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BUS 308 Week 4 Quiz




Question 1.1. The distribution for the goodness of fit test equals k-1, where k equals the number of categories. (Points: 1)TrueFalse;Question 2.2. While rejecting the null hypothesis for the goodness of fit test means distributions differ, rejecting the null for the test of independence means the variables interact. (Points: 1)TrueFalse;Question 3.3. For a two sample confidence interval, the interval shows the difference between the means. (Points: 1)TrueFalse;Question 4.4. The goodness of fit test requires the expected distribution to be equally distributed across the categories. (Points: 1)TrueFalse;Question 5.5. The Chi-square test for independence needs a known (rather than calculated) expected distribution. (Points: 1)TrueFalse;Question 6.6. Chi-square tests are parametric in nature ? requiring data that fit a specific distribution/shape. (Points: 1)TrueFalse;Question 7.7. Statistical significance in the Chi-square test means the population distribution (expected) is not the source of the sample (observed) data. (Points: 1)TrueFalse;Question 8.8. Chi-square tests rarely have type I errors. (Points: 1)TrueFalse;Question 9.9. The goodness of fit test can be used for a single or multiple set (rows) of data, such as comparing male and female age distributions with an expected distribution at the same time. (Points: 1)TrueFalse;Question 10.10. Compared to the ANOVA test, Chi-Square procedures are not powerful (able to detect small differences). (Points: 1)TrueFalse


Paper#30972 | Written in 18-Jul-2015

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