Chapter 9 Formulas and Vocabulary

• $\alpha$ (alpha) (p. 495)
• Alternative hypothesis (p. 489)
• $\beta$ (beta) (p. 495)
• Hypothesis testing (p. 488)
• Level of significance (p. 495)
• Null hypothesis (p. 489)
• Statistical significance (p. 492)
• Type I error (p. 494)
• Type II error (p. 494)

• Critical region (p. 500)
• Critical value, $Z_{\text{crit}}$ (p. 500)
• Essential idea about hypothesis testing for the mean (p. 498)
• Level of significance $\alpha$ (p. 500)
• Noncritical region (p. 500)
• Test statistic (p. 499)

• $Z_{\text{data}}$ (p. 499).

  $Z_{\text{data}}=\frac{\overline{x}-{\mu }_0}{\sigma /\sqrt{n}}$

• $p$-Value (p. 508)
• Rejection rule for performing a hypothesis test using the $p$-value method (p. 509)

• Critical value, $t_{\text{crit}}$ (p. 525)

• $t_{\text{data}}$ (p. 525).

  $t_{data}=\frac{\overline{x}-{\mu }_0}{s/\sqrt{n}}$

• Essential idea about hypothesis testing for the proportion (p. 543)
• Standard error of the proportion (p. 543)

• $Z_{\text{data}}$ for the hypothesis test for the population proportion (p. 543).

  $Z_{\text{data}}=\frac{\hat{p}-p_0}{\sqrt{\frac{p_0\left(1-p_0\right)}{n}}}$

• ${\chi }_{\text{data}}^2$ (p. 556).

  ${\chi }_{\text{data}}^2=\frac{\left(n-1\right)s^2}{{\sigma }_0^2}$

• Essential idea about hypothesis testing for the standard deviation (p. 556)

• Power curve (p. 567)
• Power of a hypothesis test (p. 567)