The standard deviation is a measure of the spread of scores within a set of data. Usually, we are interested in the standard deviation of a population.
This presentation gives you a brief idea;
-definition of frequency distribution
- types of frequency distribution
-types of charts used in the distribution
-a problem on creating types of distribution
-advantages and limitations of the distribution
This presentation gives you a brief idea;
-definition of frequency distribution
- types of frequency distribution
-types of charts used in the distribution
-a problem on creating types of distribution
-advantages and limitations of the distribution
students will be able to understand various measures of central tendency and also will be able to calculate mean median and mode for individual discrete and continuous series.
Brief description of the concepts related to correlation analysis. Problem Sums related to Karl Pearson's Correlation, Spearman's Rank Correlation, Coefficient of Concurrent Deviation, Correlation of a grouped data.
Today’s overwhelming number of techniques applicable to data analysis makes it extremely difficult to define the most beneficial approach while considering all the significant variables.
The analysis of variance has been studied from several approaches, the most common of which uses a linear model that relates the response to the treatments and blocks. Note that the model is linear in parameters but may be nonlinear across factor levels. Interpretation is easy when data is balanced across factors but much deeper understanding is needed for unbalanced data.
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means.Analysis of variance (ANOVA) is an analysis tool used in statistics that splits an observed aggregate variability found inside a data set into two parts: systematic factors and random factors. The systematic factors have a statistical influence on the given data set, while the random factors do not. Analysts use the ANOVA test to determine the influence that independent variables have on the dependent variable in a regression study.
Sir Ronald Fisher pioneered the development of ANOVA for analyzing results of agricultural experiments.1 Today, ANOVA is included in almost every statistical package, which makes it accessible to investigators in all experimental sciences. It is easy to input a data set and run a simple ANOVA, but it is challenging to choose the appropriate ANOVA for different experimental designs, to examine whether data adhere to the modeling assumptions, and to interpret the results correctly. The purpose of this report, together with the next 2 articles in the Statistical Primer for Cardiovascular Research series, is to enhance understanding of ANVOA and to promote its successful use in experimental cardiovascular research. My colleagues and I attempt to accomplish those goals through examples and explanation, while keeping within reason the burden of notation, technical jargon, and mathematical equations.
Classify data into Qualitative and Quantitative data.
Scales of Measurement in Statistics.
Nominal, Ordinal, Ratio and Interval
Prepare table or continuous frequency distribution.
students will be able to understand various measures of central tendency and also will be able to calculate mean median and mode for individual discrete and continuous series.
Brief description of the concepts related to correlation analysis. Problem Sums related to Karl Pearson's Correlation, Spearman's Rank Correlation, Coefficient of Concurrent Deviation, Correlation of a grouped data.
Today’s overwhelming number of techniques applicable to data analysis makes it extremely difficult to define the most beneficial approach while considering all the significant variables.
The analysis of variance has been studied from several approaches, the most common of which uses a linear model that relates the response to the treatments and blocks. Note that the model is linear in parameters but may be nonlinear across factor levels. Interpretation is easy when data is balanced across factors but much deeper understanding is needed for unbalanced data.
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures (such as the "variation" among and between groups) used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means.Analysis of variance (ANOVA) is an analysis tool used in statistics that splits an observed aggregate variability found inside a data set into two parts: systematic factors and random factors. The systematic factors have a statistical influence on the given data set, while the random factors do not. Analysts use the ANOVA test to determine the influence that independent variables have on the dependent variable in a regression study.
Sir Ronald Fisher pioneered the development of ANOVA for analyzing results of agricultural experiments.1 Today, ANOVA is included in almost every statistical package, which makes it accessible to investigators in all experimental sciences. It is easy to input a data set and run a simple ANOVA, but it is challenging to choose the appropriate ANOVA for different experimental designs, to examine whether data adhere to the modeling assumptions, and to interpret the results correctly. The purpose of this report, together with the next 2 articles in the Statistical Primer for Cardiovascular Research series, is to enhance understanding of ANVOA and to promote its successful use in experimental cardiovascular research. My colleagues and I attempt to accomplish those goals through examples and explanation, while keeping within reason the burden of notation, technical jargon, and mathematical equations.
Classify data into Qualitative and Quantitative data.
Scales of Measurement in Statistics.
Nominal, Ordinal, Ratio and Interval
Prepare table or continuous frequency distribution.
This is a quick presentation on Cancer Biology, I apologise that the start is exactly the same as my previous presentation but this is delivered to a different group (and I don't believe in reinventing the wheel). Appologies if some of the slide look wrong on here but slideshare some times messes up on transparency.
STANDARD DEVIATION (2018) (STATISTICS)sumanmathews
THIS IS A QUICK AND EASY METHOD TO LEARN STANDARD DEVIATION FOR DISCRETE AND GROUPED FREQUENCY DISTRIBUTION.
