relationship of 2 variables Flashcards
correlation analysis measures the ____ and ___ of relationship between 2 or more _____ variables
strength and direction
quantitative
It is a statistical term used to describe a straight line relationship between two variables.
linear relationship
- which two variables have a direct connection which means if the value of x is changed, y also changes in the same proportion. Vice versa.
how can linear relationship be shown
graph, scatter plot
mathematical formula
bivariate
means 2 variables
- independent variable
outcome variable or the effectual variable
- dependent variable
casual variable
this also test the hypothesis of the research and the analysis tools to be used depends on the clinical data to be analyzed or variables available during the study and the research design of the study.
correlation analysis
why is the correlation analysis not used in descriptive study
correlation analysis isn’t used in descriptive studies - because descriptive studies just tell you what something is, not how it relates to other things
example:
Descriptive study: “This dog is brown” (just describing what you see)
Correlation study: “Do bigger dogs eat more food?” (looking at relationship between size and food)
it is applicable in studies that show changes over time or those studies with before and after results
correlation analysis
what is the role of correlation analysis
To determine if the difference between the results from the before and after is meaningful or random.
example:
You try a new study method and your grades go up
But is it because of your new study method? Or just luck
It’s like a mathematical way to prove “This change happened because of what we did, not just by accident.”
correlation coefficient
r = sample
p, rho = population
what are the 2 commonly used correlation coefficient
Pearson Correlation Coefficient (parametric)
- more sensitive
- do not use outliers
Spearman’s Rank Correlation Coefficient (non-parametric)
- less sensitive
- use outliers
wat is the purpose and focus of the scatter plot
-
Purpose: to visualize the joint probability distribution of 2 continuous random variables.
Focus: emphasizes the overall distribution of the data, showing where the data is most concentrated and where it is less likely to occur.
how can you tell if there is an outlier
when it is not close to most of the observations
*scatter plot shld start at 0
Pearson Correlation Coefficient (r) value
positive:
strong - greater than .5
moderate - btwn .3 and .5
weak -btwn .0 and .3
none:
none - 0
negative:
weak - btwn .0 and -.3
moderate - btwn -.3 and -.5
strong - less than -.5
- if positive sign - positive correlation
if negative sign - negative correlation - negative - UL - LR
positive - UR - LL
Pearson Correlation Coefficient is also known as
○ Pearson’s r
○ Bivariate correlation
○ Pearson product-moment correlation coefficient (PPMCC)
○ The correlation coefficient
what are the 4 assumptions to check before performing a Pearson correlation test.
○ Both variables are quantitative (continuous).
○ The variables are normally distributed. (boxplot)
- if box plot is symmetrical, it normally distributed
- if plotted in histogram, it shld be bell curve shape
○ The data have no outliers.
○ The relationship is linear.
