Includes solved numerical problems on Median, in three series individual, discrete and continuous. Moreover, it consists some unsolved problems for practice after learning.
This document discusses various 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 data points. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently in the data set. Examples are given to demonstrate calculating each measure. The document also discusses advantages and limitations of each central tendency measure.
This document discusses various measures of central tendency including arithmetic mean, geometric mean, harmonic mean, median, and mode. It provides definitions and formulas for calculating each measure, as well as discussing their merits and demerits. The arithmetic mean is the sum of all values divided by the total number of values. The geometric mean uses products and logarithms. The harmonic mean gives more weight to smaller values. The median is the middle value when values are arranged in order. The mode is the most frequently occurring value.
This document provides information on measures of central tendency, including the median, mode, and mean. It defines these terms, explains how to calculate them, and discusses their advantages and disadvantages. Specifically, it explains that the median is the middle value when values are arranged in order, and the mode is the most frequently occurring value. Formulas are provided for calculating the median and mode from both individual and grouped data sets. The document also discusses different types of averages and provides examples of calculating the median and mode from various data distributions.
This document discusses measures of central tendency including the mean, median, and mode. It provides examples of calculating the mean from raw data sets and frequency distributions. The median and mode are defined as the middle value and most frequent value, respectively. Methods for calculating each from both types of data are shown. Other measures covered include the midrange and the effects of outliers. Shapes of distributions are discussed including positively and negatively skewed and symmetric. Practice problems are provided to reinforce the concepts.
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 definitions and formulas for calculating each measure for both grouped and ungrouped data. For the mean, it addresses how outliers can influence the value and introduces the trimmed mean. The median is described as the middle value of a data set and is not impacted by outliers. The mode is defined as the most frequent observation. Examples are given to demonstrate calculating each measure. Key differences between the measures are summarized.
This document provides an introduction to measures of central tendency in statistics. It defines measures of central tendency as statistical measures that describe the center of a data distribution. The three most commonly used measures are the mean, median, and mode. The document focuses on explaining the arithmetic mean in detail, including how to calculate the mean from individual data series, discrete data series, and continuous data series using different methods. It also discusses weighted means, combined means, and the relationship between the mean, median and mode. The objectives and advantages and disadvantages of the mean are provided.
This document discusses various 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 data points. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently in the data set. Examples are given to demonstrate calculating each measure. The document also discusses advantages and limitations of each central tendency measure.
This document discusses various measures of central tendency including arithmetic mean, geometric mean, harmonic mean, median, and mode. It provides definitions and formulas for calculating each measure, as well as discussing their merits and demerits. The arithmetic mean is the sum of all values divided by the total number of values. The geometric mean uses products and logarithms. The harmonic mean gives more weight to smaller values. The median is the middle value when values are arranged in order. The mode is the most frequently occurring value.
This document provides information on measures of central tendency, including the median, mode, and mean. It defines these terms, explains how to calculate them, and discusses their advantages and disadvantages. Specifically, it explains that the median is the middle value when values are arranged in order, and the mode is the most frequently occurring value. Formulas are provided for calculating the median and mode from both individual and grouped data sets. The document also discusses different types of averages and provides examples of calculating the median and mode from various data distributions.
This document discusses measures of central tendency including the mean, median, and mode. It provides examples of calculating the mean from raw data sets and frequency distributions. The median and mode are defined as the middle value and most frequent value, respectively. Methods for calculating each from both types of data are shown. Other measures covered include the midrange and the effects of outliers. Shapes of distributions are discussed including positively and negatively skewed and symmetric. Practice problems are provided to reinforce the concepts.
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 definitions and formulas for calculating each measure for both grouped and ungrouped data. For the mean, it addresses how outliers can influence the value and introduces the trimmed mean. The median is described as the middle value of a data set and is not impacted by outliers. The mode is defined as the most frequent observation. Examples are given to demonstrate calculating each measure. Key differences between the measures are summarized.
This document provides an introduction to measures of central tendency in statistics. It defines measures of central tendency as statistical measures that describe the center of a data distribution. The three most commonly used measures are the mean, median, and mode. The document focuses on explaining the arithmetic mean in detail, including how to calculate the mean from individual data series, discrete data series, and continuous data series using different methods. It also discusses weighted means, combined means, and the relationship between the mean, median and mode. The objectives and advantages and disadvantages of the mean are provided.
