Question
01 When a hypothesis test was done for a parameter to be more than a value (i.e, a right-tailed test), what would be the conclusion
01 When a hypothesis test was done for a parameter to be more than a value (i.e, a right-tailed test), what would be the conclusion if the critical value of the significance level is smaller than the test statistics?
(Hint: Sketch the areas under normal curve or t-curve for significance level and p-value and compare them)
Select one:
a. Do not reject the null hypothesis and there is significant evidence for alternative hypothesis.
b. Reject the null hypothesis and there is significant evidence for alternative hypothesis.
c. Do not reject the null hypothesis and there is not significant evidence for alternative hypothesis.
d. Reject the null hypothesis and there is not significant evidence for alternative hypothesis.
02Choose the most suitable significance value for which one can have a high chance of making the type I errorwhen the hypotheses test is done.
Select one:
a. =0.1
b. =0.01
c. =0.03
d. =0.005
03Given the following information:
H0: p = 0.09
H1: p < 0.09
n=60
sample proportion = 0.08
Calculate the test statistic (four decimal places).
Answer: ?
04 What is the degrees of freedom for the Chi-Square test, when testing for independence in a contingency table with 4 rows and 4 columns?
Answer: ?
05 A company is interested in testing customer satisfaction with five department stores that it owns. 58 number of randomly chosen customers surveyed. If ANOVA was used, what would be the degrees of freedom for error.
Answer: ?
06In an ANOVA, we find that the p-value is 0.003. We therefore conclude that:
Select one:
a. there is no statistical evidence that any population mean is different from any other
b. there is strong statistical evidence that not all the population means are equal
c. no two population means are equal
d. the null hypothesis should be accepted
e. no two variances are equal
07To test the events "Income Level" and "Church Attendance" are independent, the following observe values are obtained.
Income Level
LowHigh
Church Attendance
Occasional1550
Regular203
Then the expected value of "Regular" and "High" is (one decimal place)
Answer: ?
08
The operations manager of a company that manufactures tires wants to determine whether there are any differences in the quality of workmanship among the three daily shifts. She randomly selects 496 tires and carefully inspects them. Each tire is either classified as perfect, satisfactory, or defective, and the shift that produced it is also recorded. The two categorical variables of interest are: shift and condition of the tire produced. The datacan be summarized by the accompanying two-way table. Do these data provide sufficient evidence at the 5% significance level to infer that there are differences in quality among the three shifts?
Perfect Satisfactory Defective Total
Shift1 106 124 1 231
Shift2 67 85 1 153
Shift3 37 72 3 112
Total 210 281 5 496
Computer output:
Chi-square Test
Expected counts are printed below observed counts
C1C2C3Total
11061241231
97.80130.872.33
267851153
64.7886.681.54
337723112
47.4263.451.13
Total 2102815496
Chi-Sq = 8.647 DF = 4, P-Value = 0.071
Note: 3 cells with expected counts less than 5.0. So can you trust the final decision?
Select one:
a. Reject Ho there are no differences inquality among the three shifts.
b. Do not reject Ho so there are no differences inquality among the three shifts.
c. Do not reject Ho so there aredifferences inquality among the three shifts.
d. Reject Ho so there aredifferences inquality among the three shifts.
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