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There is the view that high inequality in the first decades of the twentieth century led to redistributive policies that made the country far more equal but also hurt its economic performance; this view sometimes sees a negative correlation between inequality and growth or, more frequently, it implies that the specific peronist social policies were fundamentally flawed.
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For example, you would chart CSAT against "hold time after reaching the agent" and see if you see a negative correlation — i.e as hold time increase, CSAT decreases, and so on.
From 1960-1999, there was a positive correlation between government expenditure and real GDP for the vast majority of developing countries (developed countries, on the other hand, generally saw a negative correlation).
At the same time, Lord Coe expressed his concern that he could see a negative correlation between social media activity and athletic success.
Washino et al. [272] could also see a negative correlation between the in utero PFOS exposure and the birth weight of baby girls.
For Southern Africa, we even see a negative correlation as the region has become more open to travel from OECD citizens while reverse travel restrictions from Southern Africa to OECD countries have gone up.
If cross-disciplinary information flows result in greater impact, one would see a negative correlation between proximity and impact.
Taken together, we might expect to see a negative correlation between male quality and gamete load among individuals within a population.
We would see a negative correlation when there are very few remaining uninfected cells, and faster decay is caused by faster disappearance of infected cells.
We see a negative correlation between GC3, gene length, and the number of exons.
Although age has an impact on gene expression patterns also distinctly in AML, we see a negative correlation of EVI1 with increasing age (Supplementary Figure 2).
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CEO of Professional Science Editing for Scientists @ prosciediting.com