this ppt gives you adequate information about Karl Pearsonscoefficient correlation and its calculation. its the widely used to calculate a relationship between two variables. The correlation shows a specific value of the degree of a linear relationship between the X and Y variables. it is also called as The Karl Pearson‘s product-moment correlation coefficient. the value of r is alwys lies between -1 to +1. + 0.1 shows Lower degree of +ve correlation, +0.8 shows Higher degree of +ve correlation.-0.1 shows Lower degree of -ve correlation. -0.8 shows Higher degree of -ve correlation.
this ppt gives you adequate information about Karl Pearsonscoefficient correlation and its calculation. its the widely used to calculate a relationship between two variables. The correlation shows a specific value of the degree of a linear relationship between the X and Y variables. it is also called as The Karl Pearson‘s product-moment correlation coefficient. the value of r is alwys lies between -1 to +1. + 0.1 shows Lower degree of +ve correlation, +0.8 shows Higher degree of +ve correlation.-0.1 shows Lower degree of -ve correlation. -0.8 shows Higher degree of -ve correlation.
HOW IS IT USEFUL IN FIELD OF FORENSIC SCIENCE AND IN THIS I HAVE SHOWN THE TYPES OF CORRELATION, SIGNIFICANCE , METHODS AND KARL PEARSON'S METHOD OF CORRELATION
This presentation contains information about Mann Whitney U test, what is it, when to use it and how to use it. I have also put an example so that it may help you to easily understand it.
Measure of dispersion has two types Absolute measure and Graphical measure. There are other different types in there.
In this slide the discussed points are:
1. Dispersion & it's types
2. Definition
3. Use
4. Merits
5. Demerits
6. Formula & math
7. Graph and pictures
8. Real life application.
The Spearman’s Rank Correlation Coefficient is the non-parametric statistical measure used to study the strength of association between the two ranked variables. This method is applied to the ordinal set of numbers, which can be arranged in order, i.e. one after the other so that ranks can be given to each. This presentation slides explains the procedure to find out the Rank Difference correlation and its applications.
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.
HOW IS IT USEFUL IN FIELD OF FORENSIC SCIENCE AND IN THIS I HAVE SHOWN THE TYPES OF CORRELATION, SIGNIFICANCE , METHODS AND KARL PEARSON'S METHOD OF CORRELATION
This presentation contains information about Mann Whitney U test, what is it, when to use it and how to use it. I have also put an example so that it may help you to easily understand it.
Measure of dispersion has two types Absolute measure and Graphical measure. There are other different types in there.
In this slide the discussed points are:
1. Dispersion & it's types
2. Definition
3. Use
4. Merits
5. Demerits
6. Formula & math
7. Graph and pictures
8. Real life application.
The Spearman’s Rank Correlation Coefficient is the non-parametric statistical measure used to study the strength of association between the two ranked variables. This method is applied to the ordinal set of numbers, which can be arranged in order, i.e. one after the other so that ranks can be given to each. This presentation slides explains the procedure to find out the Rank Difference correlation and its applications.
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.
To get a copy of the slides for free Email me at: japhethmuthama@gmail.com
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It is most useful for the students of BBA for the subject of "Data Analysis and Modeling"/
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This presentation covered the following topics:
1. Definition of Correlation and Regression
2. Meaning of Correlation and Regression
3. Types of Correlation and Regression
4. Karl Pearson's methods of correlation
5. Bivariate Grouped data method
6. Spearman's Rank correlation Method
7. Scattered diagram method
8. Interpretation of correlation coefficient
9. Lines of Regression
10. regression Equations
11. Difference between correlation and regression
12. Related examples
Building and Other Construction Workers Act, 1996TRIPTI DUBEY
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Tripti Dubey
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1. KARL PEARSON COEFFICIENT OF
CORRELATION
DEPARTMENT OF SOCIAL WORK
INSTIUTE OF SOCIAL SCIENCES
DR. BHIMRAO AMBEDKAR UNIVERSITY, AGRA
PRESENTED BY: TRIPTI DUBEY
MSW (III Sem) Roll No. 38
2. CONTENTS
Coefficient of correlation
Types of correlation
Karl Pearson Coefficient of correlation
Methods used to calculate Karl Pearson Coefficient of
correlation
Actual mean method
Assumed mean method
Step deviation method
Conclusion
3. Correlation is generally applied in statistics and it is a statistical
tool to calculate and analyze the degree of relationship between two
variables.
