# How is the z-test different from z-score analysis? (Points

How is the z-test different from z-score analysis? (Points : 1)The z-test compares a sample to a population.The z-test calculates a value of z which can be compared to Table A.The z-test provides a way to evaluate how individuals compare to a population.The z-test is based on how individual scores compare to a sample mean.A one-sample t value is statistically significant in which situation? (Points : 1)The calculated t is equal to or larger than the table value.The calculated t is equal to or smaller than the table value.The calculated t is equal to or smaller than .05.The calculated t is equal to or larger than .05.What advantage does the one-sample t offer over the z-test? (Points : 1)The one sample t requires no parameter standard error of the mean.The one sample t requires no parameter mean.The one sample t requires no sample mean.The one sample t doesn’t require interval scale data.Consulting Table 3.1, what percentage of the distribution occurs below z = 1.0? (Points : 1)15.87%34.13%50%84.13%The Cohen’s d has an upper limit of 1.0. (Points : 1)TrueFalseWhat does Cohen’s d measure in the independent t-test? (Points : 1)Whether a result is a random outcomeThe effect size of the resultThe direction of the differenceThe impact of the dependent variableThe z-test asks whether the population from which the sample was drawn has the same mean as the population to which it is compared. (Points : 1)TrueFalseWhich of the following expressions is an indication of sampling error? (Points : 1)M = mx – MsM ≠ mMA type I decision error occurs in which of the following circumstances? (Points : 1)The decision not to proceed with an analysisThe decision to proceed when the analysis is flawedErroneously determining that a result is not significantErroneously determining that a result is significantIn a distribution for which the mean is 25 and the standard deviation is 5, what percentage of all scores occur at 30 or above? (Points : 1)15.87%20%34.13%84.13%

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