Business Quiz
jams_r1
business_quiz.docx1. An infinite population has a standard deviation of 10. A random sample of 100 items from this population is selected. The sample mean is determined to be 60. At 95% confidence, the margin of error is
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1.28 |
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1.645 |
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1.96 |
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2.33 |
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None of the above |
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2. A sample of 200 elements from a population with a known standard deviation is selected. For an interval estimation of μ, the proper distribution to use is the
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3. The z value for a 99% confidence interval estimation is
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1.28 |
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1.645 |
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1.96 |
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2.33 |
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2.576 |
4. The t value for a 99% confidence interval estimation with 24 degrees of freedom (not the sample size n) is
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1.317836 |
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1.710882 |
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2.063899 |
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2.492159 |
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2.796939 |
5. A random sample of 144 observations has a mean of 20, a median of 21, and a mode of 22. The population standard deviation is known to equal 3.6. The 80% confidence interval for the population mean is
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19.62 to 20.38 |
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19.51 to 20.49 |
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19.41 to 20.59 |
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19.30 to 20.70 |
6. A random sample of 144 observations has a mean of 20, a median of 21, and a mode of 22, and a standard deviation of 3.6.. The 90% confidence interval for the population mean is
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19.60 to 20.40 |
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19.48 to 20.52 |
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19.33 to 20.67 |
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18.20 to 20.80 |
7. A random sample of 64 students at a university showed an average age of 20 years and a sample standard deviation of 4 years. The 80% confidence interval for the true average age of all students in the university is
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19.58 to 20.42 |
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19.35 to 20.65 |
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19.15 to 20.85 |
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19.00 to 21.00 |
8. For a two-tailed Z-test at a 0.05 level of significance; the table (critical) value
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-1.96 and 1.96 |
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-1.645 and 1.645 |
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-2.33 and 2.33 |
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-2.575 and 2.575 |
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9. For a one-tailed Z-test at a 0.05 level of significance; the table (critical) value
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n = 36 |
H0: 20 |
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= 22 |
Ha: > 20 |
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= 6 |
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10. The test statistic equals
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2.30 |
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2.00 |
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-2.30 |
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1.50 |
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n = 36 |
H0: ≥20 |
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= 18 |
Ha: < 20 |
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= 12 |
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11. The p-value equals
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0.1587 |
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0.0668 |
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0.0228 |
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0.0107 |
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n = 36 |
H0: ≥20 |
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= 18 |
Ha: < 20 |
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= 12 |
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12. If the test is done at a .05 level of significance, the null hypothesis should
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not be rejected |
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be rejected |
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Not enough information is given to answer this question. |
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None of the other answers are correct. |
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13. n = 9 |
H0: = 50 |
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= 53 |
Ha: 50 |
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s = 3 Assume data are from normal population |
The p-value is equal to
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0.0171 |
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0.0805 |
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0.2705 |
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0.2304 |
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The p-value equals
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16. n = 9 |
H0: = 50 |
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= 52 |
Ha: 50 |
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= 3 Assume data are from normal population |
The p-value is equal to
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0.0455 |
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0.0027 |
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0.2703 |
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0.3173 |
17. A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation y= 9 − 3x The above equation implies that if the price is increased by $1, the demand is expected to
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increase by 6 units |
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decrease by 3 units |
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decrease by 6,000 units |
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decrease by 3,000 units |
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18. If a data set has SST = 2,000 and SSE = 800, then the coefficient of determination is
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20. Exhibit 12-2 You are given the following information about y and x.
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y |
x |
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Dependent |
Independent |
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Variable |
Variable |
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5 |
15 |
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7 |
12 |
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9 |
10 |
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11 |
7 |
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Refer to Exhibit 12-2. The least squares estimate of b0 equals
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-0.1125 |
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-7.647 |
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16.412 |
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13.75 |
21. A company has recorded data on the weekly sales for its product (y) and the unit price of the competitor's product (x). The data resulting from a random sample of 7 weeks follows.
