1. The null hypothesis states that the sample mean (after treatment) is equal to
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Question
1. The null hypothesis states that the sample mean (after treatment) is equal to the original population mean (before treatment)
True or False
2. You can reduce the risk of a Type I error by using a larger sample
True or False
3. A researcher administer a treatment to a sample from a population with a mean of u = 60. If the treatment is expected to increase scores and a one –tailed test is used to evaluate the treatment effect, then the null hypothesis states that U _> 60.
True or False
4. A significant treatment effect does not necessarily indicate a large treatment effect.
True or False
5. Which of the following accurately describes the effect of increasing the sample size
A Increase the standard error and has no effect on the risk of type I error
B. Decreases the standard error and has no effect on the risk of a Type I error
C. Decreases the risk of Type I error and has no effect on the standard error
D increases the risk of a Type I error and has no effect on the standard error
Explanation / Answer
1. A null hypothesis is a type of hypothesis used in statistics that proposes that no statistical significance exists in a set of given observations. The null hypothesisattempts to show that no variation exists between variables or that a single variable is no different than its mean.
So answer is false
2. Type I error is assigned so larger sample size shouldn't help there directly I think and the larger samplesize only will increase your power.
So answer is false
3. A null hypothesis is a type of hypothesis used in statistics that proposes that no statistical significance exists in a set of given observations. The null hypothesisattempts to show that no variation exists between variables or that a single variable is no different than its mean. So for this case null hypothesis will be H0: u=60
So answer is false
4. A significant treatment effect does not necessarily indicate a substantial treatment effect so answer is True
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