Anything that increases the difference between the means increases our ability to find treatment differences. Anything that decreases the difference between the means decreases our ability to find treatment differences.
The greater the error variance (or the standard deviation), the less the power.
So Decreasing your variability increases the power of the test.
As aplha decreases power decreases.
As sample size dicreses, power decreases.
So correct choice is
Decreasing your variability
Which of the following would increase the power of your statistical test? Decreasing your mean Decreasing...
1. Which of the following will increase the value of the power in a statistical test of hypotheses? (a) Increase the Type II error probability. (b) Increase the sample size. (c) Reject the null hypothesis only if the P-value is smaller than the level of significance. (d) All of the above 2. A significance test gives a P-value of 0.023. This means that the result is statistically significant at (a) both the 0.01 and the 0.05 levels. (b) neither the...
Which of the following will increase the power of a significance test? (A) Increase the Type II Error probability (B) Increase the significance level alpha (C) Select a value for the alternative hypothesis closer to the value of the null hypothesis (D) Decrease the sample size. (E) Reject the null hypothesis only if the P-value is smaller than the level of significance.
please answer these two q thank you Select the things that INCREASE power. Check all that apply. Decrease Alpha Increase Alpha Increase N Increase Variability in data. Decrease Effect Size Decrease N 0 Increase Effect Size Decrease variability in data. QUESTION 10 One of the differences between the use of a one-sample t-test and z-test is: whether the data come from the same people the population mean the value of N the population standard deviation
Select which of these increase power. Increase Alpha Decrease variability in data. Decrease N Increase N Decrease Alpha Increase Variability in data. Increase Effect Size Decrease Effect Size
Which of the following statements is FALSE? A.) A larger sample size would increase the effectiveness of a hypothesis test. B.) Alpha (α) is equal to the probability of making a Type I error. C.) Expanding the sample size can increase the power of a hypothesis test. D.) Reducing the significance level (α) can increase a test's effectiveness.
QUESTION 5 The power of the statistical test is zero (0) when the mean is 52, the sample size is 25, and the standard deviation is 2, and the probability of committing Type II error when P is one (1) (previous problem). True False 5 5
Which of the following statements is FALSE? a.) The power of a hypothesis test is the probability of not making a Type II error. b.) Alpha (α) is equal to the probability of making a Type I error. c.) The probability of rejecting the null hypothesis when the null hypothesis is true is called a Type I Error. d.) A smaller sample size would increase the effectiveness of a hypothesis test.
Question 7 1 pts To calculate the power of a statistical test, which of the following conditions MUST be met? O Atwo-sided alternative hypothesis must be used The standard deviation of the population data must be the same as the standard error of the sample data O None are correct O Both the population data and the sample data must be normally distributed
Factors Affecting Power in the t Test After completing this week's assigned readings, discuss one of the following questions: What things can a researcher do to try to increase the magnitude of the d effect size? Suppose that you can increase the d effect size while holding group sizes n1 and n2 constant. How will an increase in d influence the magnitude of t ? Several factors influence statistical power for a one-sample t test. How does statistical power change...
QUESTION 29 Select the things that INCREASE power. Check all that apply. Decrease Alpha Increase Alpha Increase N Decrease N Increase Variability in data. Increase Effect Size Decrease Effect Size U Decrease variability in data.