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Week |
Price |
Sales |
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1 |
.33 |
20 |
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2 |
.25 |
14 |
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3 |
.44 |
22 |
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4 |
.40 |
21 |
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5 |
.35 |
16 |
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6 |
.39 |
19 |
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7 |
.29 |
15 |
The coefficient of determination equals
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0.7705 |
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-0.9941 |
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0.9941 |
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0.8438 |
22. In simple regression model (as well as in multiple regression model), the error term ε’s, are assumed to I. be independent II. be normally distributed III. with a mean of 0 IV. with a variance of 1
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I, II, III |
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I, II, IV |
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II, III, IV |
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I, III, IV |
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All of the above |
Below you are given a partial computer output based on a sample of seven (7) observations.
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ANOVA |
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df |
SS |
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Regression |
1 |
100 |
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Residual |
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Total |
6 |
288.56 |
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Coefficients |
Standard Error |
t Stat p-value |
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Intercept |
5.000 |
2.425 |
0.0942 |
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Variable x |
-3.729 |
2.290 |
0.1643 |
23. The estimated regression equation (also known as regression line fit) is
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Y = 0 + 1X1 + ε, |
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E(Y) = 0 + 1X1 + 2X2 |
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Ŷ = -3.729 + 5.000X1 |
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Ŷ = 2.425 + 1.952X1 |
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none of the above |
24. Below you are given a partial computer output based on a sample of seven (7) observations.
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ANOVA |
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df |
SS |
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Regression |
1 |
100 |
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Residual |
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Total |
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288.56 |
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Coefficients |
Standard Error |
t Stat |
p-value |
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Intercept |
5.000 |
2.425 |
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0.0942 |
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Variable x |
-3.729 |
2.290 |
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0.1643 |
To test whether the parameter 1 is significantly different from zero (i.e., Ha: β1 ≠ 0), the calculated test statistic equals
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2.0619 |
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-1.628 |
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-3.473 |
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11.377 |
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none of the above |
25. Below you are given a partial computer output based on a sample of seven (7) observations.
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ANOVA |
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df |
SS |
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Regression |
1 |
100 |
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Residual |
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Total |
6 |
288.56 |
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Coefficients |
Standard Error |
t Stat |
p-value |
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Intercept |
5.000 |
2.425 |
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0.0942 |
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Variable x |
-3.729 |
2.290 |
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0.1643 |
26. To test whether the parameter 1 is significantly different from zero (i.e., Ha: β1 ≠ 0) at 10% significance level, the critical value (table value) for the test is
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2.571 |
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2.160 |
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2.015 |
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1.771 |
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none of the above |
Below you are given a partial computer output based on a sample of seven (7) observations.
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ANOVA |
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df |
SS |
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Regression |
1 |
100 |
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Residual |
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Total |
6 |
288.56 |
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Coefficients |
Standard Error |
t Stat |
p-value |
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Intercept |
5.000 |
2.425 |
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0.0942 |
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Variable x |
-3.729 |
2.290 |
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0.1643 |
To test whether the parameter 1 is significantly different from zero (i.e., Ha: β1 ≠ 0) at 5% significance level, we will conclude to
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reject H0 and conclude β1 = 0 |
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reject H0 and conclude β1 ≠ 0 |
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fail to reject H0 and conclude β1 = 0 |
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fail to reject H0 and conclude β1 ≠ 0 |
27. Below you are given a partial computer output based on a sample of seven (7) observations.
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ANOVA |
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df |
SS |
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Regression |
1 |
100 |
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Residual |
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Total |
6 |
288.56 |
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Coefficients |
Standard Error |
t Stat |
p-value |
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Intercept |
5.000 |
2.425 |
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0.0942 |
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Variable x |
-3.729 |
2.290 |
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0.1643 |
The coefficient of determination is.
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0.5228 |
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0.4772 |
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0.6535 |
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0.3465 |
