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### 70 Cards in this Set

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• Back
 The set of all elements of interest in a particular study Population Subset of population Sample The art and science of collecting, analyzing and presenting and interpreting data Statistics All the data collected in a particular study Data Set The entries on which data is collected Elements A charateristic of interrest for the elements Variable The set of measurments obtained for a particular element Observation Nominal Scale The scale of measurment for a variable when the data are labels or names used to identify an attribute of an element. Nominal data may be non numeric or numeric Ordinal scale The scale of measurement for a variable if the data exhibit properties of nominal data and the order or rank of the data is meaningful. Ordinal data may be numeric or non numeric. Interval scale The scale of measurement for data if the data demonstrate the properties of Ordinal data and the interval between the values is expressed as a fixed unit of measure. Interval data are always numeric. Ratio Scale The scale of measurement for a variable if the data demonstrate all the properties of interval data and the ratio of the two values is meaningful. Ratio data are always numeric. Categorical data Labels or names used to identiutefy an attribute of each element. Categorical data use either the nominal or ordinal scale of measurement and may be non numeric or numeric. Quantitative data NUmeric values that indicate how much or how many of something. Quantitative data are obtained using either the interval or ratio scale of measurement Quantitative variable A variable with quantitaive data Cross -sectional data Data collected at the same or approximately the same point in time. Time series data Data collected over several time periods Descriptive statistics Tabular, graphical, and numerical summeries of data The set of all elements of interest in a particular study. Population Sample A subset of the Population Census A survey to collect data on the entire Labels or names used to identiutefy an attribute of each element. This type of data use either the nominal or ordinal scale of measurement and may be non numeric or numeric. Categorical data The process of using data obtained from a sample to make estimates or test hypothesis about the characteristics of a population Statistical inference The process of using procedures from statistics and computer science to extract useful information from extremely large databases Data Mining A tabular summary of data showing the number (frequency) of items in each of several nonoverlapping classes Frequency of distribution Frequency of distribution A tabular summary of data showing the number (frequency) of items in each of several nonoverlapping classes Data Mining The process of using procedures from statistics and computer science to extract useful information from extremely large databases The process of using data obtained from a sample to make estimates or test hypothesis about the characteristics of a population Statistical inference Relative frequency Relative frequency of a class = Frequency of the class / n where n is the number of observations in the data set Frequency of the class / n where n is the number of observations in the data set Relative frequency Relative frequency multiplied by 100 Percent frequency Approximate class width (largest data value - Smallest data value) / Number of Classes pg 40 A graph of cumulative distribution showing data values on the horizontal axis and either the cummulative frequencies or the cumulative percent frequencies on the vertical axis Ogive Page 44 Ogive A graph of cumulative distribution showing data values on the horizontal axis and either the cummulative frequencies or the cumulative percent frequencies on the vertical axis pg. 44 Whree steps are necesary to define the classes for a frequency distribution 1. Determine the number of nonoverlapping classes 2. determine the width of each class 3. determine the class limits pg 39 A graphical device for presenting relative and percent frequency for categorical data. Pie chart Page 35 Cumulative frequency distribution Shows the NUMBER of data items with values less than or equal to the upper class limit of each class pg 43 Shows the NUMBER of data items with values less than or equal to the upper class limit of each class Cumulative frequency distribution Pg 43 A simple garphical summary of data in which each data value is represented by a dot above the horizontal axis . The horizontal axis shows the range for the data. Dot Plot Page 41 An exploratory data analysis used to show rank,order and shape of data simutaneously. Stem and Leaf display pg 48 The two steps to develop a stem and leaf display are . 1. Arrange the leading digits of each data value to the left of a vertical line 2. To the right of the vertical line record the last digit for each data value pg 49 A tabular summary of data for two variables Crosstabulation Pg 53 The frequency and relative frequency distributions constructed from the nargins of a crosstabulation table provide information about the variables. Do they shaed any light on the relationship of the variables? No they do not shed any light on the relationship between variables they provide information about each of the variables individually. Pg 55 Converting the entries in a crosstabualtion table into row or column percentages can provide into the _______ of the variables Relationship pg 55 The data from two or more crosstabulations is combined to form what kind of data that is used to form a summary crosstabulation to show how two variables are related Aggregated Page 56 The reversal of conclusions based on aggregated or unaggregated data is called Simpsons paradox Page 56 Graphical representation of the relationaship between two quantitative variables is called what? what do you call the line that provides an approximation of the relationship.? Scatter diagrahm and trendline Page 57 When dealing with categorical data name four ways to summarize the data using tabular methods Frequency distribution. relative frequency distribution, percent frequency distribution and crosstabulation tables page 64 When dealing with categorical data name two ways to summarize the data using graphical methods Bar charts and Pie charts Page 64 When summarizing data we divide data into two categories or types. What are they? Categorical data and Quantitative Data Page 64 When dealing with Quantitative data name five ways to summarize the data using graphical methods Dot plot Histogram Ogive Stem and Leaf Diagrahm Scatter Diagrahm When dealing with quantitative data name seven ways to summarize the data using tabular methods frequency distribution, relative frequency distribution,percent frequency distribution,cumulative frequency distribution, cumulative relative frequency distribution,cumulative percent frequency distribution and crosstabulation page 64 categorical data Labels or names used to identify categories of like items page 64 Labels or names used to identify categories of like items Categorical data Page 64 Quantitative data Numerical values that demonstrate how much or how many Page 64 Frequency distribution a tabular summary of data showing the number (frequency) of data values in each of several nonoverlapping classes page 33 and 64 A tabular summary of data showing the fraction or proportion of data values in each of several non overlapping classes Percent frequency distribution page 34 and 64 Percent Frequency Distribution a tabular summary of data showing the percentage of data values in each of several nonoverlapping classes pages 34 and 64 a tabular summary of data showing the percentage of data values in each of several nonoverlapping classes Percent Frequency Distribution pages 34 and 64 A graphical device for depicting qualitative data that have been summarized in a frequency, relative frequency or percent frequency distribution Bar Chart Page 35 A graphical device for presenting data summaries based on subdivision of a circle into sectors that correspond to the relative frequency of a class Pie Chart Page 35 A graphical presentation of a frequency distribution or percent frequency distribution or relative frequency distribution of quantitative data constructed by placing the class intervals on the horizontal axis and the frequencies, relative frequencies or percent frequencies on the vertical axis Histogram page 41 and 64 A tabular summary of quantitative data showing the number of data values that are less than or equal to the upper class limit of each class Cummulative frequency distribution Page 43 and 64 A tabular summary of quantitative data showing the fraction or proportion of data values that are less than or equal to the the upper class limit of each class Cumulative relative frequency distribution Page 44 and 64 A tabular summary of quantitative data showing the percentage of data values that are less than or equal to the upper class limit of each class Cumulative percent frequency distribution Page 44 and 64 A graph of cumulaitive distribution Ogive Page 44 and 64 Formula for Relative frequency Frequency of the class / n Page 34 and 64 Methods that use simple arithmetic and easy to draw graphs to summarize data quickly Exploratory data analysis page 48 and 64 An exploratory data analysis technique that simutaneously shows rank order and provides insight about the shape of the distribution of quantitative data Stem and Leaf display Page 48 and 64 A tabular summary of Data for two variables. The classes for one variable are represented by the rows ; the classes for the other variable are represented by the columns Crosstabulation Page 53 and 64 conclusions drawn from two or more seperate crosstabulations that can be reversed when the data are aggregated into a single crosstabulation Simpsons Paradox Page 56 and 64