Please view the powerpoint and attached link for a YouTube video and answer the following questions -What is a correlational research? -is correlation the same as causation? Explain. -what are some advantages and disadvantages of correlational research? -give three examples of correlation research Please this must be a minimum of 140 words, apa 7th edition format, at least 2 references must be used Youtube link:https://www.youtube.com/watch?v=ROpbdO-gRUo
Correlational research is a statistical technique used to explore the relationship between two or more variables. It involves collecting data on these variables and analyzing whether there is a systematic pattern of association between them. This type of research seeks to determine the strength and direction of the relationship between variables, but it does not establish causation.
Correlation and causation are two distinct concepts in research. Correlation refers to the statistical relationship between variables, whereas causation refers to the cause-and-effect relationship between them. In other words, while correlation shows that two variables are related, it does not indicate that one variable causes the other to occur. For example, a positive correlation between ice cream sales and the crime rate does not mean that buying ice cream causes crime to increase. The relationship may be coincidental or influenced by other factors.
Correlational research has several advantages and disadvantages. One advantage is its ability to examine natural phenomena without manipulating variables. This makes it suitable for studying complex and sensitive topics, such as human behavior and social interactions. Correlation research also allows for the exploration of many variables simultaneously, providing a more comprehensive understanding of the relationships among them. Additionally, correlational studies can generate hypotheses that can later be tested using experimental research designs.
Despite its advantages, correlational research has limitations. One major disadvantage is that it cannot establish causation. While correlations provide valuable insights into the relationships between variables, they do not provide evidence of cause-and-effect. Additionally, correlational research is prone to third variable problems. This occurs when the observed relationship between two variables is influenced by a third variable that is not measured or controlled. For instance, in a study examining the relationship between smoking and lung cancer, factors like genetic predisposition or air pollution may confound the correlation.
There are numerous examples of correlational research studies conducted in various fields. Three examples are as follows:
1. A study investigating the relationship between exercise and mental health. Researchers collect data on individuals’ level of physical activity and their reported levels of depression and anxiety. By analyzing the data, researchers can assess the correlation between exercise and mental well-being, providing insights into whether increased physical activity is associated with improved mental health.
2. A study examining the correlation between socioeconomic status and academic achievement. Researchers collect data on students’ family income and their performance on standardized tests. By analyzing the data, researchers can assess the relationship between socioeconomic status and academic success, providing insights into whether there is a correlation between these variables.
3. A study investigating the relationship between sleep duration and cognitive function in older adults. Researchers collect data on the number of hours of sleep individuals get each night and their performance on cognitive tests. By analyzing the data, researchers can assess the correlation between sleep duration and cognitive function, providing insights into whether there is a relationship between these variables in older adults.
In conclusion, correlational research is a statistical technique used to explore the relationship between variables. It is distinct from causation, as correlation does not imply causation. Correlational research has advantages, such as its ability to examine complex phenomena, but also limitations, such as its inability to establish causation and susceptibility to confounding variables. Examples of correlational research studies include investigating the relationship between exercise and mental health, socioeconomic status and academic achievement, and sleep duration and cognitive function in older adults.