In Problems 5–12, find the indicated areas. For each problem, be sure to draw a standard normal curve and shade the area that is to be found.
Determine the total area under the standard normal curve
(a) to the left of z = -2.94 or to the right of z = 2.94
(b) to the left of z = -1.68 or to the right of z = 3.05
(c) to the left of z = -0.88 or to the right of z = 1.23
Step 1 of 5) Be sure to draw a standard normal curve and shade the area that is to be found. Determine the total area under the standard normal curve (a) to the left of z = -2.94 or to the right of z = 2.94 (b) to the left of z = -1.68 or to the right of z = 3.05 (c) to the left of z = -0.88 or to the right of z = 1.23. So a small t-test statistic for an explanatory variable means that a variable does not yield much additional explanation. Suppose that x1 and x2 are highly correlated to each other and to the response variable. If we include both explanatory variables in the model, the high correlation may lead to small t-test statistics for x1 and x2. This leads us to believe that neither variable is important. In fact, the model may be “confused.” This confusion results because the model believes that not much additional information is learned by adding x1 to the model when x2 is already in the model. In addition, x2 does not provide much additional information when x1 is already in the model.
