1. Correlation measures the strength and direction of association between two variables. It ranges from -1 to 1, where -1 is perfect negative correlation, 0 is no correlation, and 1 is perfect positive correlation.
2. There are different types of correlation based on the direction, number of variables, and constancy of relationships. Common types include positive, negative, simple, multiple, and partial correlation.
3. Correlation coefficients like Pearson's r and Spearman's rho are used to calculate correlation. Pearson's r assumes linear relationships while Spearman's rho assumes monotonic relationships between variables.
Unit-I, BP801T. BIOSTATISITCS AND RESEARCH METHODOLOGY (Theory)
Correlation: Definition, Karl Pearson’s coefficient of correlation, Multiple correlations -
Pharmaceuticals examples.
Correlation: is there a relationship between 2
variables.
It is most useful for the students of BBA for the subject of "Data Analysis and Modeling"/
It has covered the content of chapter- Data regression Model
Visit for more on www.ramkumarshah.com.np/
Unit-I, BP801T. BIOSTATISITCS AND RESEARCH METHODOLOGY (Theory)
Correlation: Definition, Karl Pearson’s coefficient of correlation, Multiple correlations -
Pharmaceuticals examples.
Correlation: is there a relationship between 2
variables.
It is most useful for the students of BBA for the subject of "Data Analysis and Modeling"/
It has covered the content of chapter- Data regression Model
Visit for more on www.ramkumarshah.com.np/
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
Basavarajeeyam is an important text for ayurvedic physician belonging to andhra pradehs. It is a popular compendium in various parts of our country as well as in andhra pradesh. The content of the text was presented in sanskrit and telugu language (Bilingual). One of the most famous book in ayurvedic pharmaceutics and therapeutics. This book contains 25 chapters called as prakaranas. Many rasaoushadis were explained, pioneer of dhatu druti, nadi pareeksha, mutra pareeksha etc. Belongs to the period of 15-16 century. New diseases like upadamsha, phiranga rogas are explained.
Evaluation of antidepressant activity of clitoris ternatea in animals
correlation.pptx
1. UNIT : XVI
CORRELATION
Mrs.D. MelbaSahayaSweetyRN,RM
PhDNursing, MSc Nursing(PediatricNursing) B.ScNursing
Associate Professor
Departmentof PediatricNursing
EnamNursingCollege, Savar,
Bangladesh.
1
2. Correlationis a bi-variate analysis that measures the strength
of associationbetween two variables and the direction of the relationship. In
terms of the strengthof relationship, the value of thecorrelationcoefficientvaries
between+1 and -1. A value of ± 1 indicates a perfect degree of associationbetween
thetwo variables. As the correlationcoefficient valuegoes towards 0, the
relationshipbetween the two variables will be weaker. The direction of the
relationshipis indicatedby the signof the coefficient; a + sign indicates a positive
relationshipand a – sign indicates a negative relationship. 2
3. Correlation analysis deals with the association between two
or more variables.
- Simphson & Kafka.
Correlation analysis attemptsto determine the degree of relationship
between variables .
- Ya- Lun Chou
Correlation is an analysis of covariationbetween two or more variables.”
- A.M. Tuttle 3
4. Types of Correlation
Based on the direction
of change of variables
Based upon the number
of variables studied.
Based upon the
constancy of the ratio
of change between the
variables
Positive
Correlation
Negative
Correlation
Simple Correlation
Multiple Correlation
Partial Correlation
Linear
Correlation
Non- Linear
Correlation
Total Correlation 4
5. Positive Correlation
The movement of variable in the same direction is
known as positive or direct correlation. That is the value of
both the variable either increase together or decrease
simultaneously. Example: When income rises, so does
consumption and when income falls, consumption does too.
Perfect positive Correlation : +1
Strong Positive Correlation : +0.8 to +1
Medium Positive Correlation : + 0.5
Low Positive Correlation : + 0.2
5
6. The movement of variable in the Opposite
direction is referred to as negative or Inverse correlation.
That is the value of one variable raises the value of another
falls or vise versa. Example: Height above sea level and
temperature are an example of a negative association. It
gets colder as you climb the mountain (ascend in elevation)
(decrease in temperature).
Negative Correlation
Perfect Negative Correlation : - 1
Strong Negative Correlation : - 0.8 to - 1
Medium Negative Correlation : - 0.5
Low Negative Correlation : - 0.2
6
7. The study of only two variables is referred to as
simple correlation. The usage of fertilizers and Rice
production is an example of a simple connection, as rice
production is dependent on fertilizer use.
