Flashcards
CHAP 1
Cards in this deck (23)
- 1PopulationEntire collection of individuals or objects about which information is desired.
- 2SampleA subset of population selected for study.
- 3Descriptive StatisticsNumerical,graphical, and tabular methods for organizing and summarizing data.
- 4Inferential statisticsMethods for generalizing from a sample to a population.
- 5VariableAny characteristic whose value may change from one individual/object to another.
- 6DataResults from making observations on a single variable or on two or more variables.
- 7Univariate Data SetData set consisting of observations on a single value.
- 8CategoricalAlso "Qualitative". Univariate data set with individual observations that are categorical (nonnumerical) responses.
Ex: Gender/Affiliations/Ethnicity - 9NumericalAlso "Quantitative". Univariate set in which individual observation are numerical.
Ex: Age/Height/Rank - 10Bivariate DataData set consisting of observations on two different simultaneous values.
Ex: Recording height AND weight. - 11Multivariate Data SetData set resulting from obtaining a category or number for two or more values.
Ex:Height,Weight, Pulse and Blood pressure for each individual in a group. - 12Discrete Numerical VariableThe possible values of the variable correspond to isolated points along the number line.
Determined by counting.
Ex: Number of petals on flower. - 13Continuous Numerical VariableThe possible values of the variable form an entire interval on the number line.
Determined by measurements.
Ex: Time for popcorn to pop. - 14Frequency DistributionCategorical Data.
Table that displays frequencies and/or relative frequencies, for each of the possible values of a categorical variable. - 15FrequencyNumber of times a category appears in a data set.
- 16Relative frequencyProportion of the observations that belong to a particular category.
Table is also referred as relative frequency distribution. - 17Relative Frequency FormulaFrequency / Number of Observation in Data Set.
- 18Bar GraphGraph of a frequency distribution for a categorical data set. Each category is represented by a bar, and the area of the bar is proportional to the corresponding frequency/relative frequency.
- 19Bar Charts How to Construct1. Draw a horizontal axis. Write category names below line.
2. Draw vertical axis, label scale using either frequency or relative frequency.
3.Place rectangle bar above category label.
Height: determined by scales
Width: Similar to ALL bars. - 20Bar Graph 1.When to use? 2.Why is width important? 3.What to look for?1. Categorical Data
2. With same width, both height and area of the bars are proportional to (relative) frequency.
3. Frequently and infrequently occurring categories. - 21DotplotsA graph to display numerical data when data set is small. Each observation is represented by a dot on or above a horizontal measurement scale.
- 22Dotplots How to Construct?1.Draw a horizontal line and mark it with a measurement scale.
2. Locate each value in the data along the scale, and represent it by a dot. If 2+ observations in a value, stack dots vertically. - 23Dotplots 1.When to use? 2.What to look for ?1. Small numerical data sets.
2. Information about:
-A representative or typical value in the data set
-Extent to which a the data values spread out
-Nature of the distribution of values along a number line
Presence of unusual values in the data set
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- University PSC 103 A Flashcards on CHAP 1, created by Jessie Lemoine on 26/01/2015.
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- Jessie Lemoine
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