Psychology question 4

Notes for all questions

This is the reference if you use an of the notes

Salkind, N. J. (2012). Exploring research (8th ed.). Upper Saddle River, NJ: Pearson.

Is Personality assessment more complicated than it appearing? Why or why not.

Notes : Complex issues arise when personality variables are incorporated into traditional approaches to personnel selection. Personality assessment and testing in employment contexts is more complicated than it would appear. Rather than arguing against considering personality variables, we focus on five problematic issues associated with their use in personnel selection. These issues are: the appropriateness of linear selection models; the problem of personality‐related self‐selection effects; the multi‐dimensionality of personality; bias associated with social desirability, impression management, and faking in top‐down selection models; and the legal implications of personality assessment in employment contexts. Recommends that practitioners and researchers be cognizant of these issues in the use of personality tests in employment decisions.

Winfred Arthur, David J. Woehr, William G. Graziano, (2001) "Personality testing in employment settings: Problems and issues in the application of typical selection practices", Personnel Review, Vol. 30 Issue: 6, pp.657-676, doi: 10.1108/EUM0000000005978

2. What is the purpose of Psychometric testing and why is it used?

3.What are some advantages and disadvantages of psychometric testing for employers and applicants?

Psychometric testing and employment [Video file]. (2013). Retrieved May 10, 2017, from

Notes and wepage for 2 and 3 Psychometric testing, used to assess a candidate’s psychological and cognitive suitability for a particular job, is a key stage in the recruitment process for many employers. This interview-led program explains what psychometric testing is and why it’s used, the various types of psychometric tests job candidates might encounter, how to prepare for the tests, and the advantages and disadvantages of psychometric testing. https://fod.infobase.com/PortalPlaylists.aspx?wID=18566&xtid=53207

Experts discuss several advantages and disadvantages of psychometric testing for employers and applicants; feedback is important for applicants. http://fod.infobase.com/p_ViewVideo.aspx?xtid=53207#

4.The use and importance of descriptive statistics

Descriptive Statistics The first step in the analysis of data is to describe them. Describing data usually means computing a set of descriptive statistics, so-called because they describe the general characteristics of a set or distribution of scores. In effect, they allow the researcher (or the reader of the research report) to get an accurate first impression of “what the data look like” (that’s research talk!).

First, through the use of descriptive statistics, you can describe some of the characteristics of the distribution of scores you have collected, such as the average score on one variable or the degree that one score varies from another. Finally, once the data are organized in such a way that they can be closely examined, you will apply the set of tools called inferential statistics to help you make decisions about how the data you collected relate to your original hypotheses and how they might be generalizable to a larger number of subjects than those who were tested.

Distributions of scores can be equal in their variability but very different in their mean.

Although there are many different types of descriptive research, the focus of this discussion will be on survey research, and correlational studies in which relationships between variables are described.

5.What are the advantages and disadvantages of using optical scanners to score the results of a test?

