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1. For this study and statistic, 2 groups with 24 participants were used. When the ANOVA was ran, it resulted in a p-value showing that there is about a 0.5% chance that this data was not due to random variance. However, it is important to point out that with a small group and looking at a medical condition, if the symptomology is extremely different between the different groups, then it is going to result in a higher F statistic (Fidell & Tabachnick, 2007).
2. Null Hypothesis: There is no difference between the two groups’ pain score whether they received treatment for their condition or not.

Alternative Hypothesis: The group that receives the treatment will result in a lower pain score than that of the group that does not receive the treatment.

Yes, the null hypothesis should be rejected because significance was found when running the statistical test and with the resulting p-value (Howell, 2010).

1. Yes they did. F = 9.619 with a p = 0.005
2. In order for the results to still be significant at a p-value of 0.001, the F statistic calculated must be larger than the table statistic given for an alpha value of 0.01.
3. The null hypothesis would be rejected because the p-value is less than 0.05, therefore the results found would be statistically significant at the specified alpha level (Howell, 2010).
4. The ANOVA shows for variance across groups, not within just one group. This is why we can look for interaction effects when looking at graphs produced by ANOVA. A Spearman correlation can be used to gather correlations within a single sample group (Gravetter & Wallnau, 2008).
5. There were 3 groups in the study with 150 participants.
6. The strengths are that this allows the study to apply to women specifically dealing with OA, however that limits generalizability to the population as a whole. Another problem with the design is that the groups are not matched in respect to the number of participants in each of the groups (Howell, 2010).  Another problem is dealing with the differences in age, since there was no restriction placed on age.
7. Yes they established the trends associated with the ANOVA. They were able to show statistical calculations, each with one less than at least p = 0.05. In addition, the graphs produced by the data showed drastically different trends and also showed no interaction effects that could have skewed the data (Gravetter & Wallnau, 2008)
8. The first is that with women that old, there can be other medical conditions that are going to affect the results. The second is that with it only being women, this research could not be applicable to men. In addition, the 12 week time frame may not be long enough to produce enough of the results needed to get a statistically valid answer.

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