Simple Correlation
Multiple Correlation
Multiple correlations is defined as the study of three or
more variables at the same time. For instance the
relationship of fertilizers and pesticides on Rice production
. 7
8. In partial Correlation the relationship between
two are more variables are studied, Which consider
only one dependent and independent variable while keeping
all others constant For instance the relationship of Rice
production and fertilizers excluding the effect of rainfall,
Pesticides, and natural manures.
Partial Correlation
Total Correlation
The total correlation is found by taking all the variables.
8
9. The correlation is said
to be linear when the change in one
variable bears a constant ratio to
the change in the other.
Linear Correlation
Non- Linear Correlation
The change in one variable does not have a
constant ratio to the change in the other
variables, the correlation is non-linear. It is
other wise known as Curvilinear 9
10. • Degree of correlation can be known
by coefficient of correlation ( r )
Degree of Correlation Positive Negative
Perfect Correlation +1 -1
Strong high degree Correlation +0.9 -0.9
High degree Correlation +0.9 to + 0.75 - 0.9 to - 0.75
Moderate degree Correlation +0.25 to +0.75 +0.25 to + 0.75
Low degree correlation 0 to + 0.25 0 to - 0.25
No Correlation 0 0
10
12. Correlation Coefficient Level of Measurement
Karl Pearson’s product moment
correlation coefficient : ‘r’
Both Variable Interval
Spearman’s Rank correlation coefficient:
‘ ρ ’
Kendall rank correlation: ‘τ’
Both variable Ordinal
Phi, Contingency Coefficient. ‘rφ’ Both variable Nominal
Point-Biserial correlation. ‘ɼpb’ One variable Interval and another Dichotomous
Rank-Biserial correlation. ‘ɼrb’ One variable ordinal and another Nominal
Biserial correlation. ‘ɼb’ Interval data against ordinal data but ordinal data
with an underlying continuity but measured 12
13. Based on the distribution and type of
relationship, correlations can be interpreted in two
categories as follows.
A, Parametric Correlation
B, Non – Parametric Correlation
Description Parametric Correlation Non Parametric
Methods / Metrics
Karl’s
Pearson Correlation
Spearman
& Kendall’s correlation
(interchangeably used)
Assumption Must be interval or ratio
interval or ratio level
or ordinal 13
14. Description Parametric Correlation Non Parametric
Assumption
Variable forms linear relationship
(positive or negative)
Forms monotonic Relationship
Both Variables shall follow an
approximately normal distribution
Distribution free Variables may form
a skewed distribution or uniform
Characteristics
Both variables move at a constant ratio
& follow linear correlation
(i.e., y = mx, etc. )
Variables move at a constant ratio but
do not follow linear correlation; instead,
follow the exponential, curve, parabola,
etc. (i.e., y = ax+bx^2, a=b^2)
Impacted
by/Sensitive to:
Outliers must be handled as it greatly
affects the correlation
Robust and Mitigates the effect of
outliers
Range -1 ≤ r ≤ 1 -1 ≤ r ≤ 1
14
15. The Pearson correlation coefficient (also known
as the “product-moment correlation coefficient”) measures the linear
association between two variables. It always takes on a value between -1 and 1
ASSUMPTION:
• 1. Level of Measurement: The two variables should be measured at
the interval or ratio level.
• 2. Linear Relationship: There should exist a linear relationship between the two variables.
• 3. Normality: Both variables should be roughly normally distributed.
• 4. Related Pairs: Each observation in the dataset should have a pair of values.
• 5. No Outliers: There should be no extreme outliers in the dataset.
• 6.Homoscedascity : means ‘equal variances’. 15
16. Example : 1, Find the Correlation Coefficient of the
following data
x 9 8 7 6 5 4 3 2 1
y 15 16 14 13 11 12 10 8 9
16
18. Example : 2, The following gives the prize of a product and
corresponding to quality of supply calculate Karl Pearson
correlation coefficient
x 2 4 6 8 10
y 9 7 5 3 1
18
19. r =
X Y X2 Y2 XY
2 9 4 81 18
4 7 16 49 28
6 5 36 25 30
8 3 64 9 24
10 1 100 1 10
30 25 220 165 110
5(110) – (30) (25)
[5(220) – (30)2][5(165) – (25) 2]
√
r = 550 - 750
[1100 – 900][825 – 625]
√
r = -200
[200][200]
√
-200
40000
√
=
r = -200
200
r = -1 Hence it is perfect negative Correlation
19
20. Merits Demerits
This method indicates the presence or absence
of correlation between two variables and gives
the exact degree of their correlation.