This document discusses various measures of central tendency including arithmetic mean, geometric mean, and harmonic mean. It provides formulas to calculate each measure and examples worked out step-by-step. For arithmetic mean, the sum of all values is divided by the total number of values. Geometric mean is calculated by taking the nth root of the product of all values. Harmonic mean is calculated as the reciprocal of the arithmetic mean of the reciprocals. In all examples shown, the relationship between the measures holds such that the arithmetic mean is greater than the geometric mean, which is greater than the harmonic mean.
This document discusses various measures of central tendency including arithmetic mean, median, mode, geometric mean, and harmonic mean. It provides definitions and formulas for calculating each measure, along with examples to illustrate how to calculate the median, mode, geometric mean, and harmonic mean. The document is intended as a guide for understanding and calculating different types of averages and measures of central tendency.
This document discusses measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating the arithmetic mean, geometric mean, harmonic mean, median, and mode. Examples are given for calculating each measure. The merits and demerits of each measure are outlined. In conclusion, the mean is affected by outliers while the median and mode are robust to outliers, and the mode is easiest to calculate by counting frequencies.
Measures of Central Tendency are numerical descriptive measures which indicate or locate the center of a distribution or data set.
Measures of Central Tendency
The MEAN
The MEDIAN
The MODE
The MEAN of a set of values or measurements is the sum of all the measurements divided by the number of measurements in the set.
It is sometimes called the ARITHMETIC MEAN
Population Mean Sample Mean
흁=(∑▒푿)/푵 풙 ̅=(∑▒풙)/풏
where N – total number of observations in the population
n – total number of observations in the sample
The MEDIAN is the middle value of the sample when the data are ranked in order according to size
The MODE is the value which occurs most frequently in a set of measurements or values.
The MEAN = The average
The MEDIAN = the number or average of the numbers in the middle
The MODE= the number that occurs the most.
This document defines and provides examples of measures of central tendency, including the mean, median, and mode. The mean is the average value and is calculated by summing all values and dividing by the number of values. The median indicates the middle value of an ordered data set. The mode is the most frequently occurring value. These measures can be used to describe sample data or entire populations. The appropriate measure depends on features of the data such as outliers or symmetry.
The document discusses different measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each. The mean is the average and is calculated by adding all values and dividing by the total count. The median is the middle value when data is arranged in order. The mode is the most frequently occurring value. Examples are provided to demonstrate calculating and interpreting these measures of central tendency.
Measure of Central Tendency (Mean, Median, Mode and Quantiles)Salman Khan
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 central tendency and dispersionAbhinav yadav
This document discusses various measures of central tendency and dispersion. It defines the mean, median, and mode as measures of central tendency, and describes how to calculate the arithmetic mean, geometric mean, harmonic mean, median, and mode. It also discusses measures of dispersion such as variance and standard deviation, and classifies them as either measures of absolute dispersion or relative dispersion.
The document discusses different measures of central tendency including the mean, median, and mode. It provides formulas and examples for calculating each measure. The mean is the average value and is calculated by summing all values and dividing by the total number. The median is the middle value when values are arranged in order. The mode is the value that appears most frequently in a data set.
The document discusses measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each measure. For the mean, formulas are given for both raw data and frequency data. The relationships between the mean, median, and mode are explored, including an empirical relationship that can be used to find one value if the other two are known for symmetrical data. The importance of each measure is discussed for different business applications depending on the characteristics of the data.
This document discusses measures of central tendency and dispersion. It defines mean, median and mode as measures of central tendency, which describe the central location of data. The mean is the average value, median is the middle value, and mode is the most frequent value. It also defines measures of dispersion like range, interquartile range, variance and standard deviation, which describe how spread out the data are. Standard deviation in particular measures how far data values are from the mean. Approximately 68%, 95% and 99.7% of observations in a normal distribution fall within 1, 2 and 3 standard deviations of the mean respectively.
This document discusses measures of central tendency including the mean, median, and mode. It defines each measure and provides examples of calculating them using individual, discrete, and continuous data series. The mean is the average value obtained by dividing the sum of all values by the total number of values. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently. Formulas and examples are given for calculating each measure using different types of data sets. Merits and demerits of each measure are also outlined.
This document discusses various measures of central tendency including arithmetic mean, median, mode, and quartiles. It provides definitions and formulas for calculating each measure, and describes how to calculate the mean and median for different types of data distributions including raw data, continuous series, and less than/more than/inclusive series. It also covers weighted mean, combined mean, and properties and limitations of the arithmetic mean.
Measure of central tendency provides a very convenient way of describing a set of scores with a single number that describes the PERFORMANCE of the group.
