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.
The class consists of 8 classes taught by two instructors. There are 3 take-home assignments due in classes 3, 5, and 7. A final take-home exam is assigned in class 8. The default dataset contains data from 60 subjects across 3-4 groups with different variable types. Students can also bring their own de-identified datasets. Special topics may include microarray analysis, pattern recognition, machine learning, and time series analysis.
MEASURES OF CENTRAL TENDENCY AND MEASURES OF DISPERSION Tanya Singla
Central tendency refers to typical or average values in a data set or probability distribution. The three most common measures of central tendency are the mean, median, and mode. The mean is the average calculated by summing 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. Other measures discussed include range, which is the difference between highest and lowest values, and quartiles, which divide a data set into four equal parts based on the distribution of values.
The document provides an overview of the structure and content of a biostatistics class. It includes:
- Two instructors who will teach 8 classes, with 3 take-home assignments and a final exam.
- Default and contributed datasets that students can use, focusing on nominal, ordinal, interval, and ratio variables.
- Optional late topics like microarray analysis, pattern recognition, and time series analysis.
The class consists of 8 classes taught by two instructors over biostatistics and psychology. There are 3 take-home assignments due in classes 3, 5, and 7 and a final take-home exam assigned in class 8. The default dataset for class participation contains data on 60 subjects across 3-4 treatment groups and various measure types. Special topics may include microarray analysis, pattern recognition, machine learning, and hidden Markov modeling.
The document provides an overview of the structure and content of a biostatistics class. It includes:
- Two instructors who will teach 8 classes, with 3 take-home assignments and a final exam.
- Default datasets with health data that students can use for assignments, and an option for students to bring their own de-identified data.
- Possible special topics like machine learning, time series analysis, and others.
The document provides an overview of the structure and content of a biostatistics class. It includes:
- Two instructors who will teach 8 classes, with 3 take-home assignments and a final exam.
- Default and contributed datasets that students can use, focusing on nominal, ordinal, interval, and ratio variables.
- Optional late topics like microarray analysis, pattern recognition, and time series analysis.
- A taxonomy of statistics, covering statistical description, presentation of data through graphs and numbers, and measures of center and variability.
The class consists of 8 classes taught by two instructors over biostatistics and psychology. There are 3 take-home assignments due in classes 3, 5, and 7. A final take-home exam is assigned in class 8. The default dataset contains data on 60 subjects across 3-4 treatment groups with various measure types. Students can also bring their own de-identified datasets. The course covers topics like microarray analysis, pattern recognition, machine learning and more.
STATISTICS BASICS INCLUDING DESCRIPTIVE STATISTICSnagamani651296
The class consists of 8 classes taught by two instructors over biostatistics and psychology. There are 3 take-home assignments due in classes 3, 5, and 7. A final take-home exam is assigned in class 8. The default dataset contains data on 60 subjects across 3-4 treatment groups with various measure types. Students can also bring their own de-identified datasets. The course covers topics like microarray analysis, pattern recognition, machine learning and more.
This document discusses measures of central tendency and dispersion used in epidemiology. It describes the mode, median, and mean as common measures of central tendency that attempt to quantify typical or average values in a data set. The mode is the most frequent value, the median is the middle value when data is arranged in order, and the mean is the average calculated by summing all values and dividing by the number of values. Measures of dispersion describe how spread out data is, such as the range which is the difference between the highest and lowest values. The next session will cover additional measures of disease including ratios, proportions, rates, and metrics of morbidity and mortality.
This document provides an introduction to statistics. It discusses what statistics is, the two main branches of statistics (descriptive and inferential), and the different types of data. It then describes several key measures used in statistics, including measures of central tendency (mean, median, mode) and measures of dispersion (range, mean deviation, standard deviation). The mean is the average value, the median is the middle value, and the mode is the most frequent value. The range is the difference between highest and lowest values, the mean deviation is the average distance from the mean, and the standard deviation measures how spread out values are from the mean. Examples are provided to demonstrate how to calculate each measure.
This document provides information about statistical methods for summarizing data, including measures of central tendency, variability, and position. It discusses the mean, median, mode, range, variance, standard deviation, z-scores, and percentiles. The mean is the average value and considers all data points. The median divides the data in half. The mode is the most frequent value. Variance and standard deviation measure how spread out values are around the mean. Percentiles and z-scores indicate a value's position relative to others in the data set.
The document discusses various measures of central tendency (averages) and dispersion that are used to summarize and describe data in statistics. It defines common averages like the arithmetic mean, median, mode, harmonic mean, and geometric mean. It also covers measures of dispersion such as the range, quartile deviation, mean deviation, and standard deviation. As an example, it analyzes test score data from 5 students using the arithmetic mean to find the average score.
