Question

how quantitative research can contribute to poverty reduction​

Answer 1

Answer:

pls plsfollow me

mark me as brainiest

Answer 2

Answer:

Quantitative research typically focuses on two types of testing:

Correlational

Causal Comparative

Both can be applied to the topic of poverty reduction. For correlations, testing focuses on the correlation (relationship) among possible interval-type predictors of poverty, or poverty reduction, and the outcome (poverty). While causal comparative focuses on the extent that the outcome (poverty) differs, based on the nominal-type predictor variables.

For example:

To what extent does [predictor] predict (relate to) poverty? (correlational)

To what extent does poverty differ, based on [predictor]? (causal comparative)

Note that I recommend testing the outcome as a two-tailed test, rather than as a single tailed test), such that the predictor (independent) variable predictive ability is known both positively and negatively, e.g., poverty reduction or poverty increase.

In conclusion, the key is determining what the known and measureable predictors of the outcome are. For poverty, these may include education level, country of origin/residence, race, and many more. Further, it is imperative that the definition for “poverty” is established and measureable. As for all quantitative research and testing, ensure that the data and instruments are valid and reliable.

hope it helps !