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or this assignment, please watch the results section video in this module. That video will walk you through how to analyze the data for this experiment. First impressions – the full data set is richly complex and there are a number of analyses that can be completed however, the key hypothesis can be arrived at using a paired t-test. Here is the basics from the website:

The current experiment is faithful to the original (Hamilton & Gifford, 1976) in its primary details. Participants read about people who belong to either a majority or minority group, with twice the number of majority members (n=26) as minority members (n=13). The information conveyed about each of the people describes a desirable or an undesirable behavior. The ratio of desirable to undesirable behaviors is 9:4 in both groups, but because both minority members and undesirable behaviors are rare events, participants should form illusory correlations and judge the minority members less favorably than majority group members.

More information and hypothesis:

Now that we know that there is a relationship between the variables, we can then move on to see if there is a statistical differences between the Apercentofnegative and Bpercentofnegative. Hypothesis: We hypothesize if there are illusory correlations, then there will be a significant difference between the negative characteristics attributed to the Beta group versus the Alpha group, such that the Beta group will be rated more negatively. Data: Reading a paired t-test output.

Mean: arithmetic mean

N number of participants in the sample

Std Deviation: degree to which individuals within the sample differ from the sample mean

Std Error Mean: an estimate of how far the sample mean is likely to be from the population mean, whereas the standard deviation of the sample is the degree to which individuals within the sample differ from the sample mean

Correlation: ranges from -1.0 to 1.0

Sig.: significance – in general p<0.05. Smaller is better in support of your hypothesis!
Pair samples t-test
Pair, that is which two variables you are looking at. The variable Apercentnegative is the negative characteristics attributed to the Alpha group and Bpercentnegative is that attributed to the Beta group. t: computed t-test value
df: n-1 sig (2-tailed): with a p<0.05, we give either end of the distribution tail 2.5% to each tail – this is a more conservative approach. In a one tailed, the full 5% is given to one side, the one predicted by the hypothesis. The variable Apercentnegative is the negative characteristics attributed to the Alpha group and Bpercentnegative is that attributed to the Beta group. Writing the results. t(df) = x.xx, p = .xxx
Use the following template to construct your results section. Depending on the results of your t-test, you must let us your audience know whether or not there was a statistical difference or not. If there was us this template; Using SPSS, we ran a paired samples t-test, to determine whether there was a statistical difference between the negative characteristics attributed to the Alpha group and the Beta group. There was a statistical significant difference between the two groups, t(x) = x.xx, p = .xxx.
Then you must tell us where the difference is by looking at the Means of the two variables. So for instance if there was a higher mean for the Apercentnegative variable, then you would say; In fact, there was a higher percentage of negative characteristics attributed to the Alpha group (M = xx.xx) vs. the Beta group (xx.xx). Putting it all together it would look like this. Using SPSS, we ran a paired samples t-test, to determine whether there was a statistical difference between the negative characteristics attributed to the Alpha group and the Beta group. There was a statistical significant difference between the two variables, t(x) = x.xx, p = .xxx. In fact, there was a higher percentage of negative characteristics attributed to the Alpha group (M = xx.xx) vs. the Beta group (xx.xx). If there was no difference then you would write this; Using SPSS, we ran a paired samples t-test, to determine whether there was a statistical difference between the negative characteristics attributed to the Alpha group and the Beta group. There was no statistical significant difference between the two variables, t(x) = x.xx, p = .xxx.
Instructions:
1. Use SPSS to find the means of both variables.
2. Run a pair sampled T- test to determine whether or not there was a statistical difference between the two variables.
3. Construct your results section using the template above.
4. Complete and submit the assignment by 23:59 EST Sunday.
Submission Instructions:
Use APA style to write and construct this assignment. Please turn in a word document

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