Chapter 9

The claim that we weigh evidence against in a significance test is called the _____

• Alternative hypothesis

  $H_a$
  

• Null hypothesis $H_o$

The claim that we are trying to find evidence for is the ___

• Alternative Hypothesis

  $H_a$
  

• Null Hypothesis $H_o$

The alternative hypothesis is one-sided if it states that a parameter is greater than the null value or if it states that the parameter is less than the null value.

The alternative hypothesis is two-sided if it states that the parameter is different from the null value.

• True

• False

The ____ of a test is the probability of getting evidence for the alternative hypothesis as strong or stronger than the observed evidence when the null hypothesis is true.

Which are the correct ways of making a conclusion in a significance test? Check all that apply

• If the P-value is small, accept

  $H_0$ and conclude that there is not convincing evident for $H_a$ (in context).
  

• If the P-value is small, reject $H_0$ and conclude that there is convincing evidence for $H_a$ (in context).

• If the P-value is not small, fail to reject $H_0$ and conclude that there is not convincing evidence for $H_a$ (in context).
  

• If the P-value is not small, fail to accept $H_0$ and conclude that there is convincing evidence for $H_a$ (in context).

The _____

 $\alpha$  is the value that we use as a boundary for deciding whether an observed result is unlikely to happen by chance alone when the null hypothesis is true. 

____ occurs if a test rejects

 $H_0$  when  $H_0$  is true. That is, the test finds convincing evidence that  $H_a$  is true when it really isn't.

• Type II error

• Type I error

  A ___ occurs if a test fails to reject  $H_0$  when  $H_a$  is true. That is, the test does not find convincing evidence that  $H_a$  is true when it really is. 

• Type II error

• Type I error

What is the formula for standardized test statistic?

• 
  

  $s\tan darized\ test\ statistic\ =\ \frac{statistic-parameter}{s\tan dard\ deviation\ of\ statistic}$
  

• $s\tan dardized\ test\ statistic\ =\ \frac{parameter-statistic}{s\tan dard\ deviation\ of\ statistic}$

 $z=\frac{p̂-p_0}{\sqrt{\frac{p_0\left(1-p_0\right)}{n}}}$  

The following formula is for what?

• one-sample t test for means

• one-sample z test for proportion