Unit 2 Flashcards
Frequency
counting the number of times a score occurs
Symbol = 𝑓
Distribution
any organized set of data (i.e., scores)
4 ways to organize data:
- Simple frequency
2.Relative frequency - Cumulative frequency 4.Percentile
A Bar Graph is
Used for nominal or ordinal data
Bars DO NOT touch
A Histogram is
Used for a small number of scores, interval, or ratio data
Bars DO touch
A polygon is
Use with a large number of interval or ratio scores
Continuous variable
Relative Frequency
the frequency of all scores at or below a particular score
Percentile
the percent of all scores in the data at or below a particular score
Grouped Frequency Distribution:
Method to describe large data sets
How many intervals in a grouped FD table?
10-12
What is the interval width in a grouped FD table?
Simple value…. 2, 5, 10, or 20
Central Tendency
Calculating one number that summarizes everyone’s score
Measures of Central Tendency:
Mean, Median, Mode
The Normal Distribution
Represents the ideal distribution of scores in a population
- The basis of inferential statistics
Range
The most frequently occuring score
Kurtosis
Still symmetrical, refers to the distribution of scores relative to the middle
Skewed Distribution
- Only one pronounced tail
- Measure of the degree of asymmetry
When is the mode used?
Nominal/ordinal scales of measurement
Mode limitations:
- more than 2 modes, difficult to describe the data
- Skewed distributions
The Median
The score at the 50th percentile (50% of all scores at or below the median)
Uses: nominal and ordinal scores, and skewed distributions
The Mean - most commonly used
Refers to the score located at the mathematical centre of the distribution
Mean (average) symbols
X̅ (sample)
μ = population
Measures of Variability
Describes the extent to which scores in a distribution differs from each other
The Range
The distance between the 2 most extreme scores in a distribution
Score Deviation (standard deviation)
Refers to the “distance” between an individual score and a sample mean
The magnitude of score’s deviation is referred to as an
Error
Deviation formula
Score subtract the average: x - X
Calculating SD steps:
- Calculate average (mean)
- Compute deviations = x - x̄
- Square the deviation values
- Calculate sum of squares (SS)
- Divide SS by (N-1) variance
- Square root the variance - standard deviation
Normal Distribution and Z-Score
Any known score (x) can be expressed as a z-score by knowing the mean and SD of the distribution
