Part two of two; make a data and statistical analysis of abalones population in California; keep in mind this is a basisc tatistical analysis for academic purposes. Can read the full document here: Abalones Part 2 PDF Document
In the last paper the main objective was to understand the whole data, its structure and possible variations on it to determine if data is normally distributed or present any abnormal values that can influence the results, this all with the goal to understand failure in Abalone data gathering and how to improve it. In this second delivery, the primary objective of this assignment is to devise and evaluate binary decision rules for harvesting abalones, improving the possibilities of abalone population growing by statistically defining which abalones are better to harvest and determining the tradeoffs involve in this investigation and decision making.
For this delivery the main objective is centered in examining binary decisions to harvest Abalone populations, covering statistical analysis of choosing between 2 choices (that is harvest or not to harvest) and from there deciding the cutoffs for optimizing harvesting options among the different populations. Binary decisions allow us to take quantitative decisions allowing to facilitate the resource allocation as the objective of the decision-making process and find possible risks and constrains.
Talking about what kind of information, qualifications or considerations would be presented regarding our data project analysis, I would start presenting those graphs and examinations that show our data is normally distributed this enable us to make certain kind of assumptions about data, applications and perform better tests. Also is important to present our linear regression model, this enable the investigators to us to summarize and understand relationships between the variables include it and how residuals impact our model, understanding their patterns and see possible deviations from normality that could negatively impact our results. As a final point here, is very important to present adults and infant proportions, how were obtain and the different cutoff points, ROC curve and summarizing table is quite essential for the purpose of this investigation, appreciate the different volumes and population harvest enable the discussion around which point is better to use.
Now about the different cutoff points at this point I can’t make any recommendation, as mentioned in the past data analysis delivery abalones are endangered and need to be protected but at the same time they represent an economic and recreational activity and necessities from both need to be consider when deciding a cutoff point. As revealed before in this project, at this point I don’t think a final decision can be made about which cutoff point should be use and which population would be impact or at which rate, every point has its own implication and impact at should be evaluated along with other independent variables such as rings to determine the impact for population’s future; also other variables should be include at this point in the study to make it more inclusive. If the only objective is take the decision based just in the optimal harvest proportion notwithstanding of anything else zero harvest is our point, but in the other hand if the intention is preserving and help abalones population to growth the we should take the max difference to take out the smallest amount of abalones. Having said that, I would recommend to harvest zero point, so the possibility of harvesting infants in in lower classes, particularly Class A1, must be minimized or avoid at all.
To settle these data analysis, and its conclusions, we must consider the different alternatives and possibilities regarding how to improve abalone harvesting; then evaluating alternative harvest strategies requires the definition of a suite of indicators to measure the expected performance, based on the statistical and model values deliver in the two projects, of an entire abalone system including, how well the model fitted into reality, how good interaction explorations worked, projections of abalone stock size based on the probability of harvested populations for adults and infants, the probability of dropping below certain thresholds; analytical indicators or KPIS would be used to project the future consequences of management decisions about forthcoming cutoff points.