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the difference between qualitative and quantitative variables
qualitative variables to NOT use numbers, quantitative variables DO use numbers
The 5 component parts of the science of statistics
The level of measurement that presumes that one classification is ranked higher than another
Why are unequal class intervals sometimes used in frequency distribution
to avoid a large number of empty classes
The incomes of a group of 50 loan applicants are obtained. Which level of measurement is income
Rank the measures of dispersion in terms of their relative computational difficulty from least to most difficult
Range, mean deviation, variance
A negatively skewed distribution is not symmetrical. The long tail is to the left or in the negative direction
For which measure of central location will the sum of the deviations of each value from the data;s average will always be zero?
For a set of grouped or ungrouped data, which measures of central location always have only one value
Mean and Median
a row of a stem-and-leaf chart appears as follows:
3I 0 1 0 5 7 9. Assume that the data is rounded to the nearest unit.
The maximum value in the class is 39
The test scores for a class of 147 students are computed. What is the location of the test score associated with the third quartile?
The coefficient of variation for a set of annual incomes is 18%; the coefficient of variation for the length of service with the company is 29%. What does this indicate?
More dispersion in the lengths of service compared with incomes
A probability is a number from -1 to +1 inclusive that measures one's belief than an even resulting from an experiment will occur
The complement rule states that the probability of an event not occurring is equal to one minus the probability of its occurrence
In stratified sampling, a population is divided into strata using naturally occurring geographic or other boundaries. Then strata are randomly selected and a random sample is collected from each strata
Sampling a population is often necessary because the cost of studying all the items in the population is prohibitive
It is often not feasible to study the entire population because it is impossible to observe all items in the population
A simple random sample assumes that each item or person in the population has an equal chance of being included
In cluster sampling, a population is divided into subgroups called clusters and a sample is randomly selected from each cluster
If the size of a sample equals the size of the population, we would not expect any error in estimating the population parameter
We can expect some difference between sample statistics and the corresponding population parameters. This difference is called the sampling error
A Sampling distribution of the means is the probability distribution consisting of a list of all possible sample means of a given sample size selected from a population and the probability of occurrence associated with each sample mean
The central limit theorem implies that sampling with an adequate sample size provides good estimates of population parameters
The central limit theorem implies that sample of size one or two are adequate to estimate population parameters
If a population is not normally distributed, the sampling distribution of the sample means tends to approximate a normal distribution
Based on the sampling distribution of the means and the central limit theorem, the sample mean can be used as a good estimator of the population mean, assuming that the size of the sample is sufficiently large.
An estimate of the population mean based on a large sample is less reliable than an estimate made using a small sample
If the sample size keeps getting larger and larger and finally equals the size of the population, there would be no error in predicting the population mean because the sample size and the size of the population would be the same
What is it called when all the items in a population have a chance of being selected in a sample?
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