PSY 310, Section 06
Writing the Results Section
Key aspects of the Results section:
Provides a concise summary of your results
Does not report on raw data, but does include descriptive and inferential statistics
Does NOT offer an explanation or interpretation of the data (this comes later, in the Discussion
section). Just gives the expected results of statistical tests
Most technical section of the paper (primarily uses mathematical / statistical language)
Typically the shortest section of a paper
Includes both descriptive statistics and inferential statistics
Includes tables and figures to summarize data and display results
Some terms that are relevant to your Results section:
A. Variables:
Quantitative variable:
(also called a continuous variable
) – values are
ordered along a scale or continuum, and provide information about
magnitude. Example: IQ, age, time, scores on a test
Qualitative variable:
(also called a categorical variable)
– labels identify distinct
categories. Example: treatment group vs. control group, young vs. old, Democrats vs.
Republicans vs. Independents
B.
Descriptive Statistics:
using numbers to describe the population
1.
Measures of central tendency: where the scores fall
Mode
– the score that occurs most frequently
Median
– the point that divides the distribution into equal parts (“the
middle”). To compute, rank the scores from highest to lowest, then take the middle score
**Mean
(
M
) – average value of a set of scores/numbers. To compute,
add the scores and divide by the number of scores.
2.
Measures of variability: how scores differ from one another
Range
– the span of scores. Report the two endpoints of the distribution
**Standard deviation
– the average deviation from the mean. Measures the dispersion or
variation in a distribution. To compute, take the square root of the variance
3.
Percentages (if appropriate)
Example: The majority of participants will show no change: XX% will stop
drinking, YY% will stop smoking, and ZZ% will show no change.
1
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View Full DocumentPSY 310, Section 06
C.
Inferential Statistics:
using numbers to infer something about the population, to test your
experimental hypothesis(es)
**Standard significant levels for
p
(alpha) values are
p
< .05,
p
< .01
1. To test and report
DIFFERENCES:
•
t
test
– used to compare MEANS of two
groups.
Example:
t
(df) = X.XX,
p
< .05.

df = number of participants minus 1
o
Two types of
t
tests:

Independent groups
ttest
is used when you have
independent
samples
(e.g., males and females, freshman and seniors, etc.), meaning there are
different participants in each group.

Dependent groups t test
(also called
paired, correlated, or matched
) is used
when you want to compare two sets of data from the
same
sample of
individuals (e.g., prepost test, same participant at time one and time two,
etc.).
o
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 Spring '09
 LUHMANN
 Statistics, Democrats, Statistical significance, Ideal family size

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