Range, Mode, Median and Mean
•Download as PPTX, PDF•
3 likes•2,733 views
This document defines and provides examples to calculate range, mode, median, and mean. It explains that to calculate these measures, the data set must first be arranged in ascending order. Range is the difference between the highest and lowest values, measuring dispersion. Mode is the most frequent value. Median is the middle value of an ordered data set. For an even number of values, the median is the average of the two middle values. Mean is the sum of all values divided by the total number of values, being the most widely used measure of central tendency. An example problem demonstrates calculating all four measures for a sample data set.
Report
Share
Report
Share
Recommended
Averages and range
This document provides information about different types of averages (mean, median, mode) and the range, and how to calculate them from raw data and frequency tables. It discusses when each average is most appropriate to use and how outliers can affect calculations. Examples are provided of calculating averages and range from sets of data, as well as estimating the mean from grouped data. The median is defined as the middle number when values are in order. Outliers are identified as values significantly higher or lower than others.
Data Handling
Data is a collection of observations that can be represented visually to better understand and remember the facts more easily. Data refers to a collection of information in numerical or fact form. Median is the middle value of a set of numbers when arranged in ascending order or is the average of the two middle values if the set contains an even number of numbers.
Stem and-leaf plots
This document explains how to create and interpret stem-and-leaf plots, which organize numeric data into place values to facilitate analysis. It provides examples of creating stem-and-leaf plots from sets of test scores and Olympic speed skating times. Key aspects covered include using stems for tens places and leaves for ones, adding a title and key, and how stem-and-leaf plots can be used to find the median, mode, and minimum/maximum values from a data set.
Mean, median, and mode
The document defines and provides examples to calculate mean, median, mode, and range for sets of numerical data. Mean is the average, calculated by summing the values and dividing by the count. Median is the middle number when values are ordered from lowest to highest. Mode is the number that occurs most frequently. Range is the difference between the highest and lowest values. Examples are provided to demonstrate calculating each measure using sample data sets.
Common Multiples and Least Common Multiple
The document explains how to find the least common multiple (LCM) of two numbers. It defines key terms like product, multiple, and common multiple. It then provides examples of finding the LCM of 3 and 6, 9 and 12, and 4 and 6. For each example, it lists the multiples of each number, circles the common multiples, and identifies the smallest common multiple as the LCM. The overall process is to list multiples, identify common multiples, and select the smallest value from the common multiples as the LCM.
Stem and-leaf-diagram-ppt.-dfs
This document discusses stem-and-leaf diagrams, line charts, and scatter diagrams. It provides examples and steps for constructing each type of graph. Stem-and-leaf diagrams display and order numerical data using digits in the tens and ones places. Line charts show the relationship between two quantitative variables over time. Scatter diagrams plot the relationship between two quantitative variables to determine if they are correlated. Examples and steps are given for accurately constructing each graph.
Calculating the mean, median and mode
The document discusses calculating the mean, median, and mode of data sets. It provides examples of how to calculate the mean by adding all values and dividing by the number of values. The median is found by ordering values and selecting the middle value or averaging the two middle values. The mode is the most frequently occurring value. Examples are given of calculating each measure for various data sets.
Box And Whisker Plots
This document provides instruction on calculating measures of variability such as range, quartiles, and creating box-and-whisker plots. It includes examples of finding the range and quartiles for data sets. Additional examples demonstrate how to make box-and-whisker plots from data and compare plots to analyze differences between data sets. Practice problems are provided to have students calculate range, quartiles, and create box-and-whisker plots.
Recommended
Averages and range
This document provides information about different types of averages (mean, median, mode) and the range, and how to calculate them from raw data and frequency tables. It discusses when each average is most appropriate to use and how outliers can affect calculations. Examples are provided of calculating averages and range from sets of data, as well as estimating the mean from grouped data. The median is defined as the middle number when values are in order. Outliers are identified as values significantly higher or lower than others.
