Three Elements For Inferring Causation Analysis

Throughout the first half of this class, I have learned many new things and freshened my memory on other subjects that I have learned in the past. In chapter one, I learned about the three elements for inferring causation. The three elements for inferring causation are temporal precedence, covariation of cause and effect, and alternative explanation. The temporal precedence rule states that cause must come before an effect. Covariation of cause and effect means that the variables are related and have some type of measurable effect. An alternative explanation means that there is a separate explanation that you would not normally look for.
In chapter two, I was able to further my knowledge of theories. I thought that I had already covered theories

It is extremely important for us to make sure that our test subjects give their full permission and know what they are being used for. Ethics allow things to run smoothly and if we did not rely on them, our procedures would be much more chaotic.
In chapter four, I took the time to really identify the differences and similarities between the independent and dependent variable in an experiment. Variables are something that is changing in an experiment and they are usually are a factor or trait that comes in different amounts. An independent variable is the variable in an experiment that is changed or controlled and it is used to test the effects on the dependent variable. The dependent variable in the experiment that is being measured and tested based off of the independent variable.
In chapter five, I learned about reactive measure. Reactive measure can be described as the way an individual reacts when placed in certain situations. As we already know, every person will react differently in a situation because we all process things in a different way. If you have two people in an experiment and one was briefed on what the outcome would be, the person with that extra knowledge would react differently to the outcome compared to the person who was not given the extra

Content analysis is a research method used for studying communication artifacts. It is used to quantify patterns in various types of communication such as written, spoken, and visual. Typically, content analysis will involve some sort of media like newspapers, movies, and the internet.
In chapter seven, I touched up on some ideas that were discussed in my statistics class. A simple random sample means that each member of the population has an equal opportunity to be chosen. A stratified random sample means that the entire population is split into smaller groups that share the same characteristics and then the subjects are pooled from these groups to form a random sample. Cluster sampling is somewhat similar to the stratified random sample because you divide the population into smaller groups called clusters and take your sample from a group of clusters.
In chapter eight, I learned about internal and external validity. Internal validity is linked to how well the experiment is conducted. This includes whether or not there is more than one possible independent variable, also known as confounding. The less chance for cofounding, the more internal validity. External validity is a generalization of whether or not the results from a sample can be used to make predictions about the entire