I found that the researchers did an astounding job at including statistics to compare the wealth between blacks and whites. Numbers make it easier to get a better understanding of the data and allows us to compare the figures and come to a conclusion about the research. Another aspect I found praiseworthy about what the researchers did was that they used OLS regression and quantile regression to classify the major individual-level sources of wealth differences between African Americans and Caucasians. The OLS regression allows for estimating the unknown parameters in a linear regression model. Predictions can be made which is important in the future to see if the predications made match the actual results. The quantile regression is a type of regression analysis used in statistics to model the relation between a set of predictor variables and a response variable. This too the same as the OLS regression, allows for estimations to be made which can be helpful when doing research. Limits I see with using data from a survey is that the respondents may not feel encouraged to provide accurate or honest answers. Surveys may also not be a reliable source due to respondents possibly not being full aware of their answers due to a lack of memory. In class, we discussed independent and dependent variables and both Herring and Henderson discussed independent and dependent variables in their research. The independent variable, the variable that causes the dependent variable, in the issue of the income gap between blacks and whites is race. The dependent variable, the variable that is known as the effect, is wealth and/or net worth. In Herring and Henderson’s research, a