A punter for a football team is trying to determine the optimal angle for striking the football off his foot—this is called the launch angle. Using video, his coach records a number of punts kicks using different launch angles and the height in feet for each punt. A regression equation for this relationship is . Based on the residual plot shown, is a linear model appropriate for using launch angle to predict height? A linear model is appropriate because the residual plot is curved. A linear model is appropriate because many of the residuals are close to zero. A linear model is not appropriate because the residual plot shows a clear pattern. A linear model is not appropriate because the y-intercept of the regression equation is negative.

4400

step-by-step explanation:

∠1≅∠2 by the alternate exterior angles theorem.

step-by-step explanation:

given, a ∥ b and ∠1 ≅ ∠3 .we have to prove that e ∥ f

we know that ∠1≅∠3 and that a || b because they are given. we see that by the alternate exterior angles theorem. therefore, ∠2≅∠3 by the transitive property. so, we can conclude that e || f by the converse alternate exterior angles theorem.

we have to fill the missing statement.

transitivity property states that if a = b and b = c, then a = c.

now, given ∠1≅∠3 and by transitivity property ∠2≅∠3 .

hence, to apply transitivity property one angle must be common which is not in result after applying this property which is ∠1.

the only options in which ∠1 is present are ∠1 and ∠2, ∠1 and ∠4

∠1 and ∠4 is not possible ∵ after applying transitivity we didn't get ∠4.

hence, the missing statement is ∠1≅∠2.

so, ∠1≅∠2 by the alternate exterior angles theorem.

36

step-by-step explanation:

answer is because 4×10=40

and 98×4= is 392

40,392