A researcher plans to conduct a test of hypotheses at the 1% significance level. She designs her study to have a power of 0.90 at a particular alternative value of the parameter of interest. What is the probability that the researcher will commit a Type II error for the particular alternative value of the parameter at which she computed the power

P(Type II error) = 0.1

Step-by-step explanation:

In statistics, the formula for power of a hypothesis is given by;

Power = 1 - P(Type II error)

Where P(Type II error) is the probability of making a Type II error.

We are told that the power is 0.9.

Thus;

0.9 = 1 - P(Type II error)

Making P(Type II error) the subject gives;

P(Type II error) = 1 - 0.9

P(Type II error) = 0.1

d (5 x (-20)) * (100 x (0.7))

step-by-step explanation:

5÷1/100 * -.7 *-20

copy dot flip

5*100 * -.7 *-20

rearrange

5*-20   * 100 *-.7

-100   *-70

7000

given hc ∥ gd.¯¯¯¯¯¯which statement is true

step-by-step explanation:

∠cbe and ∠deb are same-side interior angles