Notes Collecting Data Using Optical Scanners If you are collecting data where the subject’s responses are recorded as one of several options (such as in multiple-choice tests), you might want to consider scoring the results using an optical scoring sheet which is scored on an optical scanner. You have probably taken tests using these (such as the College Boards or the SATs). The responses on special scoring sheets are read by an optical scanner, and each response is compared with a key (another sheet which you have prepared). The scanner then records correct and incorrect responses, providing a total score at the top of the sheet. What are the benefits? • The process is very fast. Hand scoring 50 subjects’ data, each with 100 items, can easily take hours. • These scanners are more accurate than people. They (usually) do not make mistakes. Interestingly, in recent years, there has been an increase (or it has just been shared with the public and going on for years) where huge testing companies have reported inaccurate results due to optical scanning failures (such as when the scoring sheets were damp). • Scanned responses can provide additional analysis of individual items, such as the difficulty and discrimination indices discussed in Chapter 6 in the case of a test. Even in the case of no-test items, you can often program the software used for scoring to give you certain configurations of results. Are these machines expensive? Yes—they’ll put a little dent in a budget, but the amount of time and money they save will more than cover the cost. Imagine having your data scored the day you finish collecting it. So, when you can, use optical scoring sheets or, if appropriate, transfer the original data onto one of these sheets to make your work easier and more accurate. Optical scanning equipment is usually available at all major universities. Several companies also publish tests designed to use special answer sheets which are then returned to the company for scoring. One word of caution, however. Just because this is an attractive methodology and may save you some time, do not fall victim to the trap of believing that an optical scoring sheet is the only way to collect and score data. If you do, you will end up trying to manipulate your objectives into a framework of assessment that may not actually fit the question you are asking. Using Newer Technologies There is no question that technologies such as optical scanners are reliable and efficient and work quite well, but there has also been a host of new technologies that allow data collection (and analysis) to be facilitated as well. As you very well know, cell phones are ubiquitous in their everyday presence and the design and use of smartphones is exactly the focus here. These mini computers, using such operating systems as the iPhone OS (in the case of Apple) or Android (in the case of Google), are becoming increasingly easy to program and customize for exactly the purpose that we are discussing here—the collection and analysis of data. In fact, the limits that these tools place on the researcher’s activities are only bound by the creativity and resourcefulness of the people involved in the research endeavor. Look to these tools for assistance when it comes time to begin the data collection phase.

6. Descriptive research and the difference between it and causal comparative or experimental research.

Descriptive Research Although several factors distinguish different types of research from one another, probably the most important factor is the type of question that you want to answer (see the summary chart on page 00 in Chapter 1). If you are conducting descriptive research, you are trying to understand events that are occurring in the present and how they might relate to other factors. You generate questions and hypotheses, collect data, and continue as if you were conducting any type of research. Descriptive research describes the current state of some phenomenon. The purpose of descriptive research is to describe the current state of affairs at the time of the study. For example, if you want to know how many teachers use a particular teaching method, you could ask a group of students to complete a questionnaire, thereby measuring the outcome as it occurs. If you wanted to know whether there were differences in the frequency of use of particular types of words among 3-, 5-, and 7-year-olds, you would describe those differences within a descriptive or developmental framework. The most significant difference between descriptive research and causal comparative or experimental research (discussed in detail in Chapter 11) is that descriptive research does not include a treatment or a control group. You are not trying to test the influence of any variable upon another. In other words, all you are doing for readers of your research is painting a picture. When people read a report that includes one of the several descriptive methods that will be discussed, they should be able to envision the larger picture of what occurred. There may be room to discuss why it occurred, but that question is usually left to a more experimental approach. Although there are many different types of descriptive research, the focus of this discussion will be on survey research, and correlational studies in which relationships between variables are described.