It is also defined as a single value that is used to describe the “center” of the data.
The document discusses measures of central tendency, including the mean, median, and mode. It provides an example of monthly family incomes and calculates each measure using the data. The mean is the average, the median is the middle value, and the mode is the most frequent value. Each measure has unique properties that determine when it is most appropriate to use.
This document discusses measures of central tendency, which are statistical values that describe the center of a data set. The three main measures are the mean, median, and mode.
The mean is the average value found by dividing the total of all values by the number of values. The median is the middle value when data is arranged from lowest to highest. The mode is the most frequently occurring value.
While the mean is most commonly used, the median and mode are better in some situations, such as when outliers are present or data is categorical. The geometric mean measures rate of change over time. Choosing the appropriate measure depends on the data type and distribution.
This document discusses measures of central tendency including mean, median, and mode. It provides definitions and formulas for calculating each measure from both grouped and ungrouped data. For mean, it is the sum of all values divided by the number of values. Median is the middle value when values are arranged in order. Mode is the most frequently occurring value. The document also discusses requirements for a good measure of central tendency and provides examples calculating the measures from sample medical data sets to illustrate their use and assess skewness.
Central tendency of data is defined as the tendency of data to concentrate around some central value. here all the measures of central tendency have been explained such as mean, arithmetic mean, geometric mean, harmonic mean, mode, and median with examples.
The document defines and provides examples of calculating the median for individual observations and continuous data series. It explains that the median is the middle value when the number of observations is odd, and the average of the two middle values when the number is even. Formulas and step-by-step solutions are given to demonstrate calculating the median from raw data sets and frequency distributions.
Central tendency refers to typical or average values in a data set. There are three main measures of central tendency: mean, median, and mode. The mean is the average and is calculated by summing all values and dividing by the total number. The median is the middle value when data is arranged from lowest to highest. The mode is the most frequently occurring value. These measures were calculated for two sample data sets to illustrate how to find the mean, median, and mode from grouped and ungrouped data.
This document discusses various measures of central tendency including arithmetic mean, geometric mean, and harmonic mean. It provides formulas to calculate each measure and examples worked out step-by-step. For arithmetic mean, the sum of all values is divided by the total number of values. Geometric mean is calculated by taking the nth root of the product of all values. Harmonic mean is calculated as the reciprocal of the arithmetic mean of the reciprocals. In all examples shown, the relationship between the measures holds such that the arithmetic mean is greater than the geometric mean, which is greater than the harmonic mean.
This document discusses various measures of central tendency including arithmetic mean, median, mode, geometric mean, and harmonic mean. It provides definitions and formulas for calculating each measure, along with examples to illustrate how to calculate the median, mode, geometric mean, and harmonic mean. The document is intended as a guide for understanding and calculating different types of averages and measures of central tendency.
This document discusses measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating the arithmetic mean, geometric mean, harmonic mean, median, and mode. Examples are given for calculating each measure. The merits and demerits of each measure are outlined. In conclusion, the mean is affected by outliers while the median and mode are robust to outliers, and the mode is easiest to calculate by counting frequencies.
Measures of Central Tendency are numerical descriptive measures which indicate or locate the center of a distribution or data set.
Measures of Central Tendency
The MEAN
The MEDIAN
The MODE
The MEAN of a set of values or measurements is the sum of all the measurements divided by the number of measurements in the set.
It is sometimes called the ARITHMETIC MEAN
Population Mean Sample Mean
흁=(∑▒푿)/푵 풙 ̅=(∑▒풙)/풏
where N – total number of observations in the population
n – total number of observations in the sample
The MEDIAN is the middle value of the sample when the data are ranked in order according to size
The MODE is the value which occurs most frequently in a set of measurements or values.
The MEAN = The average
The MEDIAN = the number or average of the numbers in the middle
The MODE= the number that occurs the most.
This document defines and provides examples of measures of central tendency, including the mean, median, and mode. The mean is the average value and is calculated by summing all values and dividing by the number of values. The median indicates the middle value of an ordered data set. The mode is the most frequently occurring value. These measures can be used to describe sample data or entire populations. The appropriate measure depends on features of the data such as outliers or symmetry.
The document discusses different measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each. The mean is the average and is calculated by adding all values and dividing by the total count. The median is the middle value when data is arranged in order. The mode is the most frequently occurring value. Examples are provided to demonstrate calculating and interpreting these measures of central tendency.
