This document discusses linear correlation between two variables. It introduces scatter diagrams and correlation coefficients as ways to assess the strength and direction of linear relationships between variables. The Pearson correlation coefficient and Spearman rank correlation coefficient are presented as common measures of linear correlation, along with hypothesis testing procedures to determine if observed correlations are statistically significant. Examples are provided to demonstrate calculating and interpreting correlation coefficients.
Correlation- an introduction and application of spearman rank correlation by...Gunjan Verma
this presentation contains the types of correlation, uses, limitations, introduction to spearman rank correlation, and its application. a numerical is also given in the presentation
Correlation- an introduction and application of spearman rank correlation by...Gunjan Verma
this presentation contains the types of correlation, uses, limitations, introduction to spearman rank correlation, and its application. a numerical is also given in the presentation
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
Correlation is utilized to test connections between quantitative factors or absolute factors. As such, it's a proportion of how things are connected. The investigation of how factors are associated is called correlation.
This is about the correlation analysis in statistics. It covers types, importance,Scatter diagram method
Karl pearson correlation coefficient
Spearman rank correlation coefficient
Partial correlation. It was the introduction of relation with the third variables, called multivariate analysis. To find out the relationship between two variables, we need to control one variable. Either the relation will be the same or decrease or increase. Three cases are illustrated to explain the applicability of partial correlation.
Statistical inference: Statistical Power, ANOVA, and Post Hoc testsEugene Yan Ziyou
This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 4 (statistical power, ANOVA, and post hoc tests).
The data and R script for the lab session can be found here: https://github.com/eugeneyan/Statistical-Inference
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
Correlation is utilized to test connections between quantitative factors or absolute factors. As such, it's a proportion of how things are connected. The investigation of how factors are associated is called correlation.
This is about the correlation analysis in statistics. It covers types, importance,Scatter diagram method
Karl pearson correlation coefficient
Spearman rank correlation coefficient
Partial correlation. It was the introduction of relation with the third variables, called multivariate analysis. To find out the relationship between two variables, we need to control one variable. Either the relation will be the same or decrease or increase. Three cases are illustrated to explain the applicability of partial correlation.
Statistical inference: Statistical Power, ANOVA, and Post Hoc testsEugene Yan Ziyou
This deck was used in the IDA facilitation of the John Hopkins' Data Science Specialization course for Statistical Inference. It covers the topics in week 4 (statistical power, ANOVA, and post hoc tests).
The data and R script for the lab session can be found here: https://github.com/eugeneyan/Statistical-Inference
Correlation Analysis
Correlation Analysis
Correlation measures the relationship between two quantitative variables
Linear correlation measures if the ordered paired data follow a straight-line relationship between quantitative variables.
The correlation coefficient (r) computed from the sample data measures the strength and the direction of a linear relationship between two variables.
The range of correlation coefficient is -1 to +1. When there is no linear relationship between the two variables or only a weak relationship, the value of correlation coefficient will be close to 0.
Things to Remember
Correlation coefficient cutoff points
+0.30 to + 0.49 weak positive association.
+ 0.5 to +0.69 medium positive association.
+0.7to + 1.0 strong positive association.
- 0.5 to - 0.69 medium negative association.
- 0.7 to - 1.0 strong negative association.
- 0.30 to - 0.49 weak negative association.
0 to - 0.29 little or no association.
0 to + 0.29 little or no association.
Relationships of Linear Correlation
As x increases, no definite shift in y: no correlation.
As x increase, a definite shift in y: correlation.
Positive correlation: x increases, y increases.
Negative correlation: x increases, y decreases.
If the points exhibit some other nonlinear pattern: no linear relationship.
Example: No correlation.
As x increases, there is no definite shift in y.
Example: Positive/direct correlation.
As x increases, y also increases.
Example: Negative/indirect/inverse correlation.
As x increases, y decreases.
Coefficient of linear correlation: r, measures the strength of the linear relationship between two variables.
Pearson Correlation formula:
Note:
r = +1: perfect positive correlation
r = -1 : perfect negative correlation
Use the calculated value of the coefficient of linear correlation, r, to make an inference about the population correlation coefficient r.
Example 1: Is there a relationship between age of the children and their score on the Child Medical Fear Scale (CMFS), using the data shown in Table 1?