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 various measures of central tendency and variability used in statistics. It describes the three main measures of central tendency as the mode, median, and mean. For measures of variability, it defines concepts like range, variance, and standard deviation. The range is described as the highest score minus the lowest score and provides a simple measure of variation. Variance is defined as the mean of the squared deviations from the mean and standard deviation is the square root of the variance, providing a measure of how data points cluster around the mean. Examples are provided to demonstrate calculating each of these statistical measures.
The three main measures of central tendency are 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 values are arranged from lowest to highest. The mode is the most frequently occurring value. For symmetric distributions, the mean, median, and mode will be equal. However, for skewed distributions the mean will be pulled higher or lower than the median depending on the direction of skew.
Statistics involves collecting, organizing, and analyzing data. There are several ways to present data including lists, frequency charts, histograms, percentage charts, and pie charts. Central tendency refers to averages that describe the center of a data set. The three main measures of central tendency are the mean, median, and mode. The mean is calculated by adding 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 frequent value. A weighted mean assigns different weights or importance to values before calculating the average.
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.
Measures of Central Tendency, Variability and ShapesScholarsPoint1
The PPT describes the Measures of Central Tendency in detail such as Mean, Median, Mode, Percentile, Quartile, Arthemetic mean. Measures of Variability: Range, Mean Absolute deviation, Standard Deviation, Z-Score, Variance, Coefficient of Variance as well as Measures of Shape such as kurtosis and skewness in the grouped and normal data.
This slide is an exercise for the inquisitive students preparing for the competitive examinations of the undergraduate and postgraduate students. An attempt is being made to present the slide keeping in mind the New Education Policy (NEP). An attempt has been made to give the references of the facts at the end of the slide. If new facts are discovered in the near future, this slide will be revised.
This presentation is related to the brief History of Kashmir (Part-I) with special reference to Karkota Dynasty. In the seventh century a person named Durlabhvardhan founded the Karkot dynasty in Kashmir. He was a functionary of Baladitya, the last king of the Gonanda dynasty. This dynasty ruled Kashmir before the Karkot dynasty. He was a powerful king. Huansang tells us that in his time Taxila, Singhpur, Ursha, Punch and Rajputana were parts of the Kashmir state.
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The class consists of 8 classes taught by two instructors over biostatistics and psychology. There are 3 take-home assignments due in classes 3, 5, and 7. A final take-home exam is assigned in class 8. The default dataset contains data on 60 subjects across 3-4 treatment groups with various measure types. Students can also bring their own de-identified datasets. The course covers topics like microarray analysis, pattern recognition, machine learning and more.
STATISTICS BASICS INCLUDING DESCRIPTIVE STATISTICSnagamani651296
The class consists of 8 classes taught by two instructors over biostatistics and psychology. There are 3 take-home assignments due in classes 3, 5, and 7. A final take-home exam is assigned in class 8. The default dataset contains data on 60 subjects across 3-4 treatment groups with various measure types. Students can also bring their own de-identified datasets. The course covers topics like microarray analysis, pattern recognition, machine learning and more.
This document discusses measures of central tendency and dispersion used in epidemiology. It describes the mode, median, and mean as common measures of central tendency that attempt to quantify typical or average values in a data set. The mode is the most frequent value, the median is the middle value when data is arranged in order, and the mean is the average calculated by summing all values and dividing by the number of values. Measures of dispersion describe how spread out data is, such as the range which is the difference between the highest and lowest values. The next session will cover additional measures of disease including ratios, proportions, rates, and metrics of morbidity and mortality.
This document provides an introduction to statistics. It discusses what statistics is, the two main branches of statistics (descriptive and inferential), and the different types of data. It then describes several key measures used in statistics, including measures of central tendency (mean, median, mode) and measures of dispersion (range, mean deviation, standard deviation). The mean is the average value, the median is the middle value, and the mode is the most frequent value. The range is the difference between highest and lowest values, the mean deviation is the average distance from the mean, and the standard deviation measures how spread out values are from the mean. Examples are provided to demonstrate how to calculate each measure.
This document provides information about statistical methods for summarizing data, including measures of central tendency, variability, and position. It discusses the mean, median, mode, range, variance, standard deviation, z-scores, and percentiles. The mean is the average value and considers all data points. The median divides the data in half. The mode is the most frequent value. Variance and standard deviation measure how spread out values are around the mean. Percentiles and z-scores indicate a value's position relative to others in the data set.
The document discusses various measures of central tendency (averages) and dispersion that are used to summarize and describe data in statistics. It defines common averages like the arithmetic mean, median, mode, harmonic mean, and geometric mean. It also covers measures of dispersion such as the range, quartile deviation, mean deviation, and standard deviation. As an example, it analyzes test score data from 5 students using the arithmetic mean to find the average score.
