1. A value such that at least 80% of the data are below and no more than 20% are above the value, is called

• Lower Quartile
• Median
• P80P80
• P20P20
• Upper Quartile
• None of the above.

2.An e-business manager wants to test the claim that the proportions of subscibers who are also followers on three most popular social networks in 2020 have changed significantly since the 2018. The proportions for 2018 are known from the previous survey. Randomly selecting 3100 subscribers of 2020 she calculated the observed frequencies. What distribution should the manager use to test the claim?

• Normal (z) distribution
• Binomial distribution
• F distribution
• Student (t) distribution
• Chi-Square (2) distribution
• None of the above.

3. An e-business manager wants to estimate the mean exposure to a certain type of internet ads. Originally she constructed a 90% confidence interval and then increased the confidence level to 95%. Choose the correct statement.

• The confidence interval became shorter.
• The confidence interval didn't change.
• The confidence interval became longer.
• There is no relation between the length of the confidence interval and the confidence level.
• None of the above.

4. An e-business manager wants to use the Normal zz distribution to estimate the average browsing time of potential cutomers, visiting a certain website. The value of the standard deviation of all browsing times is known. To construct a 95% confidence interval the e-business manager originally selected a random sample of 55 browsing times, and then increased the sample size to 85. Choose the correct statement.

• The confidence interval became longer.
• The confidence interval became shorter.
• There is no relation between the length of the confidence interval and the sample size.
• The confidence interval didn't change.
• None of the above.

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

• as the sample size increases, the sampling distribution of sample means approaches a Normal (zz) distribution, regardless of the distribution of the original population.
• as the sample size increases, the sampling distribution of sample means approaches a Chi-square (22) distribution, regardless of the distribution of the original population.
• as the sample size increases, the sampling distribution of sample means approaches a Binomial distribution, regardless of the distribution of the original population.
• as the sample size increases, the sampling distribution of sample means approaches a Student (tt) distribution, regardless of the distribution of the original population.
• as the sample size increases, the sampling distribution of sample means approaches an FF distribution, regardless of the distribution of the original population.