|
Statistics
Prism offers a more comprehensive set of tools to analyze your data
than any other scientific graphics package.
While it won't replace a heavy-duty statistics
program, Prism lets you
easily perform basic statistical tests commonly
used by laboratory and
clinical researchers.
Prism offers t tests, nonparametric comparisons,
one- and two-way ANOVA, linear and nonlinear
regression, analysis of contingency tables,
and survival analysis. See a complete lists
of available tests.
Unlike other programs, Prism provides statistical
help when you need it. Press "Learn" from any data analysis dialog and
Prism