1. Laval-des-Rapides is an electoral district in Quebec where 60% of the population speak French as the first language and 40% speak English. A company conducted a public opinion poll randomly selecting 600 residents from the French speaking community and 400 from the English speaking community of Laval-des-Rapides. This type of sampling is called:
a. cluster sampling
b. convenience sampling
c. random sampling
d. stratified sampling
e. systematic sampling
2. The value occupying the central position in a ranked array is called the
a. mean
b. coefficient of correlation
c. standard deviation
d. percentile
e. median
f. coefficient of determination
g. mode
3. The regression equation, y^=93.11−7.196x expresses statistical dependence of the final grade in statistics (y) on the number of classes missed by students (x) in a sample of 75 statistics students. If the coefficient of determination is r^2 = 0.4695
then the coefficient of correlation is:
a. -0.4695
b. -0.2204
c. -0.6852
d. 0.6852
e. 0.4695
4. Type II error is
a. the mistake of rejecting the null hypothesis when it is false.
b. the mistake of failing to reject the null hypothesis when it is false.
c. the mistake of rejecting the null hypothesis when it is true.
d. the mistake of failing to reject the null hypothesis when it is true.
e. None of the above.
5. In hypothesis testing using Excel, the probability of getting a value of the sample test statistic that is at least as extreme as the one found from the sample data, assuming that the null hypothesis is true, is called
a. M-value
b. N-value
c. O-value
d. P-value
e. Q-value
f. R-value
g. S-value
6. An e-business manager wants to test the claim that the mean exposure to a certain type of internet ads exceeds 1000 viewers per day. Randomly selecting 10 days she calculated the sample mean and standard deviation. As far as the population standard deviation is not available, but the population is approximately normally distributed she has to use a
a. Normal (z) distribution.
b. Student (t) distribution.
c. F distribution.
d. Chi-square (χ²) distribution.
e. Binomial distribution.
7. An e-business manager wants to estimate the mean exposure to a certain type of internet ads. Originally, she found a 90% confidence interval and then increased the confidence level to 95%.
a. The confidence interval became longer.
b. The confidence interval became shorter.
c. The confidence interval didn’t change.
d. There is no relation between length of the confidence interval and the confidence level.
e. None of the above.
8. An e-business manager wants to use z-distribution to estimate the mean exposure to a certain type of internet ads. To construct a 99% confidence interval she originally randomly selected 100 patients and then decreased the sample size to 50.
a. The confidence interval became longer.
b. The confidence interval became shorter.
c. The confidence interval didn’t change.
d. There is no relation between the length of the confidence interval and the sample size.
e. None of the above.
9. An e-business manager wants to test the hypothesis that the mean exposure to a certain type of internet ads exceeds 1000 viewers per day. Originally, she intended to use 5% significance level, but then reduced it to 1%.
a. The rejection region became smaller.
b. The rejection region became larger.
c. The rejection region didn’t change.
d. There is no relation between the size of the rejection region and the significance level.
e. None of the above.
10. An e-business manager wants to test the hypothesis that the mean exposure to a certain type of internet ads falls below 1000 viewers per day. The null hypothesis H₀ can be mathematically expressed as
a. μ = 1000
b. μ ≠ 1000
c. μ ≤ 1000
d. μ ≥ 1000
e. μ < 1000
f. μ > 1000
11. The Central Limit Theorem is one of the most important and useful concepts of statistics. It forms a foundation for estimating population parameters and hypothesis testing and states that
a. as the sample size increases, the sampling distribution of sample means approaches a F distribution, regardless of the distribution of the original population.
b. as the sample size increases, the sampling distribution of sample means approaches a Student (t) distribution, regardless of the distribution of the original population.
c. as the sample size increases, the sampling distribution of sample means approaches a Normal (z) distribution, regardless of the distribution of the original population.
d. as the sample size increases, the sampling distribution of sample means approaches a Chi-square (χ²) distribution, regardless of the distribution of the original population.
e. as the sample size increases, the sampling distribution of sample means approaches a Binomial distribution, regardless of the distribution of the original population.
