**
Graziano & Raulin**

**Research Methods (8th edition)**

This study is a factorial experiment investigating the impact of (1) the amount of distraction and (2) the type of interaction on several social ratings of research partners.

The research partners are actually confederates who behave exactly the same in each of the interactions. The amount of distraction is manipulated by adjusting the workload on the participants. Low workload participants are engaged in tasks that require their concentration for about 20% of the total time they are in the experiment. Moderate workload participants are engaged in demanding tasks for 50% of the time, and high workload participants are engaged in demanding tasks for 80% of the time.

There are three types of tasks that participants may be engaged in. One involves competing with the partner; one involves cooperating as a teammate with the partner; one involves working on separate and unrelated tasks.

The ratings are (1) how much they liked their partner, (2) how much they trusted their partner, (3) their estimate of their partner's intelligence, and (4) their estimate of their partner's height.

Both factors were between-subjects factors, and 10 participants were randomly assigned to each of the nine groups of the study.

- Participant ID number (subject)
- Factor 1-Level of Distraction [1=20% activity; 2=50% activity; 3=80% activity] (distract)
- Factor 2-Type of Interaction [1=competitive; 2=cooperative; 3=parallel activity] (interact)
- sex of participant (sex)
- age of participant (age)
- Rating of how much participants liked their partner [1=strongly disliked to 10=strongly liked] (like)
- Rating of how much participants trusted their partner [1=strongly distrusted to 10=strongly trusted] (trust)
- Rating of their partner's intelligence [1=very unintelligent to 10=extremely intelligent] (iq)
- Estimate of the height of their partner to the nearest inch [actual height of confederate was 69 inches] (height)

- Start by using descriptive statistics to find data entry errors. (There are four of them.) Copy the practice #3 file to your hard drive and correct the data entry errors with the most likely numbers before addressing the rest of the questions.
- Verify that there are 10 participants in each of the nine cells.
- Verify that there are an equal number of males and females in each of the cells.
- What is the average age of the participants in this study?
- What is the range and standard deviation of age in this study?
- What is the average liking rating in this study?
- Is there a main effect for distraction level for the dependent variable of liking?
- Is there an interaction for the dependent variable of liking?
- Produce the matrix of cell means for the dependent variable of liking.
- Graph the cell means for the dependent variable of liking?
- Is there a relationship between the variables of liking and trusting in the entire sample?
- Conduct a two-way ANOVA for the dependent variable of trusting.
- Conduct a two-way ANOVA for the dependent variable of intelligence.
- Conduct a two-way ANOVA for the dependent variable of height.
- The height of the confederate in this study was 69 inches. Is there a significant difference between this actual height and the estimated heights from the participants in this study?
- Construct a scatter plot for the variables of liking and trusting.
- Produce the matrix of cell means for the dependent variable of height.
- Is there a correlation between trusting and the intelligence estimate in the entire sample?
- Is there a difference between the male and female participant's estimates of the height of the confederate?
- Is there a sex difference on any of the other dependent variables in the study?
- Are the groups equivalent on the variable of age?
- Are there sex differences on the variable of age?
- Conduct a three-way ANOVA using sex as the third independent variable.
- Imagine that there was only one factor (the type of interaction), with thirty participants assigned to each condition. Conduct a one-way ANOVA of the data for this factor.
- Construct a frequency distribution for height estimates.
- Compute an index of skewness for the variable of age.