Researchers term the situation as correlation. Correlation indicates a statistical relationship between two variables, showing how they move together but not necessarily implying causation. The strength and direction of the correlation can provide insights into the relationship between the variables.
Experimental surveys are research studies where participants are allocated into different groups to test the effects of certain variables on a particular outcome. These surveys involve manipulating one or more factors to determine their impact on the variables being studied, allowing researchers to establish cause and effect relationships. They are commonly used in social sciences and psychology to investigate the effects of interventions or treatments.
Experimental research method is most likely to produce quantitative data that will identify cause-and-effect relationships in sociology. This method involves manipulating an independent variable to observe the effect on a dependent variable, allowing researchers to establish causal relationships between variables.
Experimental research method is most likely to produce quantitative data that shows cause-and-effect relationships within sociology. This method involves manipulating one or more variables to observe their effect on another variable in a controlled environment, allowing researchers to establish causal relationships with greater certainty.
A casual relationship in research refers to a situation where a change in one variable appears to cause a change in another variable. It implies that there is a cause-and-effect link between the two variables. However, it is important to remember that correlation does not imply causation, and establishing a causal relationship requires further rigorous testing and evidence.
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).
Well since your getting older, your mine is is losing memory and then that is what makes you havealtimers.
If there are two variables X and Y such that changes in the value of X cause changes in the value of Y but changes in Y do not cause changes in X, then X is the independent variable and Y is the dependent variable.However, if changes in the value of X cause changes in the value of Y and changes in Y cause changes in X, then both X and Y are dependent variables.
Explanatory (or independent) variables are variables such that changes in their value are thought to cause changes in the "dependent" variables.
A and b are the variables cause they represent a number
Yes they are!
Researchers use experiments because they allow for cause-and-effect relationships to be established between variables. Experiments provide a high level of control over variables, which increases the internal validity of the study. This method helps researchers test hypotheses and make inferences about the relationship between variables.
An enzyme is a catalyst for chemical reactions. Three variables that can cause an enzyme to lose its ability to function are temperature, pH level and concentration.
cause and effect
hypothesis
cause n affect
1. The variables must be corelated. 2. The cause must come before the effect 3. Variables are nonspurious
Researchers believe that age-related memory impairment may be caused by changes in the brain's structure and function, such as a decrease in the volume of the hippocampus (a brain region important for memory) and reduced efficiency in communication between brain cells. Additionally, factors like stress, inflammation, and genetics may also contribute to memory decline in older adults.