H0: There is no significant relationship between the age of the children and their score on the CMFS
Or
H0: r = 0
IDAge (x)CMFS (y)183129253940410275113569297825893498441011191172812647136421483715935161216171512181323191026201036
Table 1
Scattergram (Scatterplot)
Age (x) = Independent variable, CMFS (y)= Dependent variable
Correlation Coefficient
The Results:
a. Decision: Reject H0.
b. Conclusion: There is evidence to suggest that there is a significant linear relationship between the age of the child and the score on the CMFS.
Answers the question of whether there is a significant linear relationship or not
Simple Linear Regression Analysis
Linear Regression Analysis
Linear Regression analysis finds the equation of the line that predicts the dependent variable based on the independent variable.
210 190 165 150 130 115 100 90 70 60 40 25 35 6.
Assessment 2 ContextIn many data analyses, it is desirable.docxfestockton
Assessment 2 Context
In many data analyses, it is desirable to compute a coefficient of association. Coefficients of association are quantitative measures of the amount of relationship between two variables. Ultimately, most techniques can be reduced to a coefficient of association and expressed as the amount of relationship between the variables in the analysis. There are many types of coefficients of association. They express the mathematical association in different ways, usually based on assumptions about the data. The most common coefficient of association you will encounter is the Pearson product-moment correlation coefficient (symbolized as the italicized r), and it is the only coefficient of association that can safely be referred to as simply the "correlation coefficient". It is common enough so that if no other information is provided, it is reasonable to assume that is what is meant.
Correlation coefficients are numbers that give information about the strength of relationship between two variables, such as two different test scores from a sample of participants. The coefficient ranges from -1 through +1. Coefficients between 0 and +1 indicate a positive relationship between the two scores, such as high scores on one test tending to come from people with high scores on the second. The other possible relationship, which is every bit as useful, is a negative correlation between -1 and 0. A negative correlation possesses no less predictive power between the two scores. The difference is that high scores on one measure are associated with low scores on the other.
An example of the kinds of measures that might correlate negatively is absences and grades. People with higher absences will be expected to have lower grades. When a correlation is said to be significant, it can be shown that the correlation is significantly different form zero in the population. A correlation of zero means no relationship between variables. A correlation other than zero means the variables are related. As the coefficient gets further from zero (toward +1 or -1), the relationship becomes stronger.Interpreting Correlation: Magnitude and Sign
Interpreting a Pearson's correlation coefficient (rXY) requires an understanding of two concepts:
· Magnitude.
· Sign (+/-).
The magnitude refers to the strength of the linear relationship between Variable X and Variable
The rXY ranges in values from -1.00 to +1.00. To determine magnitude, ignore the sign of the correlation, and the absolute value of rXY indicates the extent to which Variable X and Variable Y are linearly related. For correlations close to 0, there is no linear relationship. As the correlation approaches either -1.00 or +1.00, the magnitude of the correlation increases. Therefore, for example, the magnitude of r = -.65 is greater than the magnitude of r = +.25 (|.65| > |.25|).
In contrast to magnitude, the sign of a non-zero correlation is either negative or positive.
These labels are not interpreted ...
Assessment 2 ContextIn many data analyses, it is desirable.docxgalerussel59292
Assessment 2 Context
In many data analyses, it is desirable to compute a coefficient of association. Coefficients of association are quantitative measures of the amount of relationship between two variables. Ultimately, most techniques can be reduced to a coefficient of association and expressed as the amount of relationship between the variables in the analysis. There are many types of coefficients of association. They express the mathematical association in different ways, usually based on assumptions about the data. The most common coefficient of association you will encounter is the Pearson product-moment correlation coefficient (symbolized as the italicized r), and it is the only coefficient of association that can safely be referred to as simply the "correlation coefficient". It is common enough so that if no other information is provided, it is reasonable to assume that is what is meant.
Correlation coefficients are numbers that give information about the strength of relationship between two variables, such as two different test scores from a sample of participants. The coefficient ranges from -1 through +1. Coefficients between 0 and +1 indicate a positive relationship between the two scores, such as high scores on one test tending to come from people with high scores on the second. The other possible relationship, which is every bit as useful, is a negative correlation between -1 and 0. A negative correlation possesses no less predictive power between the two scores. The difference is that high scores on one measure are associated with low scores on the other.
