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BIO401 Biostatistics GDB Fall 2020 Solution / Discussion

BIO401 Biostatistics GDB Fall 2020 Solution / Discussion

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BIO401 GDB Solution idea Fall 2020

What are the types of correlation and also explain their usage?             

Types of Correlation

The scatter plot explains the correlation between the two attributes or variables. It represents how closely the two variables are connected. There can be three such situations to see the relation between the two variables –

  • Positive Correlation – when the value of one variable increases with respect to
  • Negative Correlation – when the value of one variable decreases with respect to
  • No Correlation – when there is no linear dependence or no relation between the two

 

 

variables.

  • Positive Correlation:

 

When the increase in one variable (X) is followed by a corresponding increase in the other variable (Y); the correlation is said to be positive correlation. The positive correlations range from 0 to +1; the upper limit i.e. +1 is the perfect positive coefficient of correlation.

The perfect positive correlation specifies that, for every unit increase in one variable, there is proportional increase in the other. For example “Heat” and “Temperature” have a perfect positive correlation.

  • Negative Correlation:

If, on the other hand, the increase in one variable (X) results in a corresponding decrease in the other variable (Y), the correlation is said to be negative correlation.

opposite direction and the graphical representation of the one variable with respect to other variable is straight line.

 

 

 

Consider another situation. First, with increase of one variable, the second variable increases proportionately upto some point; after that with an increase in the first variable the second variable starts decreasing.

Some uses of Correlations

 

from another.

Validity: Concurrent validity (correlation between a new measure and an established measure).

Reliability:

  • Test-retest reliability (are measures consistent).
  • Inter-rater reliability (are observers consistent).

Prediction: If there is a relationship between two variables, we can make predictions about one

 

 

 Theory verification:                                                                                                                           

 

  • Predictive

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