TF1. If the population standard deviation is unknown, we must use the z-distribution to construct a confidence interval estimate of the population mean.

TF2. Given a normal probability distribution, as the size of the standard deviation increases the normal curve gets narrower (more pointed and peaked).

TF3. The Continuity Correction Factor compensates for the error in approximating a discrete probability distribution using a smooth continuous normal curve.

_____4.We have been feeding fish in a pond. A sample of 35 fish showed that the mean weight was 321.6 grams with a standard deviation of 6 grams. What is the best point estimate the mean weight of all the fish in the pond in grams?

A. 35B. 402.7C. 6D. 321.6E. cannot be determined

_____5. The difference between the population mean and the mean of sample taken from that population is called:

A. a point estimateB. sampling errorC. an interval estimateD. none of theseE. standard error

TF6. Thesimple random sampleis the sampling technique most useful to our study of statistics.

TF7. The area under a normal curve represented by a z-score of 2.85 is .4978.

TF8. The Central Limit Theorem tells us that we can get a good estimate of population values based on samples taken from that population.

TF9. The shape of the z-distribution curve is broader and flatter than the curve that represents the t-distribution at a given significance level.

TF10. We can calculate the area within a uniform probability distribution, but it is not possible to calculate the area under a normal curve.

TF11. A value of +2.00 on the z-score scale corresponds to +2s on the standard deviation scale.

TF12. Sampling error tells us that and because of this it is not possible to get a good estimate of population value based on a sample from that population.

TF13. We must calculate degrees of freedom when we use the t-distribution to build a confidence interval estimate.

TF14. A z-score can be thought of as the number of standard deviation units in the distance from a given x value to the mean of the data set.

TF15. In PP 3.17 we confirmed that the JEAN district manager was correct in wanting a 30% stock of boot cut jeans.

TF16. Using a point estimate prevents you from knowing how good an estimate of the population parameter you have.

TF17. If the population is highly skewed, the distribution of sample means taken from that population will tend to approximate a normal distribution if the sample size is 20 or more.

TF18. In the Texaco PP 3.3b, the proportion of customers charging $54.00 or less was 4.2%.

TF19. As the confidence interval moves from 95% to 99% the resulting confidence interval distance gets bigger.

TF20. The formula for calculating degrees of freedom using the t-distribution isdf = n - 2.

TF21.When calculating the appropriate sample size to estimate a population proportion and the sample proportion "p" is unknown we set p = .50 and proceed.

TF22. When using the t-distribution to build a confidence interval estimate we must divide the desired confidence interval percentage by 2.

TF23. As the sample size increases the distribution of sample means taken from a given population gets more and more normally shaped.

TF24. Given a normally distributed data set where= 33 and x = 37, with a sample standard deviation s = 5.12 the resulting z-score is 0.78, when rounded to hundreds place.

TF25. A rate of return 0.03on your Cicero Select Mutual Fund investment means that the fund is losing money.