Data Handling
Data is a collection of observations that can be represented visually to better understand and remember the facts more easily. Data refers to a collection of information in numerical or fact form. Median is the middle value of a set of numbers when arranged in ascending order or is the average of the two middle values if the set contains an even number of numbers.
Stem and-leaf plots
This document explains how to create and interpret stem-and-leaf plots, which organize numeric data into place values to facilitate analysis. It provides examples of creating stem-and-leaf plots from sets of test scores and Olympic speed skating times. Key aspects covered include using stems for tens places and leaves for ones, adding a title and key, and how stem-and-leaf plots can be used to find the median, mode, and minimum/maximum values from a data set.
Mean, median, and mode
The document defines and provides examples to calculate mean, median, mode, and range for sets of numerical data. Mean is the average, calculated by summing the values and dividing by the count. Median is the middle number when values are ordered from lowest to highest. Mode is the number that occurs most frequently. Range is the difference between the highest and lowest values. Examples are provided to demonstrate calculating each measure using sample data sets.
Common Multiples and Least Common Multiple
The document explains how to find the least common multiple (LCM) of two numbers. It defines key terms like product, multiple, and common multiple. It then provides examples of finding the LCM of 3 and 6, 9 and 12, and 4 and 6. For each example, it lists the multiples of each number, circles the common multiples, and identifies the smallest common multiple as the LCM. The overall process is to list multiples, identify common multiples, and select the smallest value from the common multiples as the LCM.
Stem and-leaf-diagram-ppt.-dfs
This document discusses stem-and-leaf diagrams, line charts, and scatter diagrams. It provides examples and steps for constructing each type of graph. Stem-and-leaf diagrams display and order numerical data using digits in the tens and ones places. Line charts show the relationship between two quantitative variables over time. Scatter diagrams plot the relationship between two quantitative variables to determine if they are correlated. Examples and steps are given for accurately constructing each graph.
Calculating the mean, median and mode
The document discusses calculating the mean, median, and mode of data sets. It provides examples of how to calculate the mean by adding all values and dividing by the number of values. The median is found by ordering values and selecting the middle value or averaging the two middle values. The mode is the most frequently occurring value. Examples are given of calculating each measure for various data sets.
Box And Whisker Plots
This document provides instruction on calculating measures of variability such as range, quartiles, and creating box-and-whisker plots. It includes examples of finding the range and quartiles for data sets. Additional examples demonstrate how to make box-and-whisker plots from data and compare plots to analyze differences between data sets. Practice problems are provided to have students calculate range, quartiles, and create box-and-whisker plots.
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.
Mean, Median, Mode, And Range
The document defines and provides examples for calculating the mean, median, mode, and range of a data set. The mean is the average found by summing all values and dividing by the number of values. The median is the middle number after sorting values. The mode is the most frequently occurring value. The range is the difference between the highest and lowest values. An example data set at the end is used to demonstrate calculating all four measures.
Mean, median, mode, & range ppt
This document defines and provides examples for calculating the mean, median, mode, and range of a data set. It explains that the mean is calculated by adding all values and dividing by the number of values, the median involves ordering values and selecting the middle one, the mode is the most frequent value, and the range is the difference between the highest and lowest values. Examples are given for each statistical measure.
Standard Deviation and Variance
The document discusses how to calculate standard deviation and variance for both ungrouped and grouped data. It provides step-by-step instructions for finding the mean, deviations from the mean, summing the squared deviations, and using these values to calculate standard deviation and variance through standard formulas. Standard deviation measures how spread out numbers are from the mean, while variance is the square of the standard deviation.
Dr digs central tendency
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.
Measures Of Central Tendencies
The document discusses measures of central tendency including the mean, median, and mode. It defines each term and provides examples of what can be understood when given different statistical data involving these measures. The mean is the average and is calculated by adding all values and dividing by the number of data points. The median is the middle number when values are in order. The mode is the value that occurs most frequently. Examples are given to illustrate what can be understood when provided the mean, median, number of data points, and total values. The measures are also compared in terms of when each is most useful.
