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Q: What are the three conditions for correlation?
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What are three types of correlations?

positive correlation-negative correlation and no correlation


What are the three conditions necessary for causation between variables?

The three conditions necessary for causation between variables are covariance (relationship between variables), temporal precedence (the cause must precede the effect in time), and elimination of plausible alternative explanations (other possible causes are ruled out).


What are the three different types of correlation?

The three different types of correlation are positive correlation (both variables move in the same direction), negative correlation (variables move in opposite directions), and no correlation (variables show no relationship).


What is a Correlation example in real life?

Positive Correlation- Age - Amount of medical conditions Negative Correlation- Television Watching- Grades No Correlation- Height of a person- Number of shoes they own Hope this was helpful!


What are the possible ranges of correlation coefficients?

The possible range of correlation coefficients depends on the type of correlation being measured. Here are the types for the most common correlation coefficients: Pearson Correlation Coefficient (r) Spearman's Rank Correlation Coefficient (ρ) Kendall's Rank Correlation Coefficient (τ) All of these correlation coefficients ranges from -1 to +1. In all the three cases, -1 represents negative correlation, 0 represents no correlation, and +1 represents positive correlation. It's important to note that correlation coefficients only measure the strength and direction of a linear relationship between variables. They do not capture non-linear relationships or establish causation. For better understanding of correlation analysis, you can get professional help from online platforms like SPSS-Tutor, Silverlake Consult, etc.


Auto correlation and cross correlation?

Auto correlation is the correlation of one signal with itself. Cross correlation is the correlation of one signal with a different signal.


What are the three ways to describe data in a scatter plot?

You can describe if there's any obvious correlation (like a positive or negative correlation), apparent outliers, and the corrlation coefficient, which is the "r" on your calculator when you do a regression model. The closer "r" is to either -1 or 1, the stronger that correlation is.


What are the necessary conditions to show causation in science?

There are three conditions that must be present to show causality: 1) there must be a strong correlation between the proposed cause and effect, 2) the proposed cause must precede the effect in time, and 3) the cause has to be present whenever the effect occurs (Burns & Grove, 2001, p. 791).


What is a no correlation graph?

There are three types of correlation: positive, negative, and none (no correlation).Positive Correlation: as one variable increases so does the other. Height and shoe size are an example; as one's height increases so does the shoe size.Negative Correlation: as one variable increases, the other decreases. Time spent studying and time spent on video games are negatively correlated; as the your time studying increases, time spent on video games decreases.No Correlation: there is no apparent relationship between the variables. Video game scores and shoe size appear to have no correlation; as one increases, the other has no effect. A No Correlation graph would show this.


Is 0.5 the strongest correlation coefficient?

No. The strongest correlation coefficient is +1 (positive correlation) and -1 (negative correlation).


Can you provide an example of a weak positive correlation?

You can find examples by typing it in to Google. Weak positive correlation is a set of points on a graph that are loosely set around the line of best fit. The line will be positive rising up from left to right. A weak correlation can vary a lot as long as you can decipher which direction the data tends towards you have a correlation. If the points are close to the line of best fit you have a strong correlation and with a set of points perfectly lined up is perfect correlation. All three types can positive negative or perfect.


What is the maximum and minimum value of the correlation coefficient?

The correlation can be anything between +1 (strong positive correlation), passing through zero (no correlation), to -1 (strong negative correlation).