1. Independent variable (p. 39) – a type of variable that is controlled by the experimenter and that comes before the dependent variable. An example of an independent variable in a study would be the amount of time played by a college football player.2. Dependent variable (p. 39) – a type of variable influenced by the independent variable. An example of a dependent variable would be the amount of hits football players take versus how long they play.3. Hypothesis (p. 47) – a proposed statement of findings regarding an anticipated problem in a research study. An example hypothesis would be “If college football players play a full 60 minute game, then they are 70% more prone to concussions.”4. Null hypothesis (p. 49) – a type of hypothesis in which no relationship exists between the measured variables and offers no support for the original hypothesis. An example of a null hypothesis would be that there was no relationship between playing time and the number of concussions suffered by players who had high playing times.5. Primary Source (p. 68) – the original document that was written in the first person and is intended for readers. A researcher could find players suffering from concussions and ask them to journal about their physical and emotional sensations during a period of time while they are under concussion protocol to see how concussions affect different people. Journals written by players are the primary source of research.6. Participant (p. 95) – a person who takes part in an experiment and is used for data collection. A participant in my research could be a student or an NFL player who plays for several minutes and is prone to great success.7. Sample (p. 95) – at the heart of the article, the research is based on two ends of a spectrum. For example, a researcher researching concussions might look at football players who are linebackers who play most of the game and take a lot of hits and compare them to punters or kickers who are only in the game for a few seconds and rarely make contact with other players.12. Sampling bias (p. 112) – a sampling method can be defined as biased if the results found by the research favor the outcome the researcher is looking for. The researcher ultimately controls/influences whether the results are biased and potentially misleading. If a researcher believes that football players are more susceptible to concussions, he or she may only look at specific locations where players suffer more hits to the head for their research, which could bias the results when looking at football players as a whole.