Download Results & Data Analysis

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

History of statistics wikipedia, lookup

Regression toward the mean wikipedia, lookup

Student's t-test wikipedia, lookup

Taylor's law wikipedia, lookup

Bootstrapping (statistics) wikipedia, lookup

Time series wikipedia, lookup

Resampling (statistics) wikipedia, lookup

Misuse of statistics wikipedia, lookup

Degrees of freedom (statistics) wikipedia, lookup

Psychometrics wikipedia, lookup

Foundations of statistics wikipedia, lookup

Analysis of variance wikipedia, lookup

Transcript
RESULTS & DATA ANALYSIS
Descriptive Statistics

Descriptive (describe)
 Frequencies
 Percents
 Measures
 mean
 median
 mode
of Central Tendency
Measures of Spread

Range
 Nominal
data = number of responses in each
category (A’s = 4, B’s = 7, C’s = 21, D’s = 1, F’s=2)
 Other data = difference between responses for
the greatest and least numeric values (Age of
oldest is 104 and youngest is 18. Range =86 years)

Tertiles, Quartiles, Quintiles
 Interquartile Range (IQR)
 Range for the 25th to 75th
percentiles
which captures the middle 50%
Measures of Spread
 Standard
Deviation – describes, on
average, how much individual values differ
from the mean
 Standard
Scores or Z-scores – describes
how many SD’s away from the sample
mean an individual score or response is
Normal Distribution
68% of individuals
95% of individuals
>99% of individuals
Sample
Mean
-3 SD
-2 SD
-1 SD
+1
SD
+2
SD
+3
SD
Inferential Statistics
(Comparative)

Based on Probability

Tests of significance: are observed differences
real differences or simply the result of chance
 t-test:
test difference between means of two groups
(t statistic)
 ANOVA
(Analysis of Variance): test difference among
three of more independent groups (F statistic)
Interpreting p-values or
probability value


Used to decide whether the results observed are
likely to reflect real differences between groups
The standard is to use α = 0.05 or 5% (1 in20)
 t = 1.11, p =0.042
 t = 1.02, p = 0.051


Probability that results observed have occurred by
chance alone
α = probability of Type I error (finding statistical
significance when in reality there is none)
Significance

Statistical

Practical

Clinical
Parametric and Non-Parametric

Parametric = DV is some measured quantity
(ratio or interval) so it makes sense to calculate
means and SD
 You
can draw bell curves through the data defined
by two parameters…the mean and SD….hence
parametric (beside, near)

Non-Parametric = DV is count or rankings so
means and SD have no meaning (e.g. The
average religion of Americans is 2.67)
Parametric Tests

T-tests

ANOVA (analysis of variance)

Linear Regression or Multiple Linear Regression

ANCOVA (analysis of covariance) – combines
regression and analysis of variance
Non-Parametric Tests

Chi-square

Logistic Regression

Log-linear analysis