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the difference between qualitative and quantitative variables

qualitative variables to NOT use numbers, quantitative variables DO use numbers

mutually exclusive

only has one category


must have at least one category

The 5 component parts of the science of statistics

2. Organizing
4. interpreting

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

pie chart

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?

Geometric Mean

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

joint probability

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?

Random sampling

What is the difference between a sample mean and the population mean called?

Sampling error

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