Measure of Central Tendency (Mean, Median, Mode and Quantiles)Salman Khan
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 central tendency and dispersionAbhinav yadav
This document discusses various measures of central tendency and dispersion. It defines the mean, median, and mode as measures of central tendency, and describes how to calculate the arithmetic mean, geometric mean, harmonic mean, median, and mode. It also discusses measures of dispersion such as variance and standard deviation, and classifies them as either measures of absolute dispersion or relative dispersion.
The document discusses different measures of central tendency including the mean, median, and mode. It provides formulas and examples for calculating each measure. The mean is the average value and is calculated by summing all values and dividing by the total number. The median is the middle value when values are arranged in order. The mode is the value that appears most frequently in a data set.
The document discusses measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each measure. For the mean, formulas are given for both raw data and frequency data. The relationships between the mean, median, and mode are explored, including an empirical relationship that can be used to find one value if the other two are known for symmetrical data. The importance of each measure is discussed for different business applications depending on the characteristics of the data.
This document discusses measures of central tendency and dispersion. It defines mean, median and mode as measures of central tendency, which describe the central location of data. The mean is the average value, median is the middle value, and mode is the most frequent value. It also defines measures of dispersion like range, interquartile range, variance and standard deviation, which describe how spread out the data are. Standard deviation in particular measures how far data values are from the mean. Approximately 68%, 95% and 99.7% of observations in a normal distribution fall within 1, 2 and 3 standard deviations of the mean respectively.
This document discusses measures of central tendency including the mean, median, and mode. It defines each measure and provides examples of calculating them using individual, discrete, and continuous data series. The mean is the average value obtained by dividing the sum of all values by the total number of values. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently. Formulas and examples are given for calculating each measure using different types of data sets. Merits and demerits of each measure are also outlined.
This document discusses various measures of central tendency including arithmetic mean, median, mode, and quartiles. It provides definitions and formulas for calculating each measure, and describes how to calculate the mean and median for different types of data distributions including raw data, continuous series, and less than/more than/inclusive series. It also covers weighted mean, combined mean, and properties and limitations of the arithmetic mean.
Measure of central tendency provides a very convenient way of describing a set of scores with a single number that describes the PERFORMANCE of the group.
It is also defined as a single value that is used to describe the “center” of the data.
The document discusses measures of central tendency, including the mean, median, and mode. It provides an example of monthly family incomes and calculates each measure using the data. The mean is the average, the median is the middle value, and the mode is the most frequent value. Each measure has unique properties that determine when it is most appropriate to use.
This document discusses measures of central tendency, which are statistical values that describe the center of a data set. The three main measures are the mean, median, and mode.
The mean is the average value found by dividing the total of all values by the number of values. The median is the middle value when data is arranged from lowest to highest. The mode is the most frequently occurring value.
While the mean is most commonly used, the median and mode are better in some situations, such as when outliers are present or data is categorical. The geometric mean measures rate of change over time. Choosing the appropriate measure depends on the data type and distribution.
This document discusses measures of central tendency including mean, median, and mode. It provides definitions and formulas for calculating each measure from both grouped and ungrouped data. For mean, it is the sum of all values divided by the number of values. Median is the middle value when values are arranged in order. Mode is the most frequently occurring value. The document also discusses requirements for a good measure of central tendency and provides examples calculating the measures from sample medical data sets to illustrate their use and assess skewness.
Central tendency of data is defined as the tendency of data to concentrate around some central value. here all the measures of central tendency have been explained such as mean, arithmetic mean, geometric mean, harmonic mean, mode, and median with examples.
The document defines and provides examples of calculating the median for individual observations and continuous data series. It explains that the median is the middle value when the number of observations is odd, and the average of the two middle values when the number is even. Formulas and step-by-step solutions are given to demonstrate calculating the median from raw data sets and frequency distributions.
Central tendency refers to typical or average values in a data set. There are three main measures of central tendency: mean, median, and mode. The mean is the average and is calculated by summing all values and dividing by the total number. The median is the middle value when data is arranged from lowest to highest. The mode is the most frequently occurring value. These measures were calculated for two sample data sets to illustrate how to find the mean, median, and mode from grouped and ungrouped data.
This document discusses various measures of central tendency including the mean, median, and mode. It provides definitions and formulas for calculating each measure. The mean is the average value and is calculated by summing all values and dividing by the total number of items. The median is the middle value when data is arranged in order. The mode is the value that occurs most frequently in a data set. Examples are provided to demonstrate calculating each measure for both grouped and ungrouped data. The advantages and disadvantages of each measure are also briefly discussed.