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 various measures of central tendency and variability used in statistics. It describes the three main measures of central tendency as the mode, median, and mean. For measures of variability, it defines concepts like range, variance, and standard deviation. The range is described as the highest score minus the lowest score and provides a simple measure of variation. Variance is defined as the mean of the squared deviations from the mean and standard deviation is the square root of the variance, providing a measure of how data points cluster around the mean. Examples are provided to demonstrate calculating each of these statistical measures.
The three main measures of central tendency are 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 values are arranged from lowest to highest. The mode is the most frequently occurring value. For symmetric distributions, the mean, median, and mode will be equal. However, for skewed distributions the mean will be pulled higher or lower than the median depending on the direction of skew.
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3. History and Definition
Measures of central location was first found in the mid 1690’s in the writings of
Edmund Halley. It has been used to summarize observations of a variable since the
time of Galileo (1564 – 1642).
Measures of central location are a combination of two words i.e., “measure” and “
central location”. Measure means methods and central location means average
value of any statistical series.
Central location is a summary measure that attempts to describe a whole set of
data with a single value that represents the middle or centre of its distribution.
4. cont’d
The measures of central tendency include:
1. The mode
2. The mean
3. The range
4. Upper and lower quartile
5. Variants
6. Median
5. THE MODE
The mode is the most occurring value in a distribution.
On a bar chart, the mode is the highest bar. If the data have multiple values that are tied for
occurring the most frequently, you have a multi modal ( having several modes or maxima)
distribution.
Below is the example of mode from a data set showing the age of pupils at Chipiloni primary
school.
6,6,6,7,7,7,7,8,8,8,9,9,9,9,9,10,11,11,12,12,13,13,13,13,14,14
The numbers have to be placed in order as shown above; it may either starts from the lowest to
the highest or from the highest to the lowest.
And then count how many times each number appears in a set.
The one that appears the most is the mode.
From the data set above, the most appearing number is 9, therefore the mode is 9.
The value nine is appearing (frequency) five times greater than any other number
6. THE MEAN
This is the arithmetic average and it is probably the measure of central tendency
that you are most familiar.
To calculate the mean, you add up all the total values given in a data sheet and
divide the sum by the total number of values.
Mean = sum of given data/total number of data
Below is an example of test scores in a class:
39, 40,40,55, 62, 71, 71, 71, 86,95.
39+40+40+55+62+71+71+71+86+95
10
Mean= 63
7. THE MEDIAN
Another common measure of central location is the median. It is useful when the data is skewed (sudden change in
direction or position).
Median means middle and the median is the middle of a set of data that has been into rank order.
Median is the measure of central tendency which gives the value of the middle most observation in the data.
Median of ungrouped data, we arrange the data values of the observations in ascending order and count the total
number of observations.
The number that is at the middle after arranging the values in ascending order is the median.
E.g. 1,3,2,4,8,7,9,6
1. Arrange the numbers in order
1,2,3,4,5,6,7,8,9
The median is the number that is at the middle of the whole numbers, that is 5.
When the values are even, we add the two middle number and divide them by 2
E.g. 1,2,3,4,5,6,7,8,9,10
The middle numbers are 5 and 6.
Therefore, the median is 5+6/2= 5.5
8. RANGE
The range of set of data is the difference between the largest and smallest values.
The answer is found by subtracting the sample maximum and minimum.
It is expressed in the same units as the data.
Range of (y) = Max (y) – Min (y)
E.g. find the range of the following data set.
10,15,20,25,30,35,40
Range = 40-10
Range = 30
9. UPPER AND LOWER QUARTILE
The upper quartile or the third quartile (Q3), is the value under which 75% of data
points are found when arranged in increasing order.
The lower quartile or the first quartile (Q1), is the value under which 25% of data points
are arranged in increasing order.
How to calculate Quartiles
1. Order the data set from lowest to highest values.
2. Find the median. This is the second quartile Q2.
3. At Q2, split the ordered data set into two halves.
4. The lower quartile, Q1, is the median of the lower half of the data.
5. The upper quartile, Q3, is the median of the upper half of the data
10. Quartile cont’d
The class has the following frequency distribution of marks scored by students 20, 30, 35, 45, 50, 55, 60,
65,88. find the first and third quartile.
I. The numbers are already arranged in order.
II. The median (Q2) is 50
To find first quartile:
Q1= 30+35
2
Q1= 32.5
To find third quartile:
Q3= 60+65
2
Q3= 62.5
11. REMARKS AND CONCLUSIONS
Above scenarios shows that the measure of central location summarizes a list of
numbers by a typical value and the three most common measures are:
1) The mean
2) The mode
3) The median.
The median is the most appropriate measure of location for ordinal variable.
However, mean is generally considered the best measure of central tendency and the
most frequently used. This is the case because it uses all values in the data set to give
you an average.
Median is better than mean when measuring skewed data since it is not influenced by
extremely large values.