Vocabulary Stats for Bus. & Econ ch. 1
Terms
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 Statistics
 the art and science of collecting, analyzing, presenting, and interpreting data
 Stats in accounting
 validating every account can be too timeconsuming annd expensive. as common practice an audit staff selects a subset of the accounts called a sample. stats are used to see what the sample reflects on the whole of accounts
 Stats in Finance
 use statistical info to guide their their investment recommendations.
 Stats in Marketing
 electronic scanners at retail checkout counters collect data for a variety of marketing research applications, process data, and sell to manufactures
 Stats in Production
 From a sample group they check to see if units fall into an average that is between an upper and lower limit.
 Stats in Economics
 providing forecasts about the future of the economy or some aspect of it. Using Producer Price Index, unemployment rate, and manufacturing capacity utilization.
 Data
 the facts and figures collected, analyzed, and summarized for presentation and interpretation
 Data Set
 all the data collected in a particular study.
 Elements
 are the entities on which data are collected. i.e. an individual company stock
 variable
 characteristic of interest for the elements. a particular part of the element that is of interest
 Observation
 the set of measurements obtained for a particular element
 Scales of Measurement
 nominal, ordinal, interval, or ratio
 Nominal Scale
 When the data for a variable consist of labels or names used to identify an attribute of the element. i.e. Blood type B, or A, or so on
 Ordinal Scale

exibits the properties of nominal data and the order ofr rank of the data is meaningful.
i.e. good, fair, and poor  Interval Scale
 data show the properties of ordinal data and the interval between values is expressed in terms of a numeric value. i.e. scores on SAT 1120, 1050, 970
 Ratio Scale
 data has all the properties of interval data and the ratio of the two is meaningful. i.e. cereal from 2 companies: $4, $2. 1st comp. twice as much
 Qualitative data
 or categorical data. includes labels or names used to identigy an attribute of each element. nonnumeric or numeric.
 Quantitative data
 numeric values that indicate how much or how many.
 CrossSectional data
 data collected at the same or approximately the same point in time.
 Time Series data
 data collected over several time periods.
 2 types of Statistical Studies
 Experimentalidentify variable of intrest, then other variables are identified and controlled. Observationalmake no attempt to control the variables of interes
 Data Acquisition Error
 all data values obtained that is not equal to the true or actual value. transposition, erroneous data. always be aware of the possiblity.
 Descriptive Statistics
 Summaries of datatabular, graphical, or numerical. presented in a form that is easy for readers to understand
 Statistical Inference
 data from a sample to make estimates and test hypotheses about the characteristics of a population.
 Population
 the set of all elements of interest in a particular study
 Sample
 subset of the population
 Census
 process of conducting a servey to collect data for the entire population
 Sample Survey
 process of conducting a survey to collect data for a sample
 Cycle of Statistical Inference

1.Population, unknown adverage
2.sample of population
3.sample data, sample average
4.samp aver to estim pop aver