If the hypothesized value of a parameter under the null hypothesis lies outside the confidence interval, the null hypothesis:
Answer(s): C
The confidence interval specifies the range over which the true value of the estimated parameter can lie without rejecting the null hypothesis at the given level of significance.
What sample statistic is used to estimate a population value?
Answer(s): B
The point estimate is the estimate of a particular value in the population.
What is the area under the normal curve for z > 1.79?
Answer(s): E
From the z-tables, z = 1.79 is 0.4633. So 1 - 0.4633*2 = 0.0734. Since it is on each side of the curve, 0.0734/2 = 0.0367.
What does it mean if r = -1.00?
All the above are properties or explanations of the coefficient of correlation being equal to -1.0.
Type I error refers to the event that we will:
Remember that the null hypothesis is the one that you maintain to be true unless there is sufficient evidence to prove otherwise. Therefore, the first type of mistake that can happen is that you reject the maintained hypothesis when in fact, it is true. This error is referred to as "Type I" error. On the other hand, you may not have sufficient evidence to disprove the null when in fact, it is false. This failure to appropriately reject the null is referred to as "Type II" error.
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