Psychologist wanted to know if low-achieving students in her class are more inclined to cheat. Based on the average score of their three exams, she divided her 60 pupils into three groups: low, medium and high. She then asked her students how likely they were to cheat on tests if there was little chance of being caught. The students were asked to rate their willingness and desire to cheat. Students were given a score between 1 and 100.
What hypotheses about the study question would you make before you examine the data?
If there is a chance of negative consequences, students with low academic achievement are more likely to cheat.
2. The data collection should be activated. Examine the data carefully before performing any statistical analysis. Are you confident that the theory is valid?
The hypothesis is valid, as the large majority of low scorers were high-cheating.
You can conduct descriptive analyses and submit your results here.
N. Statistical Characteristics
Minimum Maximum Mean Standard Deviation Fraud 60 19 95 52.75 21.39 Valid N (listwise) 60
Summary Statistics
With a standard deviation 21.394, the mean cheating score is 52.75.
Do a one-way ANOVA. Discuss your results in APA style.
Sum of Squares (df) Mean Square F.Sig.
A one-way ANOVA test was done to see if students from three different groups would cheat in a test. One-way Anova showed that cheat scores were statistically different between groups (F (2.57) =65.795; p =0.000).
Which conclusion do you draw from the analysis? Which next actions should you take, if this were your research assignment?
This data shows that students are more likely to cheat than their peers, regardless of how high or low they perform. Because the statistical significance of the p value was significant, it is possible to conduct a post-hoc analysis in order to compare the data.
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