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This assignment lets you explore a quasi-experimental model using ANCOVA data analytical approach. By doing this data analysis project, you will understand a new quantitative research model when randomized sampling is not a choice. Specifically, you will develop analytical skills to use covariate to control for or partial out effects of pre-existing differences carried by sampling.

To complete the assessment, answer each question, providing IBM SPSS analysis when necessary to support your answer.

For this assignment, use the small batch of data provided by Warner's textbook on page 724. These are hypothetical data. We will imagine that a three-group quasi-experimental study was done to compare the effects of three treatments on the aggressive behavior of male children. Xc, the covariate, is a pretest measure of aggressiveness: the number of aggressive behaviors emitted by each child when the child is first placed in a neutral playroom situation. This measure was done prior to exposure to the treatment. Children could not be randomly assigned to treatment groups, so the groups did not start out exactly equivalent on aggressiveness. The dependent variable, Y, is a posttest measure: the number of aggressive behaviors emitted by each child after exposure to one of the three treatments. Treatment A consisted of three different films. The A1 group saw a cartoon animal behaving aggressively. The A2 group saw a human female model behaving aggressively. The A3group saw a human male model behaving aggressively. The question is whether these three models elicited different amounts of aggressive behavior when you do (and do not) control for individual differences in baseline aggressiveness.

Let us further assume that there was very good interrater reliability on these frequency counts of behaviors and that they are interval/ratio level of measure, normally distributed,...

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