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### 29 Cards in this Set

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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