It is more difficult to calculate than other
methods of calculations.
we can also ascertain the direction of the
correlation; positive, or negative.
It is much affected by the values of the
extreme items.
This method has many algebraic properties for
which the calculation of co-efficient of
correlation, and other related factors, are made
easy.
Cannot show cause and effect (what variables
control what)
It is based on a large number of assumptions
viz. linear relationship, cause and effect
relationship etc. which may not always hold
good. 20
21. This method of determining correlation was
propounded by Prof. Spearman in 1904.The Spearman's
Rank-order correlation is the nonparametric version of
the Pearson product-moment correlation.
Spearman’s correlation coefficient, (ρ, also signified by rs) measures the
strength and direction of association between two ranked variables.
A Spearman rank correlation is a number between -1 and +1 that
indicates to what extent 2 variables are monotonously related.
To understand Spearman’s correlation it is necessary to know what a
monotonic function is
21
22. A monotonic function is one that either never
increases or never decreases as its independent
variable increases.
Monotonically increasing - as the x variable increases the y
variable never decreases;
Monotonically decreasing - as the x variable increases the y
variable never increases;
Not monotonic - as the x variable increases the y variable
sometimes decreases and sometimes increases.
22
23. ASSUMPTION:
•Random sample (truly random sample representative of one population of interest)
•A monotonic association exists: between 2 variables.
•Variables are at least ordinal (ratio, interval, continuous (no nominal data like blood
type)
•Data contains paired samples; need variable x and y values, if there is a missing
value you need to delete the row
•Independence of observations: x observations in the x variable should be
independent from the y variable (no brother and sister) or (same subject with
multiple entries)
•Variable does not have to be sampled from a normal distribution 23
24. Example : 1 The rank obtained by 10
students in 2 classes are given below
find the spearman’s Rank correlation
coefficient ( Rank Given)
Clas
s A
1 2 5 4 1 9 10 6 8 3
Class
B
5 6 1 7 10 8 4 9 3 2
24
26. Example : 2 Find the spearman’s Rank
correlation coefficient for the following
value of x and y ( Rank Not Given)
x 50 60 50 60 80 50 80 40 70
y 30 60 40 50 60 30 70 50 60
26
29. ρ = 1-
22.5 + 0.5 + 0.5 + 2 + 0.5 + 0.5 + 2
720
ρ = 1-
28.5
720
ρ = 1- 171
720
ρ = 1- 0.2375
ρ = 0.7625
Hence there is high degree positive
correlation between x and y
6
6
29
30. • Example : 1, The correlation coefficient between height and weight of 20 girls is
0.2. Is there any relation between these two variables in the population?
Solution:
Hypothesis:
Null Hypothesis: There is no relation between the two variables (H0:ƍ = 0)
Alternative Hypothesis: There is a relation between the two variables (H0:ƍ ≠ 0)
T- Test Sample Correlation Coefficient
30
31. Test Statistics: n = 20, r = 0.2
t =
T- Test Sample Correlation Coefficient
0.2
1 – (0.2)
x √ 20-2
2
t =
0.2
1 – 0.04
√18
x
t =
0.2
0.96
x 4.24
√
√
√
t =
0.2
0.98
x 4.24
t = x 4.24
0.2040
t = 0.86496
31
32. T- Test Sample Correlation Coefficient
Degree of freedom = n-1
= 20-1
= 19
t(0.05,19) = 2.093
tcal < ttab
Thus we accept null hypothesis so There is no relation between the two
variables (H0:ƍ = 0) 32
33. Merits Demerits
It is easy to compute Only non-liner data can be computed.
It is easy to understand When data has higher values it is difficult to compute.
This method can be used to carry out correlation
analysis for variables that are not numerical. We
can study the relationships between qualitative
variables such as beauty, intelligence, honesty,
efficiency, and so on
A large computational time is required when the
number of pairs of values of two variables exceeds 30.
In such cases, assigning ranks to each of the numerical
values is a very time-consuming and tedious process.
Spearman’s formula is the only formula to be
used for finding the correlation coefficient if we
are dealing with qualitative characteristics which
cannot be measured quantitatively but can be
arranged serially.
This method cannot be applied to measure the
association between two variables whose distribution
is given in the form of a grouped frequency
distribution.
33