Require assistance with possible ANOVA use

In summary, the conversation discusses the collection of data on dominant hand strength and anthropometric properties, specifically skin-fold adjusted forearm girth, from 18 males and 18 females. The purpose is to determine any potential differences in grip strength based on the amount of musculature in the forearm. The speaker is inquiring about the appropriate analysis method to use for this purpose. They are advised to use a simple ANOVA if the assumptions are satisfied.
  • #1
Dants
7
0
I have recorded the dominant hand strength from all of my participants. I have also recorded a number of anthropometric properties of my participants, including a measure of skin-fold adjusted forearm girth, with the intention of estimating the amount of musculature in the forearm. I have recorded this data from 18 males and 18 females.

I would like to illustrate the interpretation of any sex-related differences in grip strength that might i fI consider the amount of musculature in the forearm.

Am I correct to assume that I should be using a simple ANOVA for this analysis?

Thanks,

Dants
 
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  • #2
Could be wrong, but I don't think your sample size is large enough to get a statistically significant result, assuming there was one.
 
  • #3
I have yet to start the analytics. I was more so inquiring about which analysis was appropriate to use in order to find the results.
 
  • #4
If the assumptions of ANOVA are satisfied, you should be good to go.
 

1. What is ANOVA and when is it used?

ANOVA (Analysis of Variance) is a statistical test used to compare the means of three or more groups. It is used when there are more than two groups and the goal is to determine if there is a significant difference between the groups.

2. How do I know if ANOVA is the appropriate test for my data?

ANOVA is appropriate when the data meets certain assumptions, such as normal distribution and equal variances between groups. It is also important to consider the research question and whether it involves comparing means of multiple groups.

3. What are the steps to conduct an ANOVA?

The first step is to determine the research question and hypothesis. Then, the data should be checked for assumptions and any necessary transformations should be made. Next, the ANOVA test should be conducted and the results should be interpreted. Finally, post-hoc tests may be performed to determine which specific groups have significant differences.

4. Can ANOVA be used for non-parametric data?

No, ANOVA is a parametric test and requires the data to be normally distributed. If the data is not normally distributed, a non-parametric test such as the Kruskal-Wallis test should be used instead.

5. How do I interpret the results of an ANOVA?

The results of an ANOVA will include an F-statistic and a p-value. The F-statistic measures the ratio of between-group variability to within-group variability. A larger F-statistic indicates a greater difference between the groups. The p-value indicates the probability of obtaining the observed results if there is no true difference between the groups. A p-value less than 0.05 is typically considered statistically significant and indicates that there is a significant difference between at least two of the groups.

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