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Related Concept Videos

Correlation and Causation01:27

Correlation and Causation

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Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
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Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Introduction to Test of Independence01:21

Introduction to Test of Independence

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In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
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Hypothesis Test for Test of Independence01:16

Hypothesis Test for Test of Independence

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The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...
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Correlation01:09

Correlation

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In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
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Law of Independent Assortment02:03

Law of Independent Assortment

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While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.
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Related Experiment Video

Updated: Feb 2, 2026

Ultrasonography of the Adult Male Urinary Tract for Urinary Functional Testing
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Donor Urinary C5a Levels Independently Correlate With Posttransplant Delayed Graft Function.

Bernd Schröppel1,2, Peter S Heeger2, Heather Thiessen-Philbrook3

  • 1Section of Nephrology, University Hospital, Ulm, Germany.

Transplantation
|November 20, 2018
PubMed
Summary

Donor urinary C5a levels predict kidney transplant recipients

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Area of Science:

  • Nephrology
  • Immunology
  • Transplantation Immunology

Background:

  • The complement cascade contributes to ischemia-reperfusion injury and delayed graft function (DGF) in kidney transplant recipients.
  • Kidney injury may begin in the donor before organ procurement.
  • Anaphylatoxins C3a and C5a are key complement components implicated in injury.

Purpose of the Study:

  • To investigate the association between donor urinary C5a and C3a levels and posttransplant outcomes.
  • To determine if donor urine anaphylatoxins predict acute kidney injury (AKI) and DGF in recipients.

Main Methods:

  • Evaluated C5a and C3a in donor urine from 469 deceased donors and 902 kidney recipients.
  • Correlated urinary C5a/C3a with donor AKI and recipient DGF (dialysis within the first week).
  • Performed adjusted analyses to assess independent associations with DGF and graft function.

Main Results:

  • Urinary C5a was threefold higher in donors with stage 2-3 AKI.
  • Higher donor urinary C5a associated with recipient DGF (P=0.002).
  • Donor urinary C5a independently predicted DGF in recipients from donors without AKI (RR 1.31).
  • Urinary C3a showed no association with donor AKI or recipient DGF.
  • A trend suggested better 12-month allograft function with lower donor C5a tertiles (P=0.09).

Conclusions:

  • Urinary C5a concentration correlates with donor kidney injury severity.
  • Donor urinary C5a predicts recipient DGF, especially in the absence of clinical donor AKI.
  • Donor urinary C5a may identify high-risk transplant scenarios for targeted interventions.