If two explanatory variables have a correlation that exceeds 0.5 or is less than -.5, they cannot be used together in the same model.

Concerning independent variables, a model may have only the original variable or a transformation of the variable but not both.

The picture here is from a procedure in R.  If it does not load in your browser you can open the pdf file here which also contains an image of the output. Use the output to answer the following questions. a) Which procedure in R produced the output? [a_leaps]. b) Which variable does the procedure suggest is the best variable to include in your model?  That is, if you could only include one variable which variable would that be? The variables are x1, x2, x3, …. [b_x6]. c) Which variables does the procedure suggest belong in the final model? [c_all]. d) T/F: it is possible to use the results in the output to calculate the VIF. [d_False]. e) Examine the results to find the stage at which you would add x2.  Compare this model to the model that does not include x2, that is the model before adding x2.  What is the reduction in SSE/MSE from adding x2 to the model. [e_1324].  

Calculate the VIF for the explanatory variable X4.  When X4 is regressed on the other explanatory variables the resulting R squared is [r2]. Answer to 4 decimal places.

A client has a C6/C7 incomplete spinal cord injury secondary to a gunshot wound. It is appropriate to strengthen the triceps to overcome the power of the biceps which is in flexor synergy pattern.

The patient has a C6 quadriplegia. We can anticipate that he or she has innervation of which of the following?

A client has T-12 spinal cord injury.  Which would an appropriate intervention?

The COTA decides to use Constraint induce movement therapy (CIMT). He must ensure that he provides the following types of tasks

Rotational movement of the joint on the fixed surface of the adjoining surface

_________________________refers to consistency in measurement and ______ refers to measuring exactly what you intended to measure.