Question

In: Statistics and Probability

10. An F value can never be negative. True or False 9. You use a different...

10. An F value can never be negative.

True or False

9. You use a different table to compute critical values for t-tests and ANOVAs.

True or False

8. Degrees of freedom for chi-squared tests are determined by sample size.

True or False

7. If a correlation between two variables is negative, that means there is no linear relationship between them.

True or False

6. Parametric tests usually have more statistical power than non-parametric tests.

True or False

5. A post hoc test does not need to be performed when an ANOVA produces a statistically significant F value.

True or False

4. In the case of a hypothesis t test, population mean is known.

True or False

3. There is a different t distribution for every hypothetical sample size.

True or False

2. For a chi-square test, if the observed number of cases in your sample fits what you expect given your knowledge of the population, you would reject the null hypothesis.

True or False

1. A two-tailed hypothesis will have more statistical power than a one-tailed hypothesis.

True or False

3.

Solutions

Expert Solution

10. An F value can never be negative.

F value are always positive

True

9. You use a different table to compute critical values for t-tests and ANOVAs.

Inn ANOVA we use F table not t

False

8. Degrees of freedom for chi-squared tests are determined by sample size.

No, the Degrees of freedom depends upon number of groups

False

7. If a correlation between two variables is negative, that means there is no linear relationship between them.

That mean there is negative linear relationship between them

False

6. Parametric tests usually have more statistical power than non-parametric tests.

Since we have information of population

True  

5. A post hoc test does not need to be performed when an ANOVA produces a statistically significant F value.

statistically significant F value mean equality of means is rejected, hence further we will do post hoc

True

4. In the case of a hypothesis t test, population mean is known.

We do not know population mean, we do hypothesis to get the same

False

3. There is a different t distribution for every hypothetical sample size.

As sample size changes the degree of freedom also changes and hence the t distribution

True  

2. For a chi-square test, if the observed number of cases in your sample fits what you expect given your knowledge of the population, you would reject the null hypothesis.

We will not reject the null hypothesis

False

1. A two-tailed hypothesis will have more statistical power than a one-tailed hypothesis.

one tailed test has more power

False


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