This allows us to measure things that usually are not thought of as measurable quizlet

Is the theory described in a sufficiently precise fashion that other theorists can interpret it easily and unambiguously?

-vague description? or precise?
-one is left unclear about exactly what kinds of experimental data would invalidate such theories if a theory isn't precise
-when a theory does attract criticism, the critic almost always turns out to have misunderstood and the theory stands as originally proposed = Duhmen-Quine problem
-verbal vs. formal theories
SEE PICTURE ON NOTES

Downside of precision:
-overfitting: the better the model fits the current data, the more likely it is that is does not fit the new data so well. Simple/linear models are then preferred as they are usually more robust (durable, strong, )
-To conclude that one model provides a better account of data than another based on R2 or other standard goodness-of-fit indices might be reasonable if psychological measurements were noise-free.
a model can end up overfitting the data, that is, it can capture not only the variance that results from the cognitive process of interest but also that from random error.
-The ability of a model to predict new data is called its generalizability, that is, the degree to which it is capable of predicting all potential samples generated by the same cog- nitive process, rather than to fit only a particular sample of existing data. The degree to which a model is susceptible to overfitting, in turn, is related to the model's complexity
-Two factors contribute to a model's complexity: The number of free parameters it has, and how the parameters are combined in it - in other words, its functional form.
-Increased complexity makes a model more likely to end up overfitting the data while its generalizability to new data de- creases. At the same time, a model's generalizability can also increase positively with the model's complexity - but only to the point at which the model is complex enough to capture systematic variations in the data. Beyond that point, addition- al complexity can result in decreases in generalizability, be- cause then the model may also start to absorb random varia- tions in the data

Other pitfalls:
First, if precision is the major virtue of modeling, it can also be a curse. Modelers need to decide how to bridge the gaps between informal verbal descriptions of theories and formal implementations, which can lead to unintended discrepancies between theories and their various formal counterparts, otherwise known as the irrelevant specification problem
Second, a problem that can arise in complex models is the Bononi paradox: When models become more com- plete and realistic they become less understandable and more opaque. Increased complexity of the model can cause us to be able to better predict the outcome value, without a better understanding of what we are modelling (google algorithm)
-understanding such phenomena is relevant but opinions are divided on this:
-causal relationships should be never changing
-so predictions based on causal mechanisms would be more robust over different datasets
-Third, there is the identification problem, namely, that for any behavior there may exist a universe of different models all of which are equally ca- pable of reproducing and explaining the behavior As a result it appears unreasonable to ask which of many models or theories is more "truthful"; rath- er, one needs to ask which model is better than another given a set of criteria, say, the models' practical relevance, simplicity, or usability.

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Hyams Corp. engages solely in manufacturing operations. The data below pertain to the operating segments for the current year: <center> | Operating Segment | Total Revenues | Profit (Loss) | Assets at 12/31 | |-------------------|:----------------:|:---------------:|:----------------:| | U | $13,000,000 |$ 2,000,000 | $15,000,000 | | V | 9,500,000 | 1,200,000 | 11,000,000 | | W | 5,500,000 | (1,000,000) | 3,000,000 | | X | 3,000,000 | 600,000 | 7,500,000 | | Y | 2,000,000 | 400,000 | 4,500,000 | | Z | 2,000,000 | 300,000 | 2,000,000 | | &emsp;Total | **$ 35,000,000** | **$3,500,000** | **$ 43,000,000** | </center> In its segment information for the current year, how many reportable segments does Hyams have? *a.* Three *b.* Four *c.* Five *d.* Six

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