readiness

The General Social Survey asked the question, "After an average work day, about how many hours do you have to relax or pursue activities that you enjoy?" to a random sample of 1,155 Americans. The average relaxing time was found to be 1.65 hours A. A sample statistic B. a Variable C. a population parameter D. an observation

1. An American in the sample: D. an observation 2. Number of hours spent relaxing after an average work day: B. A variable 3. 1.65: A. sample statistic 4. Average number of hours all Americans spend relaxing after an average work day: C. a population parameter

A 2012 Gallup survey suggests that 26.2% of Americans are obese. Among a random sample of 100 Americans, how many would you expect to be obese? A. It is unlikely that 10 out of 100 will be obese. B. Exactly 26 people will be obese. C. It is impossible that 40 out of 100 will be obese. D. Exactly 26.2 will be obese.

A

Rule of 68-95-99.7 is a rule of thumb for the probability of falling within 1, 2, and 3 standard deviations of the mean in the normal distribution is. This will be useful in a wide range of practical settings, especially when trying to make a quick estimate without a calculator or Z-table. A. The area under a normal curve that falls between Z = -2 and Z = 2, is about 0.95 or 95%. B. The area under a normal curve that is below Z = 2 (i.e. left tail area), is about 0.95 or 95%. C. The area under a normal curve that outside of |Z|=2 (i.e.: Z<2 or Z>2), is about 0.95 or 95%. D. The area under a normal curve that is above Z = 2 (i.e. right tail area), is about 0.95 or 95%.

A

The t-distribution is always centered at zero and has a single parameter: degrees of freedom. A. When the degrees of freedom is large, the t-distribution is very close to the standard normal distribution. B. The degrees of freedom (df) determine the mean of a t-distribution. C. When the degrees of freedom is small, the t-distribution is very close to the standard normal distribution D. The degrees of freedom (df) describes the skewness of a t-distribution.

A

Which of the following is NOT a condition that needs to be met for the binomial distribution to be applicable? A. the number of desired successes, k, must be greater than the number of trials B. the probability of success, p, must be the same for each trial C. the trials must be independent D. the number of trials, n, must be fixed E. each trial outcome must be classified as a success or a failure

A

Which of the following is NOT true about Z-score? A. In skewed distributions the Z score of the mean might be different than 0. B. For a normal distribution, IQR is less than 2*SD. C. Z scores are helpful for determining how unusual a data point is compared to the rest of the data in the distribution. D. Majority of Z scores in a right skewed distribution are negative.

A

Which of the following is true about the central limit theorem (CLT)? A. The sampling distribution of sample mean for large independent samples tends to follow a normal distribution. B. The standard error of sampling distribution is the same as the population standard deviation. C. The larger the sample size, the larger the standard error. D. Sample mean is always a biased estimate of population mean.

A

Which of the following is true about using a z-test and a t-test? A. z-test is a special case of t-test. B. t-test is a special case of z-test. C. z-test is for categorical variables, and t-test is for numerical variables. D. z-test and t-test are exactly the same.

A

According to the CLT, the standard error ___ as the sample size n ___. A. increases, becomes larger B. decreases, becomes larger C. increases, stays the same D. decreases, becomes smaller

B

In a large sample situation (df>120), which of the following is the correct p-value for this t-test= - 2.2 A. between 0.05 and 0.10 B. between 0.01 and 0.05 C. < 0.001 D. between 0.001 and 0.01

B

Standard error is A. the same as standard deviation. B. a measure of uncertainty about using sample mean to estimate population mean. C. a measure of bias when using sample mean to estimate population mean. D. the difference between population mean and sample statistic.

