Correlations and Confounding Variables

6. Many drug safety research studies are sponsored by pharmaceutical companies that would financially benefit if the results of the study are favorable. Is this an example of a potential confounding factor?

11. Why is correlation data (data showing that two events occurred at the same time) not necessarily meaningful? Because one factor might not be the cause of the other.

There are several differences between correlation and causation. Correlation is if an event happens and is not related to another event and it is a coincidence. This would be if an event happened but it was not connected to another. An example of this would be catching a foul ball at a baseball game. It would be a correlation because you just happened to be in that place where the ball was hit and were able to catch it. Causation on the other hand is a cause and effect. One thing happens because another thing previously happened. An example of this would be if a person drank caffeine late at night, then they would be up all night. Another example of this would be if someone slipped on ice coming out of class.

Correlation vs. causation: This refers to the error which emanates from having the assumption that since one thing is related with another, it must lead to the other.

Correlation is usually when two things tend to happen together at the same time and causation is something happens because of something else. I think it is harder to prove causation because

Collects numerical data that can be quantified. Research with numbers. Focus on measuring, collecting and drawing relationships through statistical analysis and experimentation.

Researchers have studied the correlation between birth defects and tobacco. Correlation is not about cause and effect but rather how a relationship between two variables works

* Statistical significance of the coefficient – This is a statistical test that confirms if the coefficient regardless of its value is robust and different from zero. Also referred to as the P-value.

Correlative studies are ones where the independent variable is not manipulated. Instead, scientists research the existing variation in them. Causative studies are ones that manipulate the independent variable to see how it affects the dependent variable.

Correlation means a mutual relationship or connection between two or more things, and it's different from causation, because that means the effect after an action. For example, in my life the correlation being a parent and their child and the causation could be a child getting an F for not studying. The Early Childhood Longitudinal Study is an overall study of the parents and students. They test their skills in academics then do a survey to better understand the thought process of each one and where it came from. The purpose was to see their correlation and causation. If they went hand-in-hand or not, another example, "A child whose parents are highly educated typically does well in school; not much surprise there" (199). What the parent does for their child is more helpful than what a parent is. With the support it all fits in and helps the child in its academic performance. I however, think it can go both ways; a parent can help and be it to be beneficial. It all depends on the child at the time and what its capabilities are, not their

Therefore, not fitting with what the hypothesis states. 5c. What could be changed and improved for the correlation technique would be what studies they receive their data from. The correlation technique cannot be manipulated and it is used with the existent data. By changing the data the answers could be changed in order to prove the hypothesis without any defaults. 5d. Correlations are great when it comes to comparing variables. By using the correlation method, it cannot be manipulated because it is using the information that already exist. But, by using an experiment a person can actually prove the hypothesis and it is more concise. It can be manipulated meaning that a person can always find the reason for the results. Furthermore, this can conclude whether the independent variable affected the other variables in the experiment. 5e. An experiment that would help support the hypothesis is by giving 2 people with split brain and 2 people with the intact brain a task that would exercise the brain to see the relationships of the functions of the left and right hemispheres. The experiment would be showing a slide with the faces of well-known celebrities and using name tags. The people with the intact

"Correlation is a measure of association that tests whether a relationship exists between two variables. It indicates both the strength of the association and its direction (direct or inverse). The Pearson product-moment correlation coefficient, written as r, can describe a linear relationship between two variables" Correlation (n.d). As a human service professional and completing research there are advantages and disadvantages to correlational research methods, such as using correlational research it allows us to collect data and determine the strength and direction of what it is we

Specific measure instruments are used in quantitative research. Gathered measurements are recorded on a chart, which can reveal how small changes between individual measurements may equal to a more noticeable change over a period of time.

Research shows that there is a correlation that shows the relationshop between the IQ and the grade point average of students. It was found that the correlation is strong at a .75 because it’s a direct relationship. For instance when someone has a higher IQ they are more likely going to have a higher GPA. However although the correlation shows a higher IQ means higher GPA does not mean that is the only reason the GPA is rising, it could be because they hired a tutor, have been studying more or are maybe just in more interesting classes. In correlation studies they show that there is a relationship between two different variables however it is not evidence or proof in any way. The reason it isn’t proof is because it has not been proven that they are directly the reason for the relationship however that they do have common results. Some of the reasons correlation cannot prove anything is because of the limitations; these would be the lack of information about the correlation, sample size or the standard deviation. In our text it states “If the word correlation is broken down co-relation it is expresses what is meant: The characteristics are related and the evidence for the relationship is that they vary together, or co-vary. As the level of one variable changes, the other changes in concert, this happens because both variables contain some of the same information. The higher the correlation the more they may have in common” (Tanner,2011).

In Psychology 101 we learned that research methods are used in order to understand our mental and behavioral processes by making observations in a systematic way, following strict rules of evidence and thinking critically about that evidence. This scientific research is based on theories (tentative explanations of observations in science), hypotheses (predictions based on a theory) and replication (testing a hypothesis in more than one study). Some of the different research methods are firstly, descriptive studies. Descriptive studies are studies that use survey methods, naturalistic observation and clinical methods. Another research method is correlational studies. Correlational studies are studies that help one to determine if a relationship exists between two or more variables and if so it tells one how strongly those two variables relate to one another. With in correlational studies one can have positive correlation (as one variable increases or decreases so does the other), negative correlation (variables go in opposite directions) or zero correlation (no relationship between the variables). Another research method is formal experiments. Formal experiments are studies that allow us to draw conclusions about how one variable may cause or have an effect on another variable. With in formal experiments there are four elements, which are the independent variable (variable that is manipulated or controlled), the dependent variable (variable that is measured), the experimental