Chapter One

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What are statistics? The art and science of collecting, analyzing, presenting, and interpreting data.
What is data? The facts and figures collected, analyzed, and summarized for presentation and interpretation.
What is a data set? All the data collected in a particular study?
What are elements? The entities on which data are collected?
What is a variable? A characteristic of interest for the elements.
What is an observation? The set of measurements obtained for a particular element.
What is nominal scale? 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 nonnumerical or numerical.
What is ordinal scale? The scale of measurement for a variable if the data exhibit the properties of nominal data and the order or rank of the data is meaningful. Ordinal data may be nonnumerical or numerical.
What is interval scale? 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 numerical.
What is ratio scale? 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 numerical.
What is categorical data? 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 nonnumerical or numerical.
What is quantitative data? Numerical values that indicate how much or how many of something. Quantitative data are obtained using either the interval or ratio scale of measurement.
What is a categorical variable? A variable with categorical data.
What is a quantitative variable? A variable with quantitative data.
What is cross-sectional data? Data collected at the same or approximately the same point in time.
What are time series data? Data collected over several time periods.
What are descriptive statistics? Tabular, graphical, and numerical summaries of data.
What is a population? The set of all elements of interest in a particular study.
What is a sample? A subset of the population.
What is a census? A survey to collect data on the entire population.
What is a sample survey? A survey to collect data on a sample.
What is statistical inference? The process of using data obtained from a sample to make estimates or test hypotheses about the characteristics of a population.
What is data mining? The process of using procedures from statistics and computer science to extract useful information from extremely large databases.
Discuss the differences between statistics as numerical facts and statistics as a discipline or field of study. The term statistics refers to numerical facts such as averages, medians, percents, and index numbers that that help us understand a variety of business and economic situations. Statistics as a discipline is defined as the art and science of collecting, analyzing, presenting, and interpreting data.
What is discrete quantitative data? Quantitative data that measure how many (e.g., number of telephone calls received in 15 minutes).
What are continuous qualitative data? Quantitative data that measure how much (e.g., weight or time) are continuous because no separation occurs between the possible data values.
What are observational or nonexperimental statistical studies? Statistical studies that make no attempt to control the variables of interest. A survey is perhaps the most common type of observational study.
What is an experimental statistical study? A study in which a variable of interest is first identified. Then one or more other variables are identified and controlled so that data can be obtained about how they influence the variable of interest.
What are outliers? Data with unusually large and small values. This data should be reviewed for possible data errors.
What is the most common numerical descriptive statistic? The average or mean.
What is data warehousing? The process of capturing, storing, and maintaining data.
Method to evaluate statistical model reliability? First, divide the sample data set into two parts: a training data set and a test data set. If the model developed using the training set data is able to accurately predict values in the test data, we say that the model is reliable.
Forms of unethical behavior in statistics? Improper sampling, inappropriate analysis of the data, development of misleading graphs, use of inappropriate summary statistics, and/or a biased interpretation of the statistical results.
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