B

Which of the following is NOT a correct interpretation of confidence intervals? A. If we took repeated samples from the population and constructed (1 − α) % intervals around all of our sample estimates, (1 − α) % of such intervals would contain the true value of the parameter. B. We can say that the true μ falls within the interval with probability (1 − α) % C. We can say that (1 − α) % of all intervals of a given width constructed in this fashion will contain the true μ. D. We can say that (1 − α) % of all intervals of a given width constructed in this fashion will capture the true μ

B

Which of the following is NOT true about normal distribution? A. Many variables are nearly normal. B. All normal distributions are the same. C. Normal distribution is a unimodal and symmetric, bell shaped curve D. A normal distribution is determined by two parameters: mean and standard deviation.

B

Which of the following is NOT true about the standard normal distribution? A. The standard normal distribution is a normal distribution with mean of 0 and standard deviation of 1. B. The standard normal distribution is the only normal distribution. C. Any normal distribution can be standardized with a score to a normal distribution. D. A normal probability table that can be used to find percentiles of a normal distribution using a Z-score, or vice-versa is often based on the standard normal distribution.

B

Which of the following is true about sampling distribution? A. Sampling distribution is always normal. B. Sampling distribution is usually unobserved. C. Sampling distribution is the same as population distribution. D. Sampling distribution is the distribution of population parameter.

B

In a large sample situation (df>120), what is the appropriate critical value α* for a 95% confidence interval? A. 1.5 B. 3 C. 2 D. 1

C

The Binomial distribution describes the probability of having exactly k successes in n independent Bernoulli trials with probability of success p. Which of the following is false? A. There is only 1 way of getting n successes in n trials. B. There is only 1 way of getting n failures in n trials. C. There are n ways of getting n successes in n trials. D. There are n ways of getting 1 success in n trials.

C

We want to investigate if there is a gender pay gap among work study students at UNC. μf stands for average hourly pay for female students, μm stands for average hourly pay for male students. Which of the following is not a null hypothesis? A. μm−μf≠q0 B. μf−μm≠q0 C. μf≠qμm D. μf=μm

C

Which of the following is true about t-distribution? A. The t-distribution has a bell shape. B. It's more likely to fall within two SDs from the mean in a normal distribution than in a t-distribution. C. All of the above D. The tails of the t-distribution are thicker than the normal distribution.

C

Anna scored 85 in both Course A and Course B. Course A had a mean of 70, and standard deviation of 10. Course B had a mean of 80 and standard deviation of 5. If both courses were curved using Z score to determine final grade. A. Anna did better in course B than in course A. B. Anna got the same grade from these two courses. C. There is not enough information to tell whether she did better in Course A or Course B. D. Anna did better in course A than in course B.

D

The difference between confidence interval construction and t-test is: A. Under the interval estimate approach we predetermine the width of intervals of will contain the value of μ B. Under the interval estimate approach we predetermine the probability that intervals of a given width will not contain the value of μ C. Under hypothesis testing, we determine how probable a particular population mean is under a hypothesized value of x D. Under hypothesis testing, we determine how probable a particular sample mean is under a hypothesized value of μ

D

What is the probability that at least 2 people (1 match) out of 121 people share a birthday? A. it is impossible to know. B. 50/50 C. very low D. very high

D

When I can use z-test to replace t-test? A. When sample is not random. B. When sample is not independent. C. When sample size is small. D. When sample size is large.

D

Which of the following is NOT true about the Z-score of an observation? A. If x is an observation from a distribution N(µ, σ), we define the Z-score mathematically as Z=(x-µ)/σ B. If the observation is one standard deviation above the mean, its Z-score is 1. C. The Z-score of an observation is defined as the number of standard deviations it falls above or below the mean. D. If the observation is right at the mean, its Z-score is 1.

D

Which of the following is a not required assumption to use t-test? A. no obvious outliers. B. independent samples C. large sample size D. samples are normally distributed

D

Which of the following is true about population parameters? A. Population parameters are point estimates about population. B. Population parameters are the same as sample estimates. C. Population parameters are the uncertainties in the sample statistics. D. Population parameters are statistical quantities or characteristics of a population.

D