7. Read the “Test Yourself” section on p. 147 in Ch. 9 of Exploring Research. What’s the big deal about these 10 commandments of data collection? Identify any three and detail about the consequences of not following them. The Ten Commandments of Interviewing If you have worked hard at getting ready for the interview, you should not encounter any major problems. Nonetheless, there are certain things you should keep in mind to make your interview run a bit more smoothly and be more useful later, when it comes time to examine the results of your efforts. No one is perfect, but you should strive to adhere to these 10 guidelines about interviewing as well as you can. With that in mind, here are the 10 commandments of interviewing (drumroll, please). Keep in mind that many, if not all of these, could also be classified as interviewer effects, in which the behavior of the interviewer can significantly affect the outcome. 1. Do not begin the interview cold. Warm up with some conversation about everything from the weather to the World Series (especially if there is a game that night and you know that the interviewee is a fan). Use anything you can to break the ice and warm up the interaction. If you are offered coffee, accept (and then do not drink all of it if you don’t want to). If you do not like coffee, politely refuse or ask for a substitute. 2. Remember that you are there to get information. Stay on task and use a printed set of questions to help you. 3. Be direct. Know your questions well enough so that you do not have to refer constantly to your sheet, but do not give the appearance that you are being too casual or uninterested. 4. Dress appropriately. Remove five of your six earrings if you feel wearing six would put off respondents. No shorts, no shirt, no interview, got it? 5. Find a quiet place where you and the interviewee will not be distracted. When you make the appointment for the interview, decide where this place will be. If a proposed location is not acceptable (such as “in the snack bar”), then suggest another (such as the lounge in the library). Call the day before your interview to confirm your visit. You will be amazed at how many interviewees forget. 6. If your interviewee does not give you a satisfactory answer the first time you ask a question, rephrase it. Continue to rephrase it in part or in whole until you get closer and closer to what you believe you need. 7. If possible, use a tape or digital recorder. If you do, you should be aware of several things. First, ask permission to tape the session before you begin. Second, the tape recorder should not be used as a crutch. Do not let the tape run without your taking notes and getting all the information you can while the interview is underway. 8. Make the interviewee feel like an important part of an important project, not just someone who is taking a test. Most people like to talk about things if given the chance. Tell interviewees you recognize how valuable their time is and how much you appreciate their participation. Be sure to promise them a copy of the results! 9. You become a good interviewer the same way you get to Carnegie Hall: practice, practice, practice. Your first interview, like everyone else’s, can be full of apprehension and doubt. As you do more of these, your increased confidence and mastery of the questions will produce a smoother process which will result in more useful information. 10. Thank the interviewee and ask if he or she has any questions. Offer to send (or call) the interviewee a summary of the results of your work. Other Types of Surveys Have you ever been at home during the dinner hour and the phone rings, and the person on the other end of the line wants to know how often you ride the bus, recycle your newspaper, use a computer, or rent a car? Those calls represent one of several types of survey research, all of which are descriptive in nature. In addition to interviews—the primary survey research method—and telephone surveys, surveys include panels or focus groups (in which a small group of respondents is interviewed and reinterviewed) and mail questionnaires.

For example, if you wanted to understand the factors that may be related to why certain undergraduates smoke and why others do not, you might want to complete some type of survey, one of the descriptive techniques that will be covered in this chapter. Or, if you were interested in better understanding the relationship between risk-taking behavior and drug abuse, perhaps the first (but not the last) step would be to conduct a correlational study in which you would learn about questions of a correlational nature. You would be examining the association between variables and learning about the important distinction between association (two things being related since they share something in common) and causality (one thing causing another).

Notes for 8. Test Yourself You read about ethics and some guidelines in Chapter 3B. What might be some conflicts that can arise with those ethical principles and the use of the various survey methods we discussed earlier?

Correlational Research Correlational research describes the linear relationship between two or more variables without any hint of attributing the effect of one variable on another. As a descriptive technique, it is very powerful because this method indicates whether variables (such as number of hours of studying and test score) share something in common with each other. If they do, the two are correlated (or co-related) with one another. In Chapter 5, the correlation coefficient was used to estimate the reliability of a test. The same statistic is used here, again in a descriptive role. For example, correlations are used as the standard measure to assess the relationship between degree of family relatedness (e.g., twins, cousins, unrelated) and similarity of intelligence test scores. The higher the correlation, the higher the degree of relatedness. In such a case, you would expect that twins who are raised in the same home would have more similar IQ scores (they share more in common) than twins raised in different homes. And they do! Twins reared apart share only the same genetic endowment, whereas twins (whether monozygotic [one egg] or dizygotic [two eggs]) reared in the same home share both hereditary and environmental backgrounds. The Relationship Between Variables The most frequent measure used to assess degree of relatedness is the correlation coefficient, which is a numerical index that reflects the relationship between two variables. It is expressed as a number between 21.00 and 11.00, and it increases in strength as the amount of variance that one variable shares with another increases. That is, the more two things have in common (like identical twins), the more strongly related they will be to each other (which only makes sense). If you share common interests with someone, it is more likely that your activities will be related than if you compared yourself with someone with whom you have nothing in common. For example, you are more likely to find a stronger relationship between scores on a manual dexterity test and a test of eye–hand coordination than between a manual dexterity test and a person’s height. Similarly, you would expect the correlation between reading and mathematics scores to be stronger than that between reading and physical strength. This is because performances on reading and math tests share something in common with each other (intellectual and problem-solving skills, for example) than a reading test and, say, weight-lifting performance. Correlations can be direct or positive, meaning that as one variable changes in value, the other changes in the same direction, such as the relationship between the number of hours you study and your grade on an exam. Generally, the more you study, the better your grade will be. Likewise, the less you study, the worse your grade will be. Notice that the word “positive” is sometimes interpreted as being synonymous with “good.” Not so here. For example, there is a negative correlation between the amount of time parents spend with their children and the child’s level of involvement with juvenile authorities. Bad? Not at all. Positive correlations are not “good” and negative ones are not “bad.” Positive and negative have to do with the direction of the relationship and nothing else. Correlations can also reflect an indirect or negative relationship, meaning that as one variable changes in value in one direction, the other changes in the opposite direction, such as the relationship between the speed at which you go through multiple-choice items and your score on the test. Generally, the faster you go, the lower your score; the slower you go, the higher your score. Do not interpret this to mean that if you slow down, you will be smarter. Things do not work like that, which further exemplifies why correlations are not causal. What it means is that, for a specific set of students, there is a negative correlation between test-taking time and total score. Because it is a group statistic, it is difficult to conclude anything about individual performance and impossible to attribute causality. The two types of correlations we just discussed are summarized in Table 9.2. Interestingly, the important quality of a correlation coefficient is not its sign, but its absolute value. A correlation of 2.78 is stronger than a correlation of 1.68, just as a correlation of 1.56 is weaker than a correlation of 2.60.

