Stats Ch 5, 6, & 7

the distribution of values taken by the statistic in all possible samples of the same size (n) are taken from the same population

A. The distribution of the sample mean tends to be skewed right of left B. The mean of the sample means is the population mean C. The sample means target the value of the population mean D. The expected value of the sample mean is equal to the population mean A

A. The sample variances target the value of the population variance B. The distribution of sample variances tends to be a normal distribution C. The mean of the sample variances is the population variance D. The expected value of the sample variance is equal to the population variance B

the distribution of sample proportions, with all samples having the same sample size n taken from the same population

Variance Median Mean Proportion Median

Population with any distribution, the distribution of the sample means approaches a normal distribution as the sample size increases

standard deviation of the sampling distribution of sample means is

A. The distribution of the sample data will approach a normal distribution as the sample size increases B. The mean of all sample means is the population mean mu C. The distribution of the sample mean x-bar will, as the sample size increases, approach a normal distribution D. The standard deviation of all sample means is the population standard deveatioj divided by the square root of the sample size A

If, under a given assumption, the probability of a particular observed event is extremely small (such as less than 0.05), we conclude that the assumption is probably not correct.

A. The original population is normally distributed, then for any sample size n, the sample means will be normally distributed B. If the original population is not normally distributed and n>30, then the population distribution is normally distributed C. If the distribution of the sample means is normally distributed, and n>30, then the population to on distribution is normally distributed D. The distribution of the sample means gets closer to a normal distribution as the sample size n gets larger C

A. Visual inspection of a histogram to see if it is roughly bell-shaped B. Identifying outliers C. Constructing a graph called a normal quantile plot D. Checking that the probability of an event is .05 or less D

Graph of Points (x,y) where each x value is from the original set of sample data, and each y value is the corresponding z score that is a quantile value expected from the standard normal distribution.

A. The criteria for interpreting a normal quartile plot should be used more strictly for large samples B. The population distribution is normal if the pattern of points is reasonably close to a straight line C. The population distribution is not normal if the points show some systematic pattern that is not a straight-line pattern D. If the plot is bell-shaped, the population distribution is normal D

A. If values are converted to standard z-scores, then procedures for working with all normal distributions are the same as those for the standard normal distribution B. The area in any normal distribution blinded by some score x is the same as the area bounded by the equivalent z-score in the standard normal distribution C. A z-score is an area under the normal curve D. A z-score is a conversion that standardized any value from a normal distribution to a standard normal distribution C

the right side of the horizontal scale of the graph

a z-score corresponding to an area located entirely in the left side of the curve

A data value associated with an area of .85 to its left