Question

Consider the following data from a factorial-design experiment. The DV was “% of participants who offered help to a stranger in distress.”

1.What is the design of this study (e.g., 2 × 2, 2 × 3, etc.)?

2.List the independent variables of this study, and list the levels of each.

3.Sketch a graph of the results of the study. Fill in the names and levels of the IVs.

4.Main effects

-On the average, how does the number of bystanders affect helping?

-On the average, how does the gender of the stranger in need affect helping?

5.Do the graphed data suggest the presence of an interaction effect? If so, describe it.

Answer 1

Analysis of Variance also known as ANOVA is a statistical method used to find the significant difference between one or more than one variables. ANOVA is of two types; one way ANOVA and two way ANOVA. Analysis of variance is also known as f-test. It is used when one variable is manipulated in more than two ways. For example, an experimenter is trying to understand the different situations in which participants offer help to strangers. The different situations exposed is the independent variable which in this case is manipulated in more than two ways to see it's effects on participants. A two way ANOVA is used when both the independent and dependent variables are manipulated in more than two ways.

When ANOVA is performed to see if there is any significant difference, and if it turns out that there is no significance difference (>.5 or .1), the above hypothesis stands corrected.

In a 2x3 analysis of variance, the first variable has 2 levels and the second variable has 3 levels. And the number of hypotheses stated will be 6.

In a 3x3 analysis of variance, the first variable has 3 levels which means that it has been manipulated by the experimenter in 3 ways and the second variable has 3 levels as well, which means that the second variable has also been manipulated in 3 ways. The number of possible hypotheses stated will be 9.