The correlation analysis deals with the association between X and Y
variables.
It was developed by Francis Galton in 1885.
Correlation is represented by “r”.
INTRODUCTION
4. TYPES OF CORRELATION
TYPES OF
CORRELATION
POSITIVE
CORRELATION
PERFECT POSITIVE
CORRELATION
LIMITED POSITIVE
CORRELATION
i) High Degree
ii) Moderate Degree
iii) Low Degree
ZERO
CORRELATION
NEGATIVE
CORRELATION
PERFECT NEGATIVE
CORRELATION
LIMITED NEGATIVE
CORRELATION
i) High Degree
ii) Moderate Degree
iii) Low Degree
5. If when the first variable increases or decreases the other also increases or decreases
respectively. This relationship is said to be positive correlation.
Ex- Height and weight
Positive correlation is divided into two categories-
1. Perfect Positive correlation: It is denoted by +1.
2. Limited Positive correlation:
i) Low Degree of limited positive correlation-
ii) Moderate Degree of limited positive correlation-
iii) High Degree of limited positive correlation-
POSITIVE CORRELATION
r = +1
0 < r < 0.25
0.25 ≤ r < 0.75
0.75 ≤ r < +1
6. If when the first variable increases or decreases, the other respectively decreases or
increases respectively. This relationship is said to be negative correlation.
Ex- Price and Quantity demanded
Negative correlation is divided into two categories-
1. Perfect Negative correlation: It is denoted by -1.
2. Limited Negative correlation:
i) Low Degree of limited negative correlation-
ii) Moderate Degree of limited negative correlation-
iii) High Degree of limited negative correlation-
NEGATIVE CORRELATION
r = -1
0 > r > -1
-0.25 ≥ r > -0.75
-0.75 ≥ r > -1
7. If there exists no relationship between two sets of measures or variables. This
relationship is said to be zero correlation.
Ex- Intelligence and Height
ZERO CORRELATION
8. This was introduced by Karl Pearson (1867-1936).
Pearson’s Correlation coefficient method is quantitative and
offer numerical value to establish the intensity of the linear
relationship between two variables.
It is the most potent and extensively used method to measure the level
of correlation.
This method is also known as Product Moment Correlation Coefficient.
KARL PEARSON COEFFICIENT OF
CORRELATION
9. Actual Mean Method
Assumed Mean Method
Step- Deviation Method
METHODS USED TO CALCULATE
PEARSON CORRELATION
METHODS USED
TO CALCULATE
PEARSON
CORRELATION
10. ACTUAL MEAN METHOD
∑dx. dy
∑d2x d2y
r= Karl Pearson Coefficient of correlation
dx= deviation from mean of x series
dy= deviation from mean of y series
∑x/n
∑y/n
n= number of items
11. ASSUMED MEAN METHOD
where, r= Karl Pearson Coefficient of correlation
dx= deviation of x series from assumed mean
dy= deviation of y series from assumed mean
N= number of observations
STEP DEVIATION METHOD
where, r= Karl Pearson Coefficient of correlation
n= number of observations
12. MERITS AND DEMERITS OF PEARSON
CORRELATION
MERITS DEMERITS
It gives a precise and quantitative figure
which can be interpreted meaningfully.
This method assumes that there is a linear
relationship between the variables unless
study the fact whether it exist or not.
It helps in establishing the value of the
dependent variable from the value of
independent variable.
The value of the coefficient is unduly
affected by extreme items.
13. Correlation is used to assess the strength and direction of linear relationship
between pair of variables.
Pearson correlation should be used only when there is a linear relationship
between pair of variables.
It can be positive or negative or zero correlation.
There are three methods to calculate Pearson correlation and it is denoted by
“r”.
CONCLUSION