Mean Median Mode
This document defines and provides instructions for calculating mean, median, mode, and range for a set of numbers. It defines each term, explains the steps to calculate each, and provides examples of calculating mean, median, mode, and range for practice number sets.
Measures of central tendency ppt
This document discusses measures of central tendency, including the mean, median, and mode. It provides examples of calculating each measure using sample data sets. The mean is the average value calculated by summing all values and dividing by the number of data points. The median is the middle value when data is ordered from lowest to highest. The mode is the most frequently occurring value. Examples are given to demonstrate calculating the mean, median, and mode from sets of numeric data.
Skewness and Kurtosis
Skewness and kurtosis explained using examples and case studies based on climatic changes to explain these concepts.
Introduction to Exponents
This presentation is an introduction to Exponents. Students will begin with repeated multiplication. They will then be reminded about a base an exponent. They will learn the term Exponential Form.
Statistics report THE RANGE
The range is the simplest measure of variability, defined as the difference between the highest and lowest values in a data set. It is quick to calculate but does not provide a full picture of the data distribution and can be strongly influenced by outliers. Other measures of variability include the average deviation, which calculates the average amount each score deviates from the mean, and the interquartile range, which is less influenced by outliers than the range. The interquartile range only considers data between the first and third quartiles and ignores half the data points.
Venn Diagrams and Sets
Introduction to Venn Diagrams and Sets. Includes the Operations: Intersection, Union, Complement.
If you would like a download of this PowerPoint then go to the following page:
http://passyworldofmathematics.com/pwerpoints/
Addition and subtraction of rational expression
To add or subtract fractions with unlike denominators:
1. Find the least common denominator (LCD), which contains all prime factors of each denominator raised to the highest power.
2. Convert the fractions to equivalent fractions with the LCD as the denominator.
3. Perform the addition or subtraction on the numerators and write the sum or difference over the common denominator.
Factors And Prime Factorization
Factors are numbers that can be multiplied together to produce another number. The prime factorization of a number breaks it down into a product of prime numbers. For example, the prime factorization of 48 is 2 x 2 x 2 x 3, as 48 can be broken down into its prime factors of 2 and 3. There are two methods for finding the prime factorization of a number: using a factor tree or a ladder.
MEAN DEVIATION
The mean deviation is a measure of how spread out values are from the average. It is calculated by:
1) Finding the mean of all values.
2) Calculating the distance between each value and the mean.
3) Taking the average of those distances. This provides the mean deviation, which tells us how far on average values are from the central mean. Examples show calculating mean deviation for both grouped and ungrouped data sets.
Algebra Expressions in Word Problems
Little Red Riding Hood needs to walk 5 miles to get to her destination. The document shows the time it would take her to walk 5 miles at different speeds: 5 hours if walking at 1 mile per hour, 1 hour if walking at 5 miles per hour, and 0.5 hours or 30 minutes if running at 10 miles per hour. The algebra expression that calculates time for any speed is 5 divided by the speed (5/S). Word problems are translated into algebra expressions so they can be solved mathematically. Examples of key words that translate into different algebra operations are provided.
Introduction To Equations
The document discusses equations and solving equations. It defines an equation as a statement of equality between two or more quantities that always includes an equal sign. Equations can be true, false, or open. To solve an equation means to find the value of the variable that makes the statement true. The document provides examples of different types of equations and introduces the cover-up method for solving equations.
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
Exponents And Order Of Operations
An exponent tells us how many times to multiply a base by itself. When evaluating an expression with exponents, exponents inside parentheses are evaluated first before any other operations. Exponents outside parentheses are evaluated after completing all operations inside the parentheses. Order of operations must be followed when evaluating expressions with multiple operations, exponents, and parentheses.
Measures of central tendency
- There are three main measures of central tendency: the mean, median, and mode. 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 data is arranged in order. The mode is the most frequently occurring value.
- To determine which measure to use, consider if the data has extreme values and whether the most common value is needed over the average. The mean can be skewed by outliers while the median and mode are more robust. The appropriate measure depends on the characteristics of the specific data set.
central tendency.pptx
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.