IT GIVES A STEP BY STEP, SIMPLE EXPLANATION OF PROBLEMS WITH FORMULAE.
SO WATCH THE ENTIRE VIDEO TODAY.
Please Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Chapter 7: Estimating Parameters and Determining Sample Sizes
7.2: Estimating a Population Mean
Unit-I Measures of Dispersion- Biostatistics - Ravinandan A P.pdfRavinandan A P
Biostatistics, Unit-I, Measures of Dispersion, Dispersion
Range
variation of mean
standard deviation
Variance
coefficient of variation
standard error of the mean
Measures of Central tendency-bio-statistics
Biostatistics and research methodology
Mean
Median
Mode
Mean- Arithmetic mean
weighted mean
harmonic mean
geometric mean
individual series
discrete series
continuous series
Relation between mean, median and mode
Statistical average
mathematical average
positional average
Merits and demerits of mean, median and mode
statistics
Bachelor of Pharmacy
8th Semester
Biostatistics
It provides hopefull concepts and solutions for degradation and recycling of other degradation- resistant plastic materials.
It provides hopefull concepts and solutions for degradation and recycling of other degradation- resistant plastic materials.
It provides hopefull concepts and solutions for degradation and recycling of other degradation- resistant plastic materials.
RNA interference (RNAi) is a biological process in which RNA molecules inhibit gene expression, typically by causing the destruction of specific mRNA molecules. Historically, it was known by other names, including co-suppression, post-transcriptional gene silencing (PTGS), and quelling.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
"Protectable subject matters, Protection in biotechnology, Protection of othe...
Standard deviation
1. Seminar on
Standard Deviation
Presented by:
Jiban Ku. Singh
M. Sc Part-I (2015-16)
P. G. DEPARTMENT OF BOTANY
BERHAMPUR UNIVERSITY
BHANJA BIHAR, BERHAMPUR- 760007
GANJAM, ODISHA, INDIA
E-mail- jibansingh9@gmail.com
3. Standard Deviation
• While looking at the earlier measures of dispersion all of them suffer
from one or the other demerit i.e.
• Range –it suffer from a serious drawback considers only 2 values and
neglects all the other values of the series.
• Quartile deviation considers only 50% of the item and ignores the
other 50% of items in the series.
• Mean deviation no doubt an improved measure but ignores negative
signs without any basis.
3
4. Standard Deviation
• The concept of standard deviation was first introduced by Karl Pearson in
1893.
• Karl Pearson after observing all these things has given us a more scientific
formula for calculating or measuring dispersion. While calculating SD we
take deviations of individual observations from their AM and then
each squares. The sum of the squares is divided by the Total number of
observations. The square root of this sum is knows as standard
deviation.
• The standard deviation is the most useful and the most popular measure of
dispersion.
• It is always calculated from the arithmetic mean, median and mode is not
considered.
4
5. Definition:
• Standard Deviation is the positive square root of the average of squared
deviation taken from arithmetic mean.
• The standard deviation is represented by the Greek letter 𝝈(sigma).
• Formula.
• Standard deviation = 𝜎=
𝑥− 𝑥 2
𝑛
7. CALCULATION OF STANDARD DEVIATION-
INDIVIDUAL OBSERVATION
Two Methods:-
By taking deviation of the items from the actual mean.
By taking deviation of the items from an assumed mean.
8. CASE-I. When the deviation are taken from the actual mean.
DIRECT METHOD
Standard deviation = 𝜎=
𝑥 𝑖 − 𝑥 2
𝑛
or =
𝑑2
𝑛
𝑤ℎ𝑒𝑟𝑒 𝑑 = 𝑥𝑖 − 𝑥
𝑥𝑖=value of the variable of observation,
𝑥= arithmetic mean
𝑛= total number of observations.
9. Example : Find the mean respiration rate per minute and its standard deviation when in 4
cases the rate was found to be : 16, 13, 17 and 22.
• Solution:
Here Mean = 𝒙 =
𝒙
𝒏
=
𝟏𝟔+𝟏𝟑+𝟏𝟕+𝟐𝟐
𝟒
=
𝟔𝟖
𝟒
= 𝟏𝟕
𝑥
16
13
17
22
𝒙 = 𝟔𝟖
Standard deviation = 𝜎=
𝑥 𝑖 − 𝑥 2
𝑛
=
𝑑2
𝑛
=
42
4
= 3.2
-1
-4
0
5
1
16
0
25
𝒅 𝟐
= 𝟒𝟐
10. Short-Cut Method
Standard deviation = 𝜎=
𝑑2
𝑛
−
𝑑
𝑛
2
𝑤ℎ𝑒𝑟𝑒 𝑑 = 𝑥 − 𝐴, 𝐴 = 𝑎𝑠𝑠𝑢𝑚𝑒𝑑 𝑚𝑒𝑎𝑛,
𝑛 = 𝑡𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑜𝑏𝑠𝑒𝑟𝑣𝑎𝑡𝑖𝑜𝑛.
