Recall that type II error is the probability of retaining the null hypothesis

# Recall that type ii error is the probability of

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error and is calculated as 1 – ß. Recall that type II error is the probability of retaining the null hypothesis when it is in fact false. When the researcher sets type II error at 0.20 prior to conducting a study, this means that the power of the planned statistic has been set to 0.80. In other words, the statistic will have an 80% chance of detecting an effect if it actually exists. DIF: Cognitive Level: Analysis REF: Page 536 7. A researcher is concerned about the power of his study. His planned interventional study examines the effect upon depression of instituting twice-yearly trips with a Road Scholar program for widows and widowers who have, 1 to 2 years before, lost a spouse to a long illness. What strategies could make type II error less likely? (Select all that apply.) a. Decreasing the effect size b . Increasing the alpha from .05 to .10 c. Increasing the beta from .20 to .30 d . Decreasing the beta from .20 to .10 e. Decreasing the alpha from .05 to .025 f. Increasing the sample size ANS: B, D, F Power is the probability that a statistical test will detect an effect when it actually exists. Therefore, power is the inverse of type II error and is calculated as 1 – ß. Recall that type II error is the probability of retaining the null hypothesis when it is in fact false. When the researcher sets type II error at 0.20 prior to conducting a study, this means that the power of the planned statistic has been set to 0.80. In other words, the statistic will have an 80% chance of detecting an effect if it actually exists. Often, reported studies failing to reject the null hypothesis (in which power is unlikely to have been examined) will have a low power level to detect an effect if one exists. Until recently, the researcher’s primary interest was in preventing a Type I error. Therefore, great emphasis was placed on the selection of a level of significance but little on power. This point of view is changing. Power analysis involves determining the required sample size needed to conduct the study. Cohen identified four parameters of power: (1) significance level, (2) sample size, (3) effect size, and (4) power. If three of the four are known, the fourth can be calculated by using power analysis formulas. Effect size is a constant; it is “the degree to which the phenomenon is present in the population or the degree to which the null hypothesis is false.” Consequently, if the researcher wants to increase a study’s power, the sample size must be increased, or the level of significance must be set at a less stringent level. DIF: Cognitive Level: Analysis REF: Page 536 8. Findings can be statistically significant be clinically not significant. Which of the following studies with statistically significant findings exemplify this? (Select all that apply.) a. Seventy-five seconds of UV light daily can completely reverse the symptoms of allergic dermatitis. b . Eating a cup of salad greens daily increases one’s life expectancy by 2 years. c. Petting a cat for five minutes daily increases one’s endorphin levels. d .  #### You've reached the end of your free preview.

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• Fall '16
• Denise Cauble
• Nursing, researcher, Cognitive Level
• • • 