Presentation slide on central tendency
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.
More Related Content
What's hot
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.
Mean, Median, Mode, And Range
The document defines and provides examples for calculating the mean, median, mode, and range of a data set. The mean is the average found by summing all values and dividing by the number of values. The median is the middle number after sorting values. The mode is the most frequently occurring value. The range is the difference between the highest and lowest values. An example data set at the end is used to demonstrate calculating all four measures.
Mean, median, mode, & range ppt
This document defines and provides examples for calculating the mean, median, mode, and range of a data set. It explains that the mean is calculated by adding all values and dividing by the number of values, the median involves ordering values and selecting the middle one, the mode is the most frequent value, and the range is the difference between the highest and lowest values. Examples are given for each statistical measure.
Standard Deviation and Variance
The document discusses how to calculate standard deviation and variance for both ungrouped and grouped data. It provides step-by-step instructions for finding the mean, deviations from the mean, summing the squared deviations, and using these values to calculate standard deviation and variance through standard formulas. Standard deviation measures how spread out numbers are from the mean, while variance is the square of the standard deviation.
Dr digs central tendency
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.
Measures Of Central Tendencies
The document discusses measures of central tendency including the mean, median, and mode. It defines each term and provides examples of what can be understood when given different statistical data involving these measures. The mean is the average and is calculated by adding all values and dividing by the number of data points. The median is the middle number when values are in order. The mode is the value that occurs most frequently. Examples are given to illustrate what can be understood when provided the mean, median, number of data points, and total values. The measures are also compared in terms of when each is most useful.
Mean Median Mode
This document defines and provides instructions for calculating mean, median, mode, and range for a set of numbers. It defines each term, explains the steps to calculate each, and provides examples of calculating mean, median, mode, and range for practice number sets.
Measures of central tendency ppt
This document discusses measures of central tendency, including the mean, median, and mode. It provides examples of calculating each measure using sample data sets. The mean is the average value calculated by summing all values and dividing by the number of data points. The median is the middle value when data is ordered from lowest to highest. The mode is the most frequently occurring value. Examples are given to demonstrate calculating the mean, median, and mode from sets of numeric data.
Skewness and Kurtosis
Skewness and kurtosis explained using examples and case studies based on climatic changes to explain these concepts.
Introduction to Exponents
This presentation is an introduction to Exponents. Students will begin with repeated multiplication. They will then be reminded about a base an exponent. They will learn the term Exponential Form.
Statistics report THE RANGE
The range is the simplest measure of variability, defined as the difference between the highest and lowest values in a data set. It is quick to calculate but does not provide a full picture of the data distribution and can be strongly influenced by outliers. Other measures of variability include the average deviation, which calculates the average amount each score deviates from the mean, and the interquartile range, which is less influenced by outliers than the range. The interquartile range only considers data between the first and third quartiles and ignores half the data points.
Venn Diagrams and Sets
Introduction to Venn Diagrams and Sets. Includes the Operations: Intersection, Union, Complement.
If you would like a download of this PowerPoint then go to the following page:
http://passyworldofmathematics.com/pwerpoints/
Addition and subtraction of rational expression
To add or subtract fractions with unlike denominators:
1. Find the least common denominator (LCD), which contains all prime factors of each denominator raised to the highest power.
2. Convert the fractions to equivalent fractions with the LCD as the denominator.
3. Perform the addition or subtraction on the numerators and write the sum or difference over the common denominator.
Factors And Prime Factorization
Factors are numbers that can be multiplied together to produce another number. The prime factorization of a number breaks it down into a product of prime numbers. For example, the prime factorization of 48 is 2 x 2 x 2 x 3, as 48 can be broken down into its prime factors of 2 and 3. There are two methods for finding the prime factorization of a number: using a factor tree or a ladder.
MEAN DEVIATION
The mean deviation is a measure of how spread out values are from the average. It is calculated by:
1) Finding the mean of all values.
2) Calculating the distance between each value and the mean.