9.Test Yourself Correlations can be negative or positive, but give an example of how negative does not carry a pejorative meaning and positive outcomes are not always good.

Computing the Pearson Correlation Coefficient The easiest manual way to compute the correlation between two variables is through the use of the raw score method. The formula for rxy (where xy represents the correlation between X and Y) is as follows: The Pearson correlation coefficient is the most frequently computed type of correlation. where Let’s look at a simple example where the correlation coefficient is computed from data set C shown in Figure 9.1. The mean for variable X is 6.3, and the mean for variable Y is 4.6. Here is what the finished equation looks like: Try it yourself and see if you can get the same result (rxy = −.82). You can also use SPSS or Excel to get the answer. Table 9.3 An example of more than two variables and the possible correlations between them Grade Reading Math Grade 1.00 .321 .039 Reading .321 1.00 .605 Math .039 .605 1.00 The correlation is the expression of the relationship between the variables of X and Y, represented as rxy. What happens if you have more than two variables? Then you have more than one correlation coefficient. In general, if you have n variables, then you will have “n taken two at a time” pairs of relationships. In Table 9.3, you can see a correlation matrix, or a table revealing the pairwise correlations between three variables (grade, reading score, and mathematics score). Each of the three correlation coefficients was computed by using the formula described earlier. You may notice that the diagonal of the matrix is filled with 1.00s because the correlation of anything with itself is always 1. Also, the coefficients to the right of the diagonal and to its left form a mirror image. The correlations for the other “half” of the matrix (above or below the diagonal of 1.00s in Table 9.3) are the same. Interpreting the Pearson Correlation Coefficient The correlation coefficient is an interesting index. It reflects the degree of relationship between variables, but it is relatively difficult to interpret as it stands. However, there are two ways to interpret these general indicators of relationships. To interpret the meaning of the correlation coefficient, look to the correlation of determination.

1.Is Personality assessment more complicated than it appearing? Why or why not.

What is the purpose of Psychometric testing and why is it used?
What are some advantages and disadvantages of psychometric testing for employers and applicants?
The use and importance of descriptive statistics
The difference between descriptive and inferential statistics
Descriptive research and the difference between it and causal comparative or experimental research.
Read the “Test Yourself” section on p. 147 in Ch. 9 of Exploring Research. What’s the big deal about these 10 commandments of data collection? Identify any three and detail about the consequences of not following them.
Advantages and Disadvantages of Correlational Methods Discussion
Correlations Discussion What might be some conflicts that can arise with those ethical principles and the use of the various survey methods we discussed earlier?
Test Yourself Correlations can be negative or positive, but give an example of how negative does not carry a pejorative meaning and positive outcomes are not always good.