If the parameter is greater than the specific value, then the statistical hypothesis is

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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.

02 Choose the most suitable significance value α for which one can have a high chance of making the type I error when the hypotheses test is done.

Select one:

a. α=0.1

b. α=0.01

c. α=0.03

d. α=0.005

03 Given 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: ?

06 In 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

07 To test the events "Income Level" and "Church Attendance" are independent, the following observe values are obtained.

             Income Level                       

              Low        High

Church Attendance

Occasional         15        50

Regular           20         3

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 data can 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

    C1   C2    C3    Total

1   106   124    1    231

    97.80  130.87  2.33

2   67    85    1    153

   64.78  86.68   1.54

3   37    72     3    112

   47.42  63.45   1.13

Total 210 281 5  496

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 in quality among the three shifts. 

b. Do not reject Ho so there are no differences in quality among the three shifts. 

c. Do not reject Ho so there are differences in quality among the three shifts. 

d. Reject Ho so there are differences in quality among the three shifts.