3) Taking the average of those distances. This provides the mean deviation, which tells us how far on average values are from the central mean. Examples show calculating mean deviation for both grouped and ungrouped data sets.
Algebra Expressions in Word Problems
Little Red Riding Hood needs to walk 5 miles to get to her destination. The document shows the time it would take her to walk 5 miles at different speeds: 5 hours if walking at 1 mile per hour, 1 hour if walking at 5 miles per hour, and 0.5 hours or 30 minutes if running at 10 miles per hour. The algebra expression that calculates time for any speed is 5 divided by the speed (5/S). Word problems are translated into algebra expressions so they can be solved mathematically. Examples of key words that translate into different algebra operations are provided.
Introduction To Equations
The document discusses equations and solving equations. It defines an equation as a statement of equality between two or more quantities that always includes an equal sign. Equations can be true, false, or open. To solve an equation means to find the value of the variable that makes the statement true. The document provides examples of different types of equations and introduces the cover-up method for solving equations.
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
Exponents And Order Of Operations
An exponent tells us how many times to multiply a base by itself. When evaluating an expression with exponents, exponents inside parentheses are evaluated first before any other operations. Exponents outside parentheses are evaluated after completing all operations inside the parentheses. Order of operations must be followed when evaluating expressions with multiple operations, exponents, and parentheses.
Measures of central tendency
- There are three main measures of central tendency: the mean, median, and mode. 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 data is arranged in order. The mode is the most frequently occurring value.
- To determine which measure to use, consider if the data has extreme values and whether the most common value is needed over the average. The mean can be skewed by outliers while the median and mode are more robust. The appropriate measure depends on the characteristics of the specific data set.
What's hot (20)
Similar to Range, Mode, Median and Mean
central tendency.pptx
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.
Presentation slide on central tendency
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.
G7-quantitative
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.
A Brief Overview On Central Tendency.pptx
Central tendency refers to a single value that describes the center of a dataset and is one of the most fundamental concepts in statistics. The three main measures of central tendency are the mean, median, and mode. The mean is the average value calculated by summing all values and dividing by the total 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. Central tendency provides a summary of a dataset without conveying information about individual values.
Descriptive statistics
This document discusses descriptive statistics concepts including measures of center (mean, median, mode), measures of variation (range, standard deviation, variance), and properties of distributions (symmetric, skewed). Frequency tables are presented as a method to summarize data, including guidelines for construction and different types (relative frequency and cumulative frequency). Common notation and formulas are provided.
Mean, median, mode, and range
The document defines and provides examples for calculating the mean, median, mode, and range of a data set. It explains that the mean is the average found by adding all values and dividing by the number of values. The median is the middle value when the data is arranged from lowest to highest. The mode is the value that appears most frequently. The range is the difference between the highest and lowest values. It provides sample data sets and asks the reader to find the mean, median, mode, and range.
Digital textbook std ix
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.
Mean, Median, Mode
This document defines and provides instructions for calculating mean, median, mode, and range for a set of numbers. It explains that mean is the average found by adding all numbers and dividing by the total. Median is the middle number after arranging in order. Mode is the number that appears most frequently. Range is the difference between the greatest and least values. Examples are provided to demonstrate calculating each measure for different data sets.
descriptive statistics- 1.pptx
This document discusses descriptive statistics techniques for quantitative data analysis. It defines two main approaches in statistics - descriptive statistics which are used to summarize and organize data, and inferential statistics which are used to make inferences about populations from samples. Descriptive statistics techniques discussed include visual displays, measures of central tendency (mean, median, mode), and measures of variability or dispersion (range, variance, standard deviation). Formulas for calculating various measures are provided along with explanations of their advantages and disadvantages.
Mean, Mode, Median[1]
This document defines and provides examples for calculating the mean, median, mode, and range of data sets. It explains that the mean is the average found by adding all values and dividing by the number of values. The median is the middle value when values are ordered from lowest to highest. The mode is the most frequently occurring value. The range is the difference between the highest and lowest values. Step-by-step instructions and examples are given for calculating each measure of central tendency and dispersion.