CASE-II. When the deviation are taken from the Assumed mean.
12. CALCULATION OF STANDARD DEVIATION- DISCERETE SERIES OR
GROUPED DATA
Three Methods
a)Actual Mean Method or Direct Method
b)Assumed Mean Method or Short-cut Method
c)Step Deviation Method
13. a) Actual Mean Method or Direct Method
• The S.D. for the discrete series is given by the formula.
𝜎=
𝑓 𝑥 − 𝑥 2
𝑛
Where 𝑥 is the arithmetic mean,
𝑥 is the size of items,
𝑓 is the corresponding frequency
and 𝑛 = 𝑓
14. b) Assumed Mean Method or Short-cut Method
Standard deviation=𝜎 =
𝑓𝑑2
𝑛
− 𝑓𝑑
𝑛
2
Where 𝐴 is the assumed mean,
𝑑 = 𝑥 − 𝐴
𝑓 is the corresponding frequency
and 𝑛 = 𝑓
16. c) Step Deviation Method
• We divide the deviation by a common class interval and use the
following formula
Standard deviation=𝜎 =
𝑓𝑑2
𝑛
− 𝑓𝑑
𝑛
2
× 𝑖
Where 𝑖 = common class interval,
𝑑 = 𝒙−𝑨
𝒊 ,
𝐴 = is assumed mean
𝑓 = f is the respective frequency.
18. S.D. of Continues Series can be calculated by any one of the methods discussed
for discrete frequency distribution But Step Deviation Method is mostly used.
Standard deviation=𝜎 =
𝑓𝑑2
𝑛
− 𝑓𝑑
𝑛
2
× 𝑖
Where𝑖 = common class interval,
𝑑 = 𝒙−𝑨
𝒊
,
𝐴 = is assumed mean
𝑓 = f is the respective frequency.
20. It is possible to compute combined mean of two or more than two groups.
Combined Standard Deviation is denoted by 𝝈 𝟏𝟐
𝝈 𝟏𝟐=
𝑛1 𝜎1
2+𝑛2 𝜎2
2+𝑛1 𝑑1
2
+𝑛2 𝑑2
2
𝑛1+𝑛2
Where𝜎12 =combined standard deviation ,
𝜎1 = 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑓𝑖𝑟𝑠𝑡 𝑔𝑟𝑜𝑢𝑝𝜎2
= 𝑠𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 𝑜𝑓 𝑠𝑒𝑐𝑜𝑛𝑑 𝑔𝑟𝑜𝑢𝑝𝑑1 = 𝑥1 − 𝑥12
𝑑2 = 𝑥2 − 𝑥12
21. a) Combined S.D. 𝝈 𝟏𝟐=
𝑛1 𝜎1
2+𝑛2 𝜎2
2+𝑛1 𝑑1
2
+𝑛2 𝑑2
2
𝑛1+𝑛2
combined Mean 𝑥12=
𝑛1 𝑥1+𝑛2 𝑥2
𝑛1+𝑛2
=
100 60 +50 45
100+50
=
6000+2250
150
= 55
𝑛1 = 100, 𝜎1
2 = 9, 𝑛2 = 50, 𝜎2
2 = 4,
𝑑1 = 𝑥1 − 𝑥12 = 60 − 55 = 5
𝑑2 = 𝑥2 − 𝑥12 = 45 − 55 = 10
The following are some of the particulars of the
distribution of weight of boys and girls in a class:
a) Find the standard deviation of the combined data
b) which of the two distributions is more variable
Boys Girls
Numbers 100 50
Mean weight 60 kg 45 kg
Variance(𝜎2
) 9 4
𝝈 𝟏𝟐=
100(9)+50(4)+100 5 2+50 10 2
100+50
=
900+200+2500+5000
150
= =
8600
150
= 7.57
b)
C.V (Boys)=
𝜎
𝑥1
× 100 =
3
60
× 100 = 5.00
C.V (Girls)=
𝜎
𝑥2
× 100 =
2
45
× 100 = 4.44
22. MERITS OF STANDARD DEVIATION
Very popular scientific measure of dispersion
From SD we can calculate Skewness, Correlation etc
It considers all the items of the series
The squaring of deviations make them positive and the
difficulty about algebraic signs which was expressed in case of
mean deviation is not found here.
22
23. DEMERITS OF STANDARD DEVIATION
• Calculation is difficult not as easier as Range and QD
• It always depends on AM
• Extreme items gain great importance
The formula of SD is =
𝑑2
𝑛
Problem: Calculate Standard Deviation of the following series
X – 40, 44, 54, 60, 62, 64, 70, 80, 90, 96
23
24. USES OF STANDARD DEVIATION
It is widely used in biological studies .
It is used in fitting a normal curve to a frequency distribution.
It is most widely used measure of dispersion.
24