Interpreting and Using Statistics in Psychological Research. Andrew N. ChristopherЧитать онлайн книгу.
This student was indeed from Michigan.
4. If you are interested, Alex continued to keep that same pair of socks and wear them every time he had a test as an undergraduate. Again, he isn’t a dumb person. It is not a lack of intelligence that makes one susceptible to illusory correlations.
5. The difference between an independent variable and a quasi-independent variable is that an independent variable is controlled by the researcher. A quasi-independent variable is not controlled by the researcher. In our example of a quasi-independent variable, the researchers cannot assign people to be first-years, sophomores, juniors, or seniors. These are naturally occurring groups.
Chapter Application Questions
1 Holly resisted changing her answer on a test question because she reminded herself that “it’s always best to stick with your first answer.” Holly’s decision best illustrates:an algorithm.a heuristic.egocentrism.the gambler’s fallacy.
2 Reliance on the representativeness heuristic is beneficial/helpful when it:simplifies a complex social world.is selectively applied.is reserved for ambiguous situations.minimizes differences within a group of people.
3 The law of small numbers states that:we are more influenced by information that contradicts our beliefs than by information that supports our beliefs.we like to categorize people, places, and events to simplify a complex world.conclusions drawn from a limited number of observations are likely to be a fluke.we pay conscious attention to a limited amount of information at any given point in time.
4 Which of the following set of outcomes is MOST probable?flipping 6 or more heads in 10 coin flips.flipping 60 or more heads in 100 coin flips.flipping 600 or more heads in 1,000 coin flips.All of the above are equally probable.
5 In an experiment, the behavior being measured as a result of the manipulated/changed variable is called the _____ variable.independentdependentspuriousillusory
6 You would probably find NO correlation between:height and weight.shoe size and scores on an intelligence test.ACT scores and SAT scores.distance from the equator and average daily high temperature.
Answers
1 b
2 a
3 c
4 a
5 b
6 b
Questions for Class Discussion
1 The use of phrases such as “federal revenue enhancement” when the government announces a “tax increase” is making use of:the framing effect.the representativeness heuristic.illusory correlation.spurious correlation.
2 The tendency to conclude that a person who is athletic is more likely to be a cross-country runner than a master piano player illustrates use of:the law of small numbers.egocentrism.the availability heuristic.the representativeness heuristic.
3 Which of the following is NOT an example of the gambler’s fallacy?A number will not be drawn in the lottery on a particular day because it was drawn on the two preceding days.A fifth child in a family will be a boy because the first four children were girls.Carl is more likely to carry his umbrella to work when there is a “20% chance of rain” than when there is an “80% chance of dry weather.”All of the above are examples of the gambler’s fallacy.
4 Drew erroneously believes that his test grades are NEGATIVELY correlated with the amount of time he studies for tests. Research on illusory correlation suggests that he is most likely to notice instances in which:poor grades follow either brief or lengthy study.either poor grades or good grades follow lengthy study.good grades follow lengthy study and poor grades follow brief study.poor grades follow lengthy study and good grades follow brief study.
5 The purpose of random assignment in an experiment is to:reduce the likelihood that participants within any group know each other.increase the likelihood that research participants are representative of the population being studied.reduce the influence of any preexisting differences between people assigned to the conditions of the experiment.ensure that the independent variable will have a strong influence on the dependent variable.
Chapter 2 Basics of Quantitative Research Variables, Scales of Measurement, and an Introduction to the Statistical Package for the Social Sciences (SPSS)
After reading this chapter, you will be able to
Identify and differentiate among independent variables, quasi-independent variables, and dependent variables
Present operational definitions for constructs
Summarize the notions and forms of reliability and validity
Classify data into appropriate scales of measurement
Establish a basic SPSS spreadsheet
As we discussed in the previous chapter, we as humans tend to have what I call “efficient flaws” in our thinking. They are efficient because they allow us to navigate the world quickly and prevent us from exhausting our cognitive capacities. They are flaws, though, because they allow for mistakes in how we think about the world. When conducting scientific research, we want to do what we can to minimize mistakes. Here is where statistics come in. I find it helps to approach classes in statistics with the mind-set that statistics are tools we need to understand research. Just as we need a spoon to eat soup, we need statistics to understand scientific research and to understand the world in as objective a manner as is possible.
In the first section of this chapter, we will summarize a research study that we will use to refresh certain information from Chapter 1 and illustrate new information in this chapter. Then, we will discuss the notion of research variables and begin discussion of how to measure them. The third section will provide more details on the measurement of variables and on how such measurements are related to statistical tools we will encounter throughout this class. In the final section, we will introduce a computer software package that will help us manage and analyze variables when we conduct research. As we will use the software package in later chapters, we will stick to the basics in this chapter so that you are comfortable navigating your way through it in later chapters when we consider various statistical tools.
The Study
We will begin by discussing a research study titled “Gender differences in aggression: The role of status and personality in competitive interactions,” which was conducted by Heather Terrell, Eric Hill, and Craig Nagoshi (2008). In this study, there were 150 undergraduate students (78 women and 72 men) at a large southwestern U.S. university. Upon arriving at the research lab, each participant completed measures of his or her personality.
Each participant then answered six questions about his or her hobbies, interests, and accomplishments. These questions are contained in Table 2.1. The researchers told each participant that his or her responses to these six questions would be exchanged with the “other participant,” who was located in a room down the hallway. However, there was no other participant. The supposed other participant was a confederate; that is, he or she was part of the experiment and pretended to be a participant in this study. The answers that the real participant received were “staged” to make the supposed other participant appear to be either “high status” or “low status.” Recall from Chapter 1 the notion of random assignment. Each of the 150 participants was randomly assigned to receive feedback that made the (not real) other participant appear to be “high status” or “low status.”
Table