If two linear regression models have the same number of explanatory variables, a model with an r2 value of 0.45 is a better prediction model than a model with an r2 value of 0.65.
true
false

False

Step-by-step explanation:

Given that two linear  regression models have the same number of explanatory variables

First model has coefficient of determination as 0.45 while other

0.65

we know that R^2 is the proportion showing the variation of dependent because of variation in independent variables.

Hence a higher R square is always better because it ensures more linearity and hence more accuracy in the regression equation.

Hence 0.65 model is better than 0.45 model.

The given statement is false.

∠lno ≅ ∠lnm

∠oln ≅ ∠mln

step-by-step explanation:

given   that triangle lno is congruent to triangle lnm.

we have to fill up the blanks in the given question.

according to above order of congruency   kept in mind we can say that

∠lno ≅ ∠lnm

∠oln ≅ ∠mln

ln ≅ ln due to common in both.

hence, by sas congruency,

the side angle side rule   states that if two sides and the included angle of one triangle are congruent to another triangle, then these two triangles are congruent.