Inferential Statistics Quiz 2

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A 5% level of significance suggests a higher level of confidence than a 1% level of significance.

False.

A relationship that is reported as being significant at "p = 0.945" is statistically significant.

False.

When both variables are categorical, the t-test should be used for hypothesis testing

False. Its the chi-square test.

The paired samples t-tests the null hypothesis that the mean difference between the before and after test scores is zero.

True.

The purpose of inferential statistics is to make inferences about characteristics of the population from which the data were drawn.

True.

When the sample size is smaller than 30, the normal distribution is replaced by the t distribution for calculating the confidence interval.

True.

It is easier to reject the null hypothesis with a large sample than with a small sample.

True.

Statistical inference is about drawing conclusions about a population from sample data

True.

The concept of statistical significance relates to the matter of confidence.

True.

The critical value is compared against the test statistic for the purpose of hypothesis testing.

True.

The estimation error is the difference between a sample statistic and a population parameter.

True.

The first step in hypothesis testing is stating the null hypothesis.

True.

The last step in hypothesis testing is looking up the critical value of test statistics.

True.

The null hypothesis is stated in Greek letters because the null hypothesis refers to relations in the population.

True.

The term robust is used, generally, to describe the extent to which test conclusions are unaffected by departures from test assumptions

True

When both variables are continuous, simple regression can be used.

True

A probability distribution is a statistical function which describes all possible values and likelihoods that a variable can take.

True.

A test for the equality of variances is the Leven's Test

True.

A 95% confidence interval is sometimes expressed as stating that when drawing many samples, 5% of the times the mean will lie within a confidence interval.

False.

All t-tests first test for equality of means and then test for equality of variances

False.

The Kolmogorov-Smirnov test is a test of equal variance

False.

The χ2 (chi square) test statistic is useful for determining the direction of relationships.

False.

We use population parameters to estimate unknown sample statistics.

False.

Degree of freedom is a concept associated with determining the critical value

True.

The Central Limit Theorem is fundamental statistical insight that allows us to make inferences from a single sample to the population

True

The Mann-Whitney and Wilcoxon tests are equivalent

True

The one-sample t-test tests whether the mean of a single variable is different from a prespecified value (norm).

True

A combination of visual inspection and statistical testing should always be used to determine normality

True

Confidence intervals are also calculated for proportions (e.g., polling data).

True

The t-test has four test assumptions

True


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