BSLEC 2 Flashcards
Statistical procedures used to organize, summarize, and simplify data.
Descriptive Statistics
Does not allow conclusions made beyond the data analyzed
Descriptive Statistics
Comes in Count, Frequency, and/or Percent
Measures of Frequency
Shows how frequent something occurs
Measures of Frequency
Comes in Mean, Median, and Mode
Measures of Central Tendency
Use when there is a need to show an average or the most commonly indicated response
Measures of Central Tendency
Comes in Range, Variance, and Standard Deviation
Measures of Dispersion or Variation
dentifies the spread of scores by stating intervals
Measures of Dispersion or Variation
dispersed or “spread out” the data are. It is helpful to know when your data are so spread out that it affects the mean.
Measures of Dispersion or Variation
Percentile ranks, Quartile Ranks
Measures of Position
Use this when you need to compare scores to a normalized score (e.g., a national norm)
Measures of Position
Use when there is a need to show how a response was given
Measures of Frequency
Statistical measure to determine a single score that defines the center of the distribution; the goal is to find the single score that is most typical or most representative of the entire group
Central Tendency
Concept of an average or representative score – usually attempts to identify the “average” or “typical” individual
Central Tendency
There is no single, standard procedure for determining central tendency.
Central Tendency
Arithmetic average
MEAN
Greek letter of mean
µ
Amount that each individual gets when the total is distributed equally
MEAN
Balance point of a distribution
MEAN
Goal: To locate the midpoint of the distribution
MEDIAN
Definition and computations for a sample and for a population are the identical
MEDIAN
“customary fashion” or a “popular style”
MODE
Same as median, has no symbols
MODE
Same definition with sample and population mo
MODE
Distribution with two modes
Bimodal
Distribution with more than two modes
Multimodal
Provides a quantitative measure of the differences between scores in a distribution and describes the degree to which the scores are spread out or clustered together
Variability
Purpose of measuring variability
To obtain an objective measure of how the scores are spread out in a distribution
Usually, variability is defined in terms of___
distance
measures how well an individual score (or group of scores) represents the entire distribution.
Variability
means specific method of estimation
Measure
means deviation or difference of certain values from their central value
Dispersion
Distance covered by the scores in a distribution, from the smallest score to the largest score
Range
most obvious way to describe how spread out the scores are
Range
Most commonly used
Standard Deviation
Uses the mean of the distribution as reference point and measures variability by considering the distance between each score and the mean
Standard Deviation
represents the rate of divergence from the mean in a date set and is used a lot in trading
Standard Deviation
Measures the dispersion of set of data points around their mean
Variance
square root of the variance and provides a measure of the standard, or average distance from the mean.
Standard deviation
measure that indicates the extent to which the central 50% of values within the dataset are dispersed.
Interquartile Range
same way that the median divides a dataset into two halves, it can be further divided into quarters by identifying the upper and lower quartiles.
Interquartile Range
One quarter of the way along a dataset
Lower quartile
lies halfway between the median and the highest value in the dataset
upper quartile
found three quarters along the dataset
upper quartile
lies halfway between the median
lower quartile
provides a clearer picture of the overall dataset by removing/ignoring the outlying values.
interquartile range
most important distribution. It describes well the distribution of random variables that arise in practice, such as the heights or weights of people,
normal distribution
NORMAL DISTRIBUTION AKA ____
GAUSSIAN DISTRIBUTION
However, even if the data are not known to be exactly normal, but are known to be bell shaped, then the exact results stated above will be approximately true.
empirical rule.
An organized tabulation of the number of individuals located in each category on the scale of measurement
FREQUENCY DISTRIBUTION
