Reference no: EM131961526

Question: Provide a substantive contribution that advances the discussion in a meaningful way by identifying strengths of the posting, challenging assumptions, and asking clarifying questions. Your response is expected to reference the assigned readings, as well as other theoretical, empirical, or professional literature to support your views and writings.

Data screening is having missing values in your database, and a program estimates the missing values using either a simple average or a more elaborate multiple regression technique. Doing a data screen you can find missing values, outliers and even error in the work. Even just having one piece of data that is put of whack you can cause an error or typing in something wrong would be a human error.

"An outlier may be due to variability in the measurement or it may indicate experimental error". (Rapallo, 2012). The outlier itself is a point that is more distant then the other observations or data. If you have an outlier in your data set it can throw your calculations.

Missing data is when you have no data for a single set or point. At that point no record is there for that particular observation. Having missing data can also throw your calculations and have your data off.

References: Rapallo, F. (2012) Outliers and Patterns of Outliers in Contingency Tables with Algebraic Statistics. Scandinavian Journal of Statistics, 39(4), 784-797. doi:10.1111/j.1467-9469.2012.00790.x