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I have written up a proposed research design for an assignment an it requires the use of a mixed factorial ANOVA. Below is my "analysis" portion of the proposed study and I wanted to make sure I used the write verbiage/described the variables (p value, F) correctly for the ANOVA. Thanks for your expertise!
Data analysis will be conducted using SPSS Software. A mixed factorial ANOVA will be used to compare the mean differences between groups. The mixed factorial ANOVA can be used to measure a dependent variable (VO2max) over two points in time (pre-test and post-test) where subjects have undergone different interventions (AT and AT+RT). It is mixed because there are two types of factors: within-subjects (time: pre and post-test) and between subjects (interventions: AT and AT+RT).
The effectiveness of the plan will be determined by the ability to reject the null hypothesis. This will be determined by the F-ratio in the mixed factorial ANOVA. An F-ratio of close to 1.0 suggests that the null hypothesis is true while a large F-ratio indicates the variation among group means is more than expected by chance (i.e. reject null hypothesis). A significance level of (p < 0.05) will be used to determine if the F-ratio is significant and the null hypothesis can be rejected. That is, there is enough evidence to suggest that AT+RT is more effective than AT at increasing the aerobic capacity of older adults.
Data analysis will be conducted using SPSS Software. A mixed factorial ANOVA will be used to compare the mean differences between groups. The mixed factorial ANOVA can be used to measure a dependent variable (VO2max) over two points in time (pre-test and post-test) where subjects have undergone different interventions (AT and AT+RT). It is mixed because there are two types of factors: within-subjects (time: pre and post-test) and between subjects (interventions: AT and AT+RT).
The effectiveness of the plan will be determined by the ability to reject the null hypothesis. This will be determined by the F-ratio in the mixed factorial ANOVA. An F-ratio of close to 1.0 suggests that the null hypothesis is true while a large F-ratio indicates the variation among group means is more than expected by chance (i.e. reject null hypothesis). A significance level of (p < 0.05) will be used to determine if the F-ratio is significant and the null hypothesis can be rejected. That is, there is enough evidence to suggest that AT+RT is more effective than AT at increasing the aerobic capacity of older adults.