Quentin Cheeks Math 221 Prof. Jim Chaires

Quentin Cheeks
Math 221
Prof. Jim Chaires
Chapter 1 Keywords
1. Business Statistics: the collection, summarization, analysis and reporting of
numerical findings relevant to a business decision or situation.
2. Population: the entire set of people or objects of interest.
3. Sample: the smaller number of the people or objects that exist within the larger
4. Representative: a sample in which members tend to have the same characteristics
as the population from which they were selected.
5. Census: a sample is so large as to include all members of the population.
6. Statistics: measured characteristics of the sample.
7. Parameter: numerical characteristics of the population, such as the mean,
standard deviation or proportion.
8. Quantitative variables: to determine how much of something is possessed, not
just whether it is possessed.
9. Discrete quantitative variables: can take on only certain values along an interval,
with the possible values having gaps between them.
10. Continuous quantitative variables: can take on a value at any point along an
11. Nominal scale: uses numbers only for the purpose of identifying membership in a
group or category.
12. Ordinal scale: numbers represent “greater than” or “less than” measurements,
such as preferences or rankings.
13. Interval scale: has a unit of measurement that permits us to describe how much
more or less on object possess than another.
14. Ratio scale: similar to the interval scale, but also has an absolute zero and
multiples are meaningful.
Chapter 3 Keywords
1. Measure of central tendency: numbers describing typical data values.
2. Measure of dispersion: numbers that describe the scatter of data.
3. Arithmetic mean: referred to as the arithmetic average or simple the mean; the
addition of the values given and then divided by the number of values given.
4. Weighted mean: each data value is weighted according to its relative importance.
5. Median: the value that has just as many values below it as it does above it.
6. Mode: a value that occurs with the greatest frequency.
7. Skewness: refers to the tendency of the distribution to “tail off” to the right or
left; ex: symmetrical distribution, positively skewed distribution, negatively
skewed distribution.
8. Range: difference between the highest and lowest values.
9. Midrange: the average of the lowest data value and the highest value.
10. Quantiles: separate data into equal size groups in order of numerical value.
11. Mean absolute deviation: the average of the absolute values of differences from
the mean.
12. Variance: a common measure of dispersion includes all data values and is
calculated by a mathematical formula.
13. Standard deviation: the positive square root of the variance of either a population
or a sample is a quantity
14. Standardizing: the data is involved in expressing each data value in terms of its
distance from the mean.
15. Coefficient of variation: indicates the relative amount of dispersion in the data.
16. Grouped data: convenient summary of raw data, but it loses some of the
information originally contained in the data.
17. Coefficient of correlation: a number that indicates both the direction and the
strength of the linear relationship between the dependent variable (y) and the
dependent variable (x)