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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 population. 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 interval. 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)