Exam 11: Factorial Design: I Lost My Phone Number, Can I Borrow Yours Do Pickup Lines Really Work

A 4 × 3 × 2 × 2 × 2 factorial design includes how many levels in the second independent variable?

A 2 × 2 × 4 factorial design includes how many independent variables?

Dr. Raqui computed a two-way factorial analysis of variance with types of aggression (relational or overt) and the type of communication method (email, phone, or in-person) as the independent variables and level of self-esteem as the dependent variable. The relational aggression main effect was significant, F(1, 222) = 4.2, p = .001, eta² = .031. Which of the following represents the F score?

What is an interaction effect hypothesis?

Use the following to answer questions Scenario I Scenario I is based on fabricated data inspired by the following study: Hennig-Thurau, T., Groth, M., Paul, M. & Gremler, D. D. (2006). Are all smiles created equal? How emotional contagion and emotional labor affect service relationships. Journal of Marketing, 70, 58-73. Do Smiling Employees Improve Customer Satisfaction? In this 2 × 2 between-subjects design, Hennig-Thurau and colleagues examined the effect of employee emotions and authenticity of the emotion on customer relations. A total of 223 undergraduate volunteers participated in this study. The participants were told they would be testing a new movie consulting service. The movie consulting service was created by the experimenters, and actors were hired to act as customer service representatives. Each participant approached the service desk where the actor asked them a number of questions Figure 1. Customers rate their experience more favorably when employees are smiling. -(Scenario I) Figure 1 supports which of the following hypotheses?

Use the following to answer questions Scenario I Scenario I is based on fabricated data inspired by the following study: Hennig-Thurau, T., Groth, M., Paul, M. & Gremler, D. D. (2006). Are all smiles created equal? How emotional contagion and emotional labor affect service relationships. Journal of Marketing, 70, 58-73. Do Smiling Employees Improve Customer Satisfaction? In this 2 × 2 between-subjects design, Hennig-Thurau and colleagues examined the effect of employee emotions and authenticity of the emotion on customer relations. A total of 223 undergraduate volunteers participated in this study. The participants were told they would be testing a new movie consulting service. The movie consulting service was created by the experimenters, and actors were hired to act as customer service representatives. Each participant approached the service desk where the actor asked them a number of questions Figure 1. Customers rate their experience more favorably when employees are smiling. -(Scenario I)How many hypotheses were tested in the study described in Scenario I?

Factorial designs have the added benefit of being able to establish:

Distinguish between a within-subjects factorial design and a between-subjects factorial design.

A two-way analysis of variance is a statistical test that allows researchers to simultaneously test how two separate _____ or categorical independent variables influence the _____ variable and how those independent variables interact to influence the dependent variable.

Marginal mean refers to the average of all participants on _____ level(s) of the _____ variable.

If a factorial design is set up to be a within-subjects design then:

In a 2003 study looking at histocompatibility complex genes, symmetry and body scent attractiveness in men and women researchers asked 200 males and females to provide a blood sample to assess their major histocompatibility complex (MHC) gene, then to sleep a new clean T-shirt for two nights. Researchers also took photos of the males and females to document left- and right-side body symmetry. When the participants were asked about attractiveness, their answers indicated that the:

Use the following to answer questions Scenario III Scenario III is based on fabricated data inspired by the following study: Spencer, S. J., Steele, C. M. & Quinn, D. M. (1999). Stereotype threat and women's math performance. Journal of Experimental Social Psychology, 35, 4-28. Effect of Stereotype Threat on Math Study The myth that men outperform women in math is widely believed by many individuals. The purpose of the study described in Scenario III was to determine if a sample of women whose math abilities equaled a sample of men would fall victim to this threat. To that end, 28 adult men and 28 adult women were administered an easy math test or a difficult math test. The performance of men and women on both the easy and hard test was quantified. A two-factor ANOVA revealed a significant main effect for test, with participants scoring significantly better on the easy test. The analyses also revealed a main effect for sex, with men performing significantly better than women. The interaction between test difficulty and sex was also statistically significant. Further inspection of the data revealed that although men and women did not differ on the easy math test, women performed significantly less well than men on the difficult math test. Given that the screening criteria for participants including earning a grade of B or better in college calculus, and scoring in at least the 85^th percentile on the math subsection of the ACT, the current study indicates that women do succumb to math stereotype threat but only when the math challenge is great. The data are presented in Figure 2. Figure 2. Although women and men performed equally on an easy version of the math test, women performed significantly worse than men on the difficult version. -(Scenario III) What makes the design in Scenario III a hybrid design?

In factorial design, the number of independent variables indicates the number of potential:

In a research scenario where Red Bull alters the manner in which an individual absorbs alcohol into their systems and influences their overall alertness, which variable is the dependent variable?

_____ is a prediction that focuses on one independent variable at a time, ignoring all other independent variables.

Study interactions permit researchers to mimic the complexity of real life, which also tends to:

In a 2 × 2× 3 factorial design how many levels does the second independent variable have?

Use the following to answer questions Scenario III Scenario III is based on fabricated data inspired by the following study: Spencer, S. J., Steele, C. M. & Quinn, D. M. (1999). Stereotype threat and women's math performance. Journal of Experimental Social Psychology, 35, 4-28. Effect of Stereotype Threat on Math Study The myth that men outperform women in math is widely believed by many individuals. The purpose of the study described in Scenario III was to determine if a sample of women whose math abilities equaled a sample of men would fall victim to this threat. To that end, 28 adult men and 28 adult women were administered an easy math test or a difficult math test. The performance of men and women on both the easy and hard test was quantified. A two-factor ANOVA revealed a significant main effect for test, with participants scoring significantly better on the easy test. The analyses also revealed a main effect for sex, with men performing significantly better than women. The interaction between test difficulty and sex was also statistically significant. Further inspection of the data revealed that although men and women did not differ on the easy math test, women performed significantly less well than men on the difficult math test. Given that the screening criteria for participants including earning a grade of B or better in college calculus, and scoring in at least the 85^th percentile on the math subsection of the ACT, the current study indicates that women do succumb to math stereotype threat but only when the math challenge is great. The data are presented in Figure 2. Figure 2. Although women and men performed equally on an easy version of the math test, women performed significantly worse than men on the difficult version. -(Scenario III) The study described in Scenario III used a factorial design to examine the effect of sex and test difficulty on math performance. Which of the following is NOT true of factorial designs?

In a 2 × 2 factorial design using a within-subjects design: