Correlation Analysis In Excel: Correlation and Causation With Example
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- Опубліковано 19 лип 2024
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Correlation Analysis In Excel Tutorial, Correlation and Causation With Example, Correlation Coefficient (Pearson Coefficient):
Hello Friends,
Correlation Analysis is one of the most commonly used tools to identify the strength of the relationship between 02 or more continuous variables. But, this should not be confused with Causation. I have explained it in detail with the help of examples.
This video consists of the following topics:
✅ Introduction to Excel Data Analysis (Data Analysis In Excel)
✅ What is Correlation and when to use it?
✅ Types of Correlation and Graphical representation of it
✅ Correlation and Causation
✅ Pearson Correlation Coefficient
✅ Correlation Coefficient Value and its interpretation
✅ Conduct Correlation Analysis In Excel With Example Using Data Analysis
✅ Interpretation of results from Correlation Analysis
✅ Calculate Correlation Analysis by using Excel Formulae
✅ Correlation and Causation With Example by conducting analysis
✅ Interpretation of results from Correlation and Causation
✅ Learn Lean Six Sigma and Minitab Most Effectively and Practically
I am sure you will like it.
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0:00 Introduction to Excel Data Analysis (Data Analysis In Excel)
0:41 What is Correlation and when to use it?
0:59 Types of Correlation and Graphical representation of it
2:25 Correlation and Causation
4:30 Pearson Correlation Coefficient
5:47 Correlation Coefficient Value and its interpretation
6:56 Conduct Correlation Analysis In Excel With Example Using Data Analysis
8:06 Interpretation of results from Correlation Analysis
9:19 Calculate Correlation Analysis by using Excel Formulae
10:39 Correlation and Causation With Example by conducting analysis
11:35 Interpretation of results from Correlation and Causation
12:53 Learn Lean Six Sigma and Minitab Most Effectively and Practically
Thank you for watching...🙏😊
#correlation #correlationanalysis #correlationcoefficient #causation #exceldataanalysis #dataanalysisexcel #sixsigmaexcel #analysistools #leansixsigma #sixsigma #successfulcareerhub #learnandapply #statistics #excel
Very very impressive explanation
Thank you so much for your valuable comments and appreciation 🙏🙏☺
Very very good video...thank alot
Thank you so much for your valuable comments and appreciation! 🙏😊
Really superb explanation
Thank you so much for your valuable comments and appreciation 🙏🙏😊
Sir, kindly explain and confirm me that...The word "Effect" is use only in experimental researcher? Can I use the word as "EFFECT OF" in correlational research ? I confused..kindly dee that.
Yes, you can use either of that. It conveys the same meaning. I appreciate your learning approach to such a deeper level.🙏🙏
Thank you for the video. But still i did not get how ti see causation vs correlation from the excel data. Both coefficients are mire then 0,9. Just logically or there some signs that data shows us?
Thank you for your valuable comments and appreciation.
Causation or correlation, you need subject matter expertise to understand that. If there is a cause-and-effect relationship, then it's Causation. Otherwise, it's a correlation.
@@learnandapply but in your example both sun burn and temperature shows more then 0,9 correlation. If put logic aside, use just excel result, how we know what is the cause?
correlation and causation, it is not decided based on the value. Based on the type of relationship.
Please revisit the video. You need cause and effect relationship for Causation.
Dear researchers, I have MSR (meta cognitive self regulation) learning strategy as independent variable while Students' Score (Students'GPA) is my dependent variable. MSR is on five point Likert scale while for Students'GPA each student put his own GPA on the questionnaire in form of digits like 2 , 2.1, 2.7, 2.3, 3, 3.6, 4 etc.
The students score is in random form.
Each student put his own score whatever he got in the previous semester. Now my question is which kind of correlation should I use? Can I go for the Pearson correlation? How to handle with the Students'GPA variable? The sample size is 300 students which means that I have 300 Students'GPAs. It's a confusing whether I should consider the Students'GPA as ordinal, interval or ratio variable? Which kind of correlation should I go for?
Please, guide.
Thank you for the detailed description of the scenario. You need to use Logistic Regression Analysis in this case.