This document provides an outline and summary of key concepts related to data analysis, including measures of central tendency (mean, median, mode), spread of distribution (range, variance, standard deviation), and experimental designs (paired t-test, ANOVA). It explains how to calculate and interpret the mean, median, mode, range, variance, and standard deviation. It also provides brief definitions and examples of paired t-tests and ANOVA.
This document discusses measures of central tendency and different methods for calculating averages. It begins by defining central tendency as a single value that represents the characteristics of an entire data set. Three common measures of central tendency are introduced: the mean, median, and mode. The document then focuses on explaining how to calculate the arithmetic mean, or average, including the direct method, shortcut method, and how it applies to discrete and continuous data series. Weighted averages are also covered. In summary, the document provides an overview of key concepts in measures of central tendency and how to calculate various types of averages.
“No human mind is capable of
grasping in its entirety the meaning of
any considerable quantity of numerical
data. We want to be able to express all
the relevant information contained in the
mass by means of comparatively few
numerical values. This is a purely
practical need which the science of
statistics is able to some extent to
meet” (Fisher, 1950 p 7).
This mini project is created by Md Halim from Haldia Insititute of Technology, Haldia WB. Disclaimer:- if any error is not the responsibility to team Halim
Mean, Median, Mode: Measures of Central Tendency Jan Nah
There are three common measures of central tendency: mean, median, and mode. The mean is the average value found by dividing the sum of all values by the total number of values. The median is the middle value when values are arranged from lowest to highest. The mode is the value that occurs most frequently. Each measure provides a single number to represent the central or typical value in a data set.
There are three common measures of central tendency: mean, median, and mode. The mean is the average value found by dividing the sum of all values by the total number of values. The median is the middle value when values are arranged from lowest to highest. The mode is the value that occurs most frequently. Each measure provides a single number to represent the central or typical value in a data set.
The median of a dataset is the middle value when the observations are arranged in ascending order. It is the value below which 50% of the observations lie. For an odd number of observations, the median is the middle value. For an even number, the median is the average of the two middle values. The median can be calculated for both grouped and ungrouped data using different formulas depending on whether the data is grouped by value or range. Examples are provided to demonstrate calculating the median for different types of datasets.
The single numerical value that indicates the orientation
of data towards the calculated central value of distribution. This value is sometimes called as nuclear value of the data.
This document discusses calculating the arithmetic mean of a data set. It provides examples of finding the mean goals scored by a hockey team and the mean number of times students bought lunch. The mean is calculated by summing all values and dividing by the total number of values. For data with frequencies, each value is multiplied by its frequency before summing. The document also reviews calculating the mean from frequency tables and lists of raw data values.
The document discusses different measures of central tendency including the mean, median and mode. It provides definitions and formulas for calculating different types of means:
- The arithmetic mean is calculated by summing all values and dividing by the total number of values. It can be calculated using direct or short-cut methods for both individual observations and grouped data.
- Other means include the geometric mean and harmonic mean, which are called special averages.
- The median is the middle value when values are arranged in order. The mode is the value that occurs most frequently.
- Data can be in the form of individual observations, discrete series or continuous series. Formulas are provided for calculating the mean of grouped or ungrouped data
Frequency distribution, central tendency, measures of dispersionDhwani Shah
The presentation explains the theory of what is Frequency distribution, central tendency, measures of dispersion. It also has numericals on how to find CT for grouped and ungrouped data.
This document discusses measures of central tendency, which are values used to describe the center or typical value of a data set. There are three main measures: mean, median, and mode. 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 values are arranged from lowest to highest. The mode is the most frequently occurring value. The document provides formulas and examples for calculating each measure, and discusses their relative advantages and disadvantages.
This document discusses three common measures of central tendency: mean, median, and mode. It provides definitions and formulas for calculating each, along with examples. The mean is the average and is calculated by adding all values and dividing by the total number. The median is the middle value when values are arranged from lowest to highest. The mode is the value that occurs most frequently. Each measure is used in different situations depending on the type of data and what aspect of central tendency is most relevant.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
-------------------------------------------------------------------------------
Find out more about ISO training and certification services
Training: ISO/IEC 27001 Information Security Management System - EN | PECB
ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB
General Data Protection Regulation (GDPR) - Training Courses - EN | PECB
Webinars: https://pecb.com/webinars
Article: https://pecb.com/article
-------------------------------------------------------------------------------
For more information about PECB:
Website: https://pecb.com/
LinkedIn: https://www.linkedin.com/company/pecb/
Facebook: https://www.facebook.com/PECBInternational/
Slideshare: http://www.slideshare.net/PECBCERTIFICATION
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
हिंदी वर्णमाला पीपीटी, hindi alphabet PPT presentation, hindi varnamala PPT, Hindi Varnamala pdf, हिंदी स्वर, हिंदी व्यंजन, sikhiye hindi varnmala, dr. mulla adam ali, hindi language and literature, hindi alphabet with drawing, hindi alphabet pdf, hindi varnamala for childrens, hindi language, hindi varnamala practice for kids, https://www.drmullaadamali.com
BÀI TẬP BỔ TRỢ TIẾNG ANH 8 CẢ NĂM - GLOBAL SUCCESS - NĂM HỌC 2023-2024 (CÓ FI...
