Stats Terms: Pop., Sample, Central Tendency, Variability, Probability, Normal Dist. - Prof, Study notes of Humanities

An overview of basic statistics terms, including population and sample, measures of central tendency (mean, median, mode), measures of variability (range, sample variance, sample standard deviation), probability concepts (experiment, simple event, sample space), and the normal distribution. It covers definitions, examples, and key properties.

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Pre 2010

Uploaded on 09/17/2009

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FCS 504
Spring 09
Basic Statistics Terms
Population- set of data that characterizes some phenomenon
e.g. The weights of each 5-year-old in Idaho
Sample- subset of data selected from a population
e.g. The weights of 100 5-year-olds in Idaho
Statistical inference- a decision, estimate, prediction, or generalization about the population
based on information contained in a sample
e.g. Estimation of the average weight of all 5-year-olds based on the sample
Measures of Central Tendency for Quantitative Data:
Mean- is the sum of the measurements divided by the number of measurements in a data set. The
symbol is an x with a line over it.
Median- is the middle number when the measurements in a data set are arranged in ascending or
descending order.
Mode- is the measurement that occurs most frequently in the data set.
If median is less than the mean: several larger values skewed data to the right
If median equals mean: symmetrical data set
If median is greater than the mean, several smaller values skewed data to the left
Measures of Variability:
Range- the largest measurement minus the smallest measurement.
Sample Variance- for a sample of n measurements is equal to the sum of the squared distances
from the mean divided by (n-1). The symbol is s2.
Sample Standard Deviation- The positive square root of the sample variance. The symbol is s.
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FCS 504

Spring 09 Basic Statistics Terms Population - set of data that characterizes some phenomenon e.g. The weights of each 5-year-old in Idaho Sample - subset of data selected from a population e.g. The weights of 100 5-year-olds in Idaho Statistical inference - a decision, estimate, prediction, or generalization about the population based on information contained in a sample e.g. Estimation of the average weight of all 5-year-olds based on the sample

Measures of Central Tendency for Quantitative Data:

Mean - is the sum of the measurements divided by the number of measurements in a data set. The symbol is an x with a line over it. Median - is the middle number when the measurements in a data set are arranged in ascending or descending order. Mode - is the measurement that occurs most frequently in the data set. If median is less than the mean: several larger values skewed data to the right If median equals mean: symmetrical data set If median is greater than the mean, several smaller values skewed data to the left

Measures of Variability:

Range - the largest measurement minus the smallest measurement. Sample Variance - for a sample of n measurements is equal to the sum of the squared distances from the mean divided by (n-1). The symbol is s^2. Sample Standard Deviation - The positive square root of the sample variance. The symbol is s.

Probability Terms Experiment - process of making an observation or taking a measurement. Simple event - most basic outcome of an experiment. Sample space - of an experiment is the collection of all its simple events. Two rules of assigning probabilities:

  1. All simple event probabilities must lie between 0 and 1.
  2. The probabilities of all the simple events within a sample space must sum to 1 Branen definition: Probability - What are the chances? Normal (Parametric) Distribution: Mean=Median= Mode Symmetrical 68% of all values fall between one SD below mean & one SD above mean 95% of all values fall between two SD below mean & two SD above mean Central Limit Theorem - For samples of sufficiently large size, the real distribution of MEANS is almost always approximately normal. The original variable can have any kind of distribution.