An example of the kinds of measures that might correlate negatively is absences and grades. People with higher absences will be expected to have lower grades. When a correlation is said to be significant, it can be shown that the correlation is significantly different form zero in the population. A correlation of zero means no relationship between variables. A correlation other than zero means the variables are related. As the coefficient gets further from zero (toward +1 or -1), the relationship becomes stronger.Interpreting Correlation: Magnitude and Sign
Interpreting a Pearson's correlation coefficient (rXY) requires an understanding of two concepts:
· Magnitude.
· Sign (+/-).
The magnitude refers to the strength of the linear relationship between Variable X and Variable
The rXY ranges in values from -1.00 to +1.00. To determine magnitude, ignore the sign of the correlation, and the absolute value of rXY indicates the extent to which Variable X and Variable Y are linearly related. For correlations close to 0, there is no linear relationship. As the correlation approaches either -1.00 or +1.00, the magnitude of the correlation increases. Therefore, for example, the magnitude of r = -.65 is greater than the magnitude of r = +.25 (|.65| > |.25|).
In contrast to magnitude, the sign of a non-zero correlation is either negative or positive.
These labels are not interpreted .
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
Affordable Stationery Printing Services in Jaipur | Navpack n PrintNavpack & Print
Looking for professional printing services in Jaipur? Navpack n Print offers high-quality and affordable stationery printing for all your business needs. Stand out with custom stationery designs and fast turnaround times. Contact us today for a quote!
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
Premium MEAN Stack Development Solutions for Modern BusinessesSynapseIndia
Stay ahead of the curve with our premium MEAN Stack Development Solutions. Our expert developers utilize MongoDB, Express.js, AngularJS, and Node.js to create modern and responsive web applications. Trust us for cutting-edge solutions that drive your business growth and success.
Know more: https://www.synapseindia.com/technology/mean-stack-development-company.html
Unveiling the Secrets How Does Generative AI Work.pdfSam H
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
As a business owner in Delaware, staying on top of your tax obligations is paramount, especially with the annual deadline for Delaware Franchise Tax looming on March 1. One such obligation is the annual Delaware Franchise Tax, which serves as a crucial requirement for maintaining your company’s legal standing within the state. While the prospect of handling tax matters may seem daunting, rest assured that the process can be straightforward with the right guidance. In this comprehensive guide, we’ll walk you through the steps of filing your Delaware Franchise Tax and provide insights to help you navigate the process effectively.
Accpac to QuickBooks Conversion Navigating the Transition with Online Account...PaulBryant58
This article provides a comprehensive guide on how to
effectively manage the convert Accpac to QuickBooks , with a particular focus on utilizing online accounting services to streamline the process.
Business Valuation Principles for EntrepreneursBen Wann
This insightful presentation is designed to equip entrepreneurs with the essential knowledge and tools needed to accurately value their businesses. Understanding business valuation is crucial for making informed decisions, whether you're seeking investment, planning to sell, or simply want to gauge your company's worth.
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
Grote partijen zijn al een tijdje onderweg met retail media. Ondertussen worden in dit domein ook de kansen zichtbaar voor andere spelers in de markt. Maar met die kansen ontstaan ook vragen: Zelf retail media worden of erop adverteren? In welke fase van de funnel past het en hoe integreer je het in een mediaplan? Wat is nu precies het verschil met marketplaces en Programmatic ads? In dit half uur beslechten we de dilemma's en krijg je antwoorden op wanneer het voor jou tijd is om de volgende stap te zetten.
Explore our most comprehensive guide on lookback analysis at SafePaaS, covering access governance and how it can transform modern ERP audits. Browse now!
12. A measurement of linear relationship: 1) Whether there is a correlation If the correlation coefficient is 0 or not big enough -- no correlation 2) If correlation coefficient is big enough The direction of correlation? -- positive or negative The strength of correlation? high or not? -- Is the absolute value big enough? Complete correlation : +1 or -1,
13. Example 7.3 Calculate the correlation coefficient between the heights of father and son.
14.
15.
16. Question : If r =0.90, can you claim the two variables are correlated each other? Table 8 Critical values for r
17.
18.
19.
20. Example 7.5 After getting , please find out a 95% confidence interval for population correlation coefficient .
21.
22.
23. Example 7.6 An etiology study on liver cancer has collected data on liver-cancer-specific death rate and the relative content of aflatoxin in certain food for 10 Counties. Putting the ranks into the formula of Spearman’s correlation coefficient
24. Table 9 Critical value for Spearman’s rank correlation coefficient 7.4.2 Hypothesis test for (1) Checking a special table (Table 9) P <0.02 and it is significant