Median
1. MEDIAN
Median is the value which divides the series into two equal parts. Thus in the case
of median, the number of terms less than the median value and the number of terms
more than the median value, are equal.
Median is a positional measure. The position which is exactly in the centre, equal
number of terms lie on either side of it, when terms are arranged in ascending or
descending order.
Median is a statistical measure that determines the middle value of a dataset listed
in ascending order (i.e., from smallest to largest value). The measure divides the
lower half from the higher half of the dataset. Along with mean and mode, median
is a measure of central tendency.
According to Prof. L.R. Conner, “The median is that value of the variable which
divides the group into two equal parts, one part comprising all values greater and
the other all values less than median.”
Calculation of Median
I. Individual series
When number of terms is odd (1,3,7,5,9)
1. 5,7,9,12,10,8,7,15,21.
Arrange in ascending or descending order;
5,7,7,8,9,10,12,15,21.
N= 9
Now, M= N+1th term
2
= 9+1 th term
2
= 10/2
= 5th
term
M= 9
2. When number of terms is even (2,4,6,8,10)
2. 13,17,29,18,24,21,31,27,34,25.
Arrange in ascending or descending order;
13,17,18,21,24,25,27,29,31,34.
N= 10
Now, M= N+1th term
2
= 10+1 th term
2
= 11/2 = 5.5th
term
= 5th
term+ 6th
term
2
= 24+25
2
M = 24.5
Or
5.5th
term
5th
term +.5 (6th
term-5th
term)
24 +.5 (25-24) = 24.5
Do it yourself:
Calculate median from the following figures:
1. 28,47,30,37,54,58,61,64,31,34,52,55,62. (Ans. 52)
2. 10,18,9,17,15,24,30,11. (Ans. 16)
3. 60,35,48,52,26,27,47,50. (Ans. 47.5)
4. 17,32,35,32,15,21,42,11,10,18. (Ans. 19.5)
II. Discrete series
1. Calculate the value of median:
X 10 20 30 40 50 60 70
f 4 7 21 34 25 12 3
3. x f cf terms
10 4 4 1-4
20 7 4+7=11 5-11
30 21 11+21=32 12-32
40 34 32+34=66 33-66 53.5
50 25 66+25=91 67-91
60 12 91+12=103 92-103
70 3 103+3=106 104-106
N=106
M= size of {N+1}th term
2
= {106+1}th term
2
=107/2 th term
=53.5th
term (53.5 lies between 33-66)
Thus, M= 40.
Do it yourself
Calculate median:
1.
X 10 20 30 40 50 60 70
f 2 3 5 10 5 3 2
(Ans. 40)
2.
Size 105 110 115 120 125 130 135
f 2 3 4 6 10 5 2
(Ans. 125)
III. Continuous series
C.I. f cf terms
1-3 6 6 1-6
3-5 53 6+53=59 7-59
5-7 85 59+85=144 60-144
7-9 56 144+56=200 145-200
9-11 21 200+21=221 201-221
4. 11-13 16 221+16=237 222-237
13-15 4 237+4=241 238-241
15-17 4 241+4=245 242-245
M= L+ N1-cf X i
F
N= 245
N1 = N/2
245/2= 122.5
Cf= 59
F=85
i= 2
l= 5
M= 5 + 122.5-59 X 2
85
M= 5+ 63.5 X 2
85
M= 5 + 1.5
M= 6.5 Ans.
Do it yourself:
1.
C.I. 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50
f 22 45 67 73 85 190 64 55
(Ans. 35.22)
2.
X 10-25 25-40 40-55 55-70 70-85 85-100
f 6 50 44 26 3 1
(Ans. 43.07)
E-notes by:
Asst. Prof. Harpreet Kaur