Premiu...

University of California, Irvine degree offer diploma Transcript

University of California, Irvine degree offer diploma Transcript

- 1. Central Tendency & Dispersion Types of Distributions: Normal, Skewed Central Tendency: Mean, Median, Mode Dispersion: Variance, Standard Deviation
- 2. DESCRIPTIVE STATISTICS are concerned with describing the characteristics of frequency distributions Where is the center? What is the range? What is the shape [of the distribution]?
- 3. Frequency Table Test Scores Observation Frequency (scores) (# occurrences) 65 1 70 2 75 3 80 4 85 3 90 2 95 1 What is the range of test scores? A: 30 (95 minus 65) When calculating mean, one must divide by what number? A: 16 (total # occurrences)
- 4. Summarizing Distributions Two key characteristics of a frequency distribution are especially important when summarizing data or when making a prediction: CENTRAL TENDENCY What is in the “middle”? What is most common? What would we use to predict? DISPERSION How spread out is the distribution? What shape is it?
- 5. 3 measures of central tendency are commonly used in statistical analysis - MEAN, MEDIAN, and MODE. Each measure is designed to represent a “typical” value in the distribution. The choice of which measure to use depends on the shape of the distribution (whether normal or skewed). The MEASURES of Central Tendency
- 6. Mean - Average Most common measure of central tendency. Is sensitive to the influence of a few extreme values (outliers), thus it is not always the most appropriate measure of central tendency. Best used for making predictions when a distribution is more or less normal (or symmetrical). Symbolized as: x for the mean of a sample μ for the mean of a population
- 7. Finding the Mean Formula for Mean: X = (Σ x) N Given the data set: {3, 5, 10, 4, 3} X = (3 + 5 + 10 + 4 + 3) = 25 5 5 X = 5
- 8. Find the Mean Q: 85, 87, 89, 91, 98, 100 A: 91.67 Median: 90 Q: 5, 87, 89, 91, 98, 100 A: 78.3 (Extremely low score lowered the Mean) Median: 90 (The median remained unchanged.)
- 9. Median Used to find middle value (center) of a distribution. Used when one must determine whether the data values fall into either the upper 50% or lower 50% of a distribution. Used when one needs to report the typical value of a data set, ignoring the outliers (few extreme values in a data set). Example: median salary, median home prices in a market Is a better indicator of central tendency than mean when one has a skewed distribution.
- 10. To compute the median first you order the values of X from low to high: 85, 90, 94, 94, 95, 97, 97, 97, 97, 98 then count number of observations = 10. When the number of observations are even, average the two middle numbers to calculate the median. This example, 96 is the median (middle) score.
- 11. Median Find the Median 4 5 6 6 7 8 9 10 12 Find the Median 5 6 6 7 8 9 10 12 Find the Median 5 6 6 7 8 9 10 100,000
- 12. Mode Used when the most typical (common) value is desired. Often used with categorical data. The mode is not always unique. A distribution can have no mode, one mode, or more than one mode. When there are two modes, we say the distribution is bimodal. EXAMPLES: a) {1,0,5,9,12,8} - No mode b) {4,5,5,5,9,20,30} – mode = 5 c) {2,2,5,9,9,15} - bimodal, mode 2 and 9
- 13. Measures of Variability Central Tendency doesn’t tell us everything Dispersion/Deviation/Spread tells us a lot about how the data values are distributed. We are most interested in: Standard Deviation (σ) and Variance (σ2)
- 14. Why can’t the mean tell us everything? Mean describes the average outcome. The question becomes how good a representation of the distribution is the mean? How good is the mean as a description of central tendency -- or how accurate is the mean as a predictor? ANSWER -- it depends on the shape of the distribution. Is the distribution normal or skewed?
- 15. Dispersion Once you determine that the data of interest is normally distributed, ideally by producing a histogram of the values, the next question to ask is: How spread out are the values about the mean? Dispersion is a key concept in statistical thinking. The basic question being asked is how much do the values deviate from the Mean? The more “bunched up” around the mean the better your ability to make accurate predictions.
- 16. Means Consider these means for hours worked day each day: X = {7, 8, 6, 7, 7, 6, 8, 7} X = (7+8+6+7+7+6+8+7)/8 X = 7 Notice that all the data values are bunched near the mean. Thus, 7 would be a pretty good prediction of the average hrs. worked each day. X = {12, 2, 0, 14, 10, 9, 5, 4} X = (12+2+0+14+10+9+5+4)/8 X = 7 The mean is the same for this data set, but the data values are more spread out. So, 7 is not a good prediction of hrs. worked on average each day.
- 17. Data is more spread out, meaning it has greater variability. Below, the data is grouped closer to the center, less spread out, or smaller variability.
- 18. How well does the mean represent the values in a distribution? The logic here is to determine how much spread is in the values. How much do the values "deviate" from the mean? Think of the mean as the true value, or as your best guess. If every X were very close to the Mean, the Mean would be a very good predictor. If the distribution is very sharply peaked then the mean is a good measure of central tendency and if you were to use the Mean to make predictions you would be correct or very close much of the time.
- 19. What if scores are widely distributed? The mean is still your best measure and your best predictor, but your predictive power would be less. How do we describe this? Measures of variability Mean Absolute Deviation (You used in Math1) Variance (We use in Math 2) Standard Deviation (We use in Math 2)
- 20. Mean Absolute Deviation The key concept for describing normal distributions and making predictions from them is called deviation from the mean. We could just calculate the average distance between each observation and the mean. We must take the absolute value of the distance, otherwise they would just cancel out to zero! Formula: | |iX X n
- 21. Mean Absolute Deviation: An Example 1. Compute X (Average) 2. Compute X – X and take the Absolute Value to get Absolute Deviations 3. Sum the Absolute Deviations 4. Divide the sum of the absolute deviations by N X – Xi Abs. Dev. 7 – 6 1 7 – 10 3 7 – 5 2 7 – 4 3 7 – 9 2 7 – 8 1 Data: X = {6, 10, 5, 4, 9, 8} X = 42 / 6 = 7 Total: 12 12 / 6 = 2
- 22. What Does it Mean? On Average, each value is two units away from the mean. Is it Really that Easy? No! Absolute values are difficult to manipulate algebraically Absolute values cause enormous problems for calculus (Discontinuity) We need something else…
- 23. Variance and Standard Deviation Instead of taking the absolute value, we square the deviations from the mean. This yields a positive value. This will result in measures we call the Variance and the Standard Deviation Sample - Population - s Standard Deviation σ Standard Deviation s2 Variance σ2 Variance
- 24. Calculating the Variance and/or Standard Deviation Formulae: Variance: Examples Follow . . . 2 ( )iX X s N 2 2 ( )iX X s N Standard Deviation:
- 25. Example: -1 1 3 9 -2 4 -3 9 2 4 1 1 Data: X = {6, 10, 5, 4, 9, 8}; N = 6 Total: 42 Total: 28 Standard Deviation: 7 6 42 N X X Mean: Variance: 2 2 ( ) 28 4.67 6 X X s N 16.267.42 ss XX 2 )( XX X 6 10 5 4 9 8