the difference between qualitative and quantitative variables
qualitative variables to NOT use numbers, quantitative variables DO use numbers
only has one category
must have at least one category
The 5 component parts of the science of statistics
What are 2 types of statistics
descriptive and inferential
A varibale that can assume any value within a specific range is
4 levels of measurement
nominal ordinal interval ratio
The level of measurement that presumes that one classification is ranked higher than another
A population in the statistical sense does not always refer o people
to infer something about a population we usually take a ________ from the population
The highest level of measurement is
the type of chart that best represents relative class frequencies is
when a class interval is expressed as 100 up to 200
observations with values of 200 are EXCLUDED
the relative frequency for a class is computed as the
class frequency divided by total frequency
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
The standard deviation is the square root of the variance
Rank the measures of dispersion in terms of their relative computational difficulty from least to most difficult
Range, mean deviation, variance
A distribution that has the same shape on either side of the center is said to be symmetrical
A negatively skewed distribution is not symmetrical. The long tail is to the left or in the negative direction
The principal difference between the interval and ratio scale has a meaningful zero point
Which word is not part of the definition of descriptive statistics
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?
What statistics are needed to draw a box plot?
minimum, maximum, median, first and third quartiles
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
What is the possible range of values for the coefficient of variation?
0% - 100%
The probability of 2 or more events occurring concurrently is called
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
The standard error of the mean can also be called a sampling error
When systematic random sampling is used, the central limit theorem cannot be applied
When using stratified random sampling, the sampling error will be zero
In cluster sampling, a population is divided into subgroups called clusters and a sample is randomly selected from each cluster
If probability sampling is done, each item in the population has a chance of being chosen
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?
What is the difference between a sample mean and the population mean called?