A test of : μ = 20 versus : μ > 20 is performed using a significance level of ∝ = 0.05. The value of the test statistic is z = 1.47.

If the true value of μ is 25, does the test conclusion result in a Type I error, a Type II error, or a Correct decision?

Type II error

Step-by-step explanation:

Type 1 error occurs when:

We reject a True Null Hypothesis

Type 2 error occurs when:

We fail to reject a wrong Null Hypothesis.

The given hypothesis are:

Level of significance = α = 0.05

The calculated z test statistic = z = 1.47

In order to make a decision we first need to convert z = 1.47 to its equivalent p-value. From the z-table the p value for z score being greater than 1.47 comes out to be:

p-value = 0.0708

Since, p-value is greater than the level of significance, we fail to reject the Null Hypothesis.

It is given that the true value of μ is 25. If the true value of μ is 25, then the Null hypothesis was false. But from the test we performed, we failed to reject the Null Hypothesis.

Since, we failed to reject a False Null Hypothesis, the conclusion resulted in a Type II error.

the largest number of the four options is 1.8 x 10-2

you have it in scientific notation.

1.80 x 10-6   = 0.00000180

1.80 x 10-4   = 0.000180 (bigger, or "less small", than the former one)

so

1.8 x 10-2       = 0.0180. as you see. the "less small", or the biggest one of them all.

as you have negative exponent, it means you are dividing 1.8 by 100 (i.e. moving the dot towards left, two times).

if you had positive exponent for the scientific notation, power of tenths, you would be multiplying times 100 (moving the dot towards right) as below:

1.8 x (10)2 = 180

so. if you have negative exponent in scientific notation, move the dot toward left. if it is positive, toward right as many times the exponent tells you.

a

step-by-step explanation: