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30 Cards in this Set
- Front
- Back
Statistics
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The branch of mathematics that examines ways to process and analyze data.
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Variables
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Characteristics of items or individuals.
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Population
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Consists of all the members of a group about which you want to draw a conclusion.
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Sample
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The Portion of the population selected for analysis.
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Parameter
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is a numerical measure that describes a characteristic of a population
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Statistic
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A Numerical measure that describes a characteristic of a sample.
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Descriptive Statistics
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focuses on collecting, summerizing, and presenting a set of data. A
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Inferential Statistics
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uses sample data to draw conclusions about a population.
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Primary Sources
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The data when it is collected by the one using the data for analysis.
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Secondary Sources
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When the individual using the data has gathered their sources from another source.
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Data
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The observed values of variables.
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Categorical Variables
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Yield categorical responses, such as yes and no.
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Numerical Variables
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Yield numerical responses, such as height, weight.
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Discrete Variables
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Produce numerical responses (counting)
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Continuous Variables
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Produce numerical responses (measuring)
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Central Tendency
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The extent to which all of the data values group around a central value.
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Variation
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The amount of dispersion or scattering of values away from a central value.
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Shape
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The pattern of the distribution of values from the lowest to the highest value.
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Arithmetic Mean
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The most common measure of central tendency. Serves as a balance point for all data
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Mode
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The value in a set of data appears most frequently.
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Quartiles
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Split a data set into four equal parts.
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Range
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Is the simplist numerical descriptive measure of variation in a set of data.
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Geometric Mean
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Measure the rate of change of a variable over time. The geometric mean is the nth root of the product of n values.
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Interquartile Range
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Also called the midspread, is the difference between the third and the first quartiles in a set of data.
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Sample Variance
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Is the sum of the squared differences around the mean divided by the sample size minus one.
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Sample Standard Deviation
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Is the square root of the sum of the mean divided by the sample size minus one.
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Coefficient of Variation
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Is the relative measure of variation that is always expressed as a percentage rather than in terms of units of the particular data. Denoted by CV
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Z Scores
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the difference between the value and the mean divided by the population size N
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Population Variance
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measure variation in population. This is represented by sigma squared.
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The Empirical Rule
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Quick Estimation of the spread of data given the mean and standard deviation of a set of data that follows normal distribution.
+/- 1 SD = 68% +/- 2 SD = 95% +/- 3 SD = 99.7% |