Mean, Mode, Median[1]
This document defines and provides examples for calculating the mean, median, mode, and range of data sets. It explains that the mean is the average found by adding all values and dividing by the number of values. The median is the middle value when values are ordered from lowest to highest. The mode is the most frequently occurring value. The range is the difference between the highest and lowest values. Step-by-step instructions and examples are given for calculating each measure of central tendency and dispersion.
Mean,%20 Mode,%20 Median[1]
This document defines and provides examples for calculating the mean, median, mode, and range of data sets. It explains that the mean is the average found by adding all values and dividing by the number of values. The median is the middle value when values are ordered from lowest to highest. The mode is the most frequently occurring value. The range is the difference between the highest and lowest values. Step-by-step instructions and examples are given for calculating each measure of central tendency and dispersion.
Mean, Mode, Median[1]
This document defines and provides examples for calculating the mean, median, mode, and range of data sets. It explains that the mean is the average found by adding all values and dividing by the number of values. The median is the middle value when values are ordered from lowest to highest. The mode is the most frequently occurring value. The range is the difference between the highest and lowest values. Step-by-step instructions and examples are given for calculating each measure of central tendency and dispersion.
Mean,%2520 Mode,%2520 Median[1][1]
This document defines and provides examples for calculating the mean, median, mode, and range of data sets. It explains that the mean is the average found by adding all values and dividing by the number of values. The median is the middle value when values are ordered from lowest to highest. The mode is the most frequently occurring value. The range is the difference between the highest and lowest values. Step-by-step instructions and examples are given for calculating each measure of central tendency and dispersion.
Measurement of Central Tendency.pptx
Central tendency refers to statistical measures that identify a single representative value of a data distribution. There are three main measures of central tendency: 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 of a sorted list of numbers. The mode is the most frequently occurring value in a data set. These measures are used across various domains to analyze and summarize data.
Central Tendency.pptx
Central tendency refers to measures that describe the center or typical value of a dataset. The three main measures of central tendency are the 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 data is arranged in order. For even datasets, the median is the average of the two middle values. The mode is the value that occurs most frequently in the dataset.
classroom 2.pptx
The document defines and provides examples of calculating the mean, median, and mode of data sets. It discusses how the mean is the average, median is the middle value, and mode is the most frequent value. Examples are provided to demonstrate calculating each measure of central tendency for both ungrouped and grouped data. An assessment with multiple choice and short answer questions is also included to test understanding of these concepts.
Statistics " Measurements of central location chapter 2"
This is the power point presentation on measurement of central location chapter 2 in Statics field.
Medidas de Tendencia Central
La Medida de Tendencia Central: Es un número ubicado hacia el centro de la distribución de los valores de una serie, en la que se encuentra ubicado el conjunto de los datos.
Measures of central tendency
Central tendency refers to measures that characterize the middle or center of a data set. The three most common measures of central tendency are the mean, median, and mode. The mean is the average value found by dividing the sum of all values by the 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 in the data set. These measures help analyze and understand data in a statistical analysis.
Similar to Range, Mode, Median and Mean (20)
Statistics " Measurements of central location chapter 2"
Statistics " Measurements of central location chapter 2"
Recently uploaded
How to Make a Field Mandatory in Odoo 17
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.
South African Journal of Science: Writing with integrity workshop (2024)
South African Journal of Science: Writing with integrity workshop (2024)Academy of Science of South Africa
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.BBR 2024 Summer Sessions Interview Training
Qualitative research interview training by Professor Katrina Pritchard and Dr Helen Williams
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
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
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS Template 2023-2024 by: Irene S. Rueco
Azure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHat
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Aberdeen
Hindi varnamala | hindi alphabet PPT.pdf
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
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...National Information Standards Organization (NISO)
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.The History of Stoke Newington Street Names
Presented at the Stoke Newington Literary Festival on 9th June 2024
www.StokeNewingtonHistory.com
PCOS corelations and management through Ayurveda.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
How to Build a Module in Odoo 17 Using the Scaffold Method
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
The Diamonds of 2023-2024 in the IGRA collection
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.
