CJ 3675 Midterm
The midterm will consist of short answer and essays. Please answer the questions in full sentences. Students who simply provide a list will be docked points. Please make sure that you read and answer the questions carefully, if the question asks for you to identify and define and you only identify, you will only receive half credit.
Midterm total points: 25
Part I: Short answers – worth 1 point each:
For the following characters, please identify what they mean methodologically and provide a definition (please remember to answer in full sentences and make sure you are answering the entire question):
1. x= In research, the ‘x’ variable is known as the independent variable or the predictor variable. The ‘x’ variable precedes in time and causes change in the dependent variable. Basically, because of ‘x’, something will happen to the dependent variable.
2. y= The ‘y’ variable is known as the dependent variable or the outcome variable. The ‘y’ variable is the subject of the study. This is the variable that should be affected by the independent variable, ‘x’.
3. z= The ‘z’ variable represents any rival causal factors in the study. These are factors, other than ‘x’, that could really cause a change in the dependent variable, ‘y’.
For the following questions, complete the sentence:
4. In order to make a concept into a variable we operationalize it.
5. Operationalization tell me how the concepts will be defined and measured.
Part II: Short answers – worth 2 points each, please remember to answer in full sentences and make sure you are answering the entire question:
6. Identify the issue with the survey question below and make a recommendation for fixing it.
Question: Did you drive to school and the mall today?
Issue: Double-Barreled Question
Fix: Did you drive to school today? Yes No
Did you drive to the mall today? Yes No
7. Identify the issue with the survey question below and make a recommendation for fixing it.
Question: Star Wars: A New Hope, is one of the highest grossing movies of all time and considered to be cinematic genius. Have you seen this movie?
Issue: Biased/Leading Question
Fix: Have you seen the movie Star Wars: A New Hope? Yes No
8. Identify the issue with the survey question below and make a recommendation for fixing it.
Question: Selecting a good Halloween costume is hard. Does being able to sew help you feel prepared for Halloween?
Issue: Biased/Leading Question
Fix: Being able to sew prepares me for Halloween.
Yes No I do not know how to sew
9. What is the difference between qualitative and quantitative data?
The difference between qualitative and quantitative data stems from what they measure. While qualitative data includes information that can only be observed and not measured such as behavior and characteristics, quantitative data includes information from research that can be measured and expressed as numbers.
Part III – Essay worth 12 points. Please make sure that you read and answer the questions carefully, if the question asks for you to identify and define and you only identify, you will only receive half credit.
10. Identify, explain, and provide an example of the eight threats to internal validity (rival causal factors).
There are eight threats to internal validity or rival causal factors. These are factors that could be held responsible for constructing a result rather than what was assumed would be responsible.
History, as a rival causal factor, refers to a specific event or events (major or minor) that occur during the study that may affect the results of the experiment. For example, a researcher is studying if foot patrols will decrease crime in an area, but during the time the study is launched, a neighborhood watch program is developed which encourages citizens to be vigilant and to report any suspicious activity. This program may have also been responsible for the outcome of the study.
Testing or pretest bias is also a threat to internal validity. This rival causal factor occurs when participants of a new study are tested and then re-tested. This poses an issue because when the participants are re-tested, they know what to expect and therefore, their test scores are usually higher. Take, for example, a professor reviews an exam by reading the questions on the exam to the students and then provides them with the correct answer. The students can write down the questions and answers. When given the test, majority of the class passes. Was this because they knew the answers or was it because they memorized the answers that were given to them by the professor? This is therefore a threat because the knowledge of the students was not properly tested.
Maturation is also considered to be a rival causal factor. This is where the subject of the study undergoes biological or psychological changes during the time of the experiment; these changes are in no way related to the experimental variable. An example of maturation would be if a researcher gives a second grade class a breakfast meal every morning for two months to determine if the children’s reading will improve. After two months, the researcher has seen an improvement in how the children are reading and he determines it is because of the breakfast. However, the threat of maturation is present in this scenario because a child may mature and learn quickly. Therefore, the researcher would have to ask himself if maturation of the children could have been a factor in their improved reading.
The threat of mortality is also sometimes present in a researcher’s study. Mortality refers to an expected loss of subjects (willingly or naturally) after studying the same group over a period of time. For example, if I were to study if foot patrol in an area lowers the number of crimes reported in an area, and after a while the residents of the area move, this would directly affect the number of crimes reported. I would not be able to conclude if the crime rate has been lowered because of the increased foot patrols in the area, or if the same amount of crime is being committed but because the residents have moved, there is no one to report the crimes and therefore it appears the crime rate has been lowered.
The threat of statistical regression is the tendency of groups that have been selected for study based on extreme high or low scores to regress or move toward the mean or average on second testing. For example, everyone planning to join the police department are subject to a physical fitness test prior to their admittance. The lowest scoring participants are selected for two weeks of extensive training. Following this training, they are tested again and their physical fitness test scores improve.
Instrumentation involves changes in the measuring instrument from the beginning or first period of evaluation to the second, later, or final evaluation and data collection issues. For instance, assume I want to know how nervous a student may feel when going to take an exam. Imagine that the responses on the survey include: extremely nervous, moderately nervous, mildly nervous, and completely relaxed. The answers from the respondents are going to fall mostly on the side of nervousness. If I had included responses such as moderately relaxed and mildly relaxed, then the outcome of the research may be different.
Selection of subjects occurs when the researcher chooses nonequivalent groups for comparison. For example, if in a foot patrol study the precinct chosen for the experiment was characterized by high levels of citizen involvement and reportage of crime, and these data were compared with those for another non-foot patrol precinct with historically low levels of reported crime, the rival causal factor, selection of subjects, rather than foot patrol, might explain the differences in findings.
The threat of selection by maturation interaction states that the treatment and no-treatment groups, although similar at one point, would have grown apart even if no treatment had been administered. For example, “a researcher is interested in the impact that a new science curriculum has on boys’ and girls’ long-term interest in science. He matches 4th grade boys and girls on their overall interest in science and tracks them until the 12th grade. The researcher found that by the 12th grade, the boys had significantly more interest in science than they girls. The researcher concluded that the new science curriculum was only effective in increasing boys’ long-term interest in science.”