1. Yes, this is a good way to visualize the data. It assumes that the primary focus is on the proportion in each group, which seems to be the case here. I like that you have used a horizontal chart.
2. How big are your groups? The bigger they are, the more confidence you can have that the point estimates are representative of the subpopulations A, B, and C. If the groups are somewhat large (30 or more?) I think it is safe to make statements such as "Professional-Younger" Groups A, B and C have a higher % of females [at the institution(s) in the study] as compared to overall population.
1. Yes, this is a good way to visualize the data. It assumes that the primary focus is on the proportion in each group, which seems to be the case here. I like that you have used a horizontal chart.
2. How big are your groups? The bigger they are, the more confidence you can have that the point estimates are representative of the subpopulations A, B, and C. If the groups are somewhat large (30 or more?) I think it is safe to make statements such as "Professional-Younger" Groups A, B and C have a higher % of females [at the institution(s) in the study] as compared to overall population.
Thanks so much! That makes sense about having a large enough group size for the comparison, as smaller numbers would produce unstable percentages. They are all >100. Really appreciate your valuable thoughts!!
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ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.
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