Recently uploaded (20)
South African Journal of Science: Writing with integrity workshop (2024)
South African Journal of Science: Writing with integrity workshop (2024)
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
RPMS TEMPLATE FOR SCHOOL YEAR 2023-2024 FOR TEACHER 1 TO TEACHER 3
Azure Interview Questions and Answers PDF By ScholarHat
Azure Interview Questions and Answers PDF By ScholarHat
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
The simplified electron and muon model, Oscillating Spacetime: The Foundation...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
What is Digital Literacy? A guest blog from Andy McLaughlin, University of Ab...
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Executive Directors Chat Leveraging AI for Diversity, Equity, and Inclusion
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
Pollock and Snow "DEIA in the Scholarly Landscape, Session One: Setting Expec...
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UP
How to Build a Module in Odoo 17 Using the Scaffold Method
How to Build a Module in Odoo 17 Using the Scaffold Method
Range, Mode, Median and Mean
- 1. Range Mode Median Mean What do they all mean?
- 2. NEED TO KNOW! ALWAYS ARRANGE THE VALUES IN A DATA SET IN ASCENDING (LEAST TO GREATEST) ORDER BEFORE SOLVING FOR RANGE, MODE, MEDIAN AND MEAN.
- 3. Range measure of dispersion (spread) obtained by subtracting the smallest value fromthelargestvalue 14, 17, 17, 21, 25, 28, 28, 28, 33 highest value = 33 lowest value = 14 range = 33 – 14 = 19
- 4. Central Tendency single numerical value used to describe the average or typical value in a set of values 3 measures of central tendency mode median mean
- 5. Mode most frequent or popular value in a data set determined by inspection 14, 17, 17, 21, 25, 28, 28, 28, 33 mode = (get 28 three time, get 17 twice and all other values only once) 28
- 6. Median counting average the middle score 14, 17, 17, 21, 25, 28, 28, 28, 33 median = With an odd number of values, the median is the middle value. However, with an even number of values, there are two middle values. Since the median can only be a single value, the median will have to be calculated with an even number of values. How can this be done? 25
- 7. Median cont’d to figure out the median with an even number of values find the two middle values find the average of these values by adding the two values together and dividing by two 14, 17, 17, 19, 21, 25, 28, 28, 28, 33 two middle numbers = 21 & 25 21 + 25 = 46 median = 46 ÷ 2 = 23
- 8. Mean arithmetic average most widely used measure of central tendency calculate by adding all the values together and dividing by the number of values 14, 17, 17, 21, 25, 28, 28, 28, 33 14+17+17+21+25+28+28+28+33 = 211 mean = 211 ÷ 9 = 23.4
- 9. REMEMBER ALWAYS ARRANGE THE VALUES IN A DATA SET IN ASCENDING (LEAST TO GREATEST) ORDER BEFORE SOLVING FOR RANGE, MODE, MEDIAN AND MEAN.
- 10. LET’S PRACTICE
- 11. Find the range, mode, median and mean of this data set. 21, 18, 26, 30, 15, 26, 12, 18, 29, 26, 14, 23 First arrange the numbers in ascending order… 12, 14, 15, 18, 18, 21, 23, 26, 26, 26, 29, 30 range = 30 – 12 = 18 mode = 26 median = 21 + 23 = 44 ÷ 2 = 22 12+14+15+18+18+21+23+26+26+26+29+30 12 mean = 258 ÷ 12 = 21.5
- 12. NOW FOR A STORY PROBLEM…
- 13. Amy works for a record store. For the past two weeks, she has kept track of the number of records that have sold each day. Find the range, mode, median and mean of this data.
- 14. Answers Put the numbers in order… 15, 17, 18, 19, 19, 19, 20, 22, 24, 25, 26, 28, 29, 30 range = 15 mode = 19 median = 21 mean = 22.2