Brown Ch 4; Portney Ch 22 Flashcards
M, x
mean of a sample
M (sd)
Mean and standard deviation of a
samples
s, sd, o
standard deviation of a sample
s2
Variance of a sample
N, n
Number of participants
provide an analysis of the data that helps describe, show, or summarize it in a meaningful way such that patterns can emerge
Descriptive statistics
techniques that allow us to use study samples to make generalizations that apply to the population
Inferential statistics
used to describe how often something occurs.
•Typically, the actual number or count is provided, along with a percentage.
Frequencies
the count that indicates how often something occurs within a given interval
frequency distribution
presents the data in columns and rows so it can be interpreted horizontally and vertically.
•Graphs present information pictorially, allowing the reader to “see” patterns.
frequency table
frequency distribution represented in a bar graph.
•The vertical (y) axis identifies the frequency with which a score occurs.
•The horizontal (x) axis presents the values of the scores.
histogram
only appropriate for representing frequencies when all of the “slices,” or categories, of the pie total 100%
Pie chart
describes the location of the center of a distribution.
Measure of central tendency
value that occurs most frequently in the distribution
Mode
the same as the average and balances the scores above and below it
Mean
the score value that divides the distribution into the lower and upper halves of the scores
Median
the spread of the data and is another way to compare data sets
Variability
measure of variability that indicates the lowest and highest scores
Range
the expression of the amount of spread in the frequency distribution and the average amount of deviation by which each individual score varies from the mean
Standard deviation
an estimate of the standard deviations of multiple samples
Standard error of the mean
Distributions of scores differ in terms of …
their measures of central tendency and variability
The central tendency and variability of a data set provide…
important information for understanding a particular distribution of scores
In a normal distribution, data points are distributed in a
symmetrical, bell-shape curve
the spread of scores lacks symmetry, such that one end of the curve is longer than the other
Skewed distribution
mode is a lower score than the mean, and the median falls between the mode and mean; there are more low scores, and the right tail is longer.
Positive skew
mode is a higher score than the mean, and the median falls between the mode and mean; there are more high scores, and the left tail is longer.
Negative skew
Used to characterize the shape, central tendency, and variability within a set of data.
Descriptive Statistics
measures of population characteristics
Parameters
descriptive index from sample data
Statistics
Measures of Variability
●Range - Minimum to maximum
●Percentiles and quartiles
●Box plots
●Variance
●Standard deviation
●Coefficient of variation
Examples of Descriptive Statistics
Coin rotation test
Shapes of Distributions
●Normal (B)
●Skewed to right (A)
●Skewed to left (C)
Coin Rotation Test (CRT) measures
Frequency distribution and cumulative percent
Box represents the interquartile range
Horizontal line at median
“Whiskers” show minimum and maximum scores
Shows group B more variable
Box plots
Also known as a bell-shaped distribution or Gaussian distribution.
The normal distribution
68% of the scores are within
1 SD of the mean
95% of the scores are within
2 Sd of the mean
99% of scores are within
3 Sd of the mean
A standardized score based on the normal distribution
Allows for interpretation of a score in relation to the sample mean and variance
Z-scores
standard deviation units
z
