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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 time-consuming 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.
Cross-Sectional 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
Experimental-identify variable of intrest, then other variables are identified and controlled. Observational-make 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 data-tabular, 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

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