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Business Analytics Chapters 1 – 3 (rated 100% correct.
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Business Analytics Chapters 1 – 3 (rated100% correct.
Chapter 1 ANS - Data & Statistics
Statistics ANS - The art and science of collecting, analyzing, presenting, and interpreting data.
statistics refers to ANS - numerical facts such as averages, medians, percentages, and maximums that
help us understand a variety of business and economic situations.
Data ANS - The facts and figures collected, analyzed, and summarized for presentation and
interpretation.
Data Set ANS - All the data collected in a particular study.
Elements ANS - The entities on which data are collected.
Variable ANS - A characteristic of interest for the elements.
Observation ANS - The set of measurements obtained for a particular element.
The Scales of measurement:
(More difficult as you go down the list) ANS - Nominal
Ordinal
Interval
Ratio
,Nominal ANS - The scale of measurement for a variable when the data are labels or names used to
identify an attribute of an element. Nominal data may be nonnumeric or numeric.
Scales of measurement can be nominal even if the data appears as ANS - numerical values.
Ordinal ANS - The scale of measurement for a variable if the data exhibit the properties of nominal data
and the order or rank o the data is meaningful. Ordinal data may be nonnumeric or numeric.
Ex. AAA, AA, A, BBB, BB, B, etc.
Interval ANS - The scale of measurement for a variable if the data demonstrate the properties of ordinal
data and the interval between values is expressed in terms of a fixed unit of measure. Interval data are
always numeric.
o Ex. SAT, IQ, & ACT scores
Interval Scale is always ANS - numerical.
Ratio ANS - The scale of measurement for a variable if the data demonstrate all the properties of interval
data and the ratio of two values is meaningful. Ratio data are always numeric.
Ratio data are always ANS - numeric.
Give a few examples of ratio data: ANS - Distance, ratio, weight, and time.
The scale of ratio data requires a (blank) value. ANS - Zero
Data can be classified as either ANS - categorial or quantitative.
Categorical Data ANS - Labels or names used to identify an attribute of each element. Categorical data
use either the nominal or ordinal scale of measurement and may be nonnumeric or numeric.
, Categorical data is obtained by either ANS - nominal or ordinal scales of measurement.
Quantitative Data ANS - Numeric values that indicate how much or how many of something.
Quantitative data are obtained using either the ANS - interval or ratio scale of measurement.
Categorical Variab ANS - A variable with categorical data.
Statistical analysis is limited.
Quantitative Variable ANS - A variable with quantitative data.
Arithmetic operations provide meaningful results for quantitative variables.
Cross-sectional Data ANS - - Data collected at the same or approximately the same point in time.
Ex. Data detailing the number of building permits issued in November in 2013 in each county
Time Series Data ANS - Data collected over several time periods.
o Ex. Number of building permits issued in Lucas County, Ohio in 2013.
- The number of observations is always the same as the number of elements.
- The number of measurements obtained for each element equals the number of variables
Data Sources ANS - Can be obtained from existing sources, by conducting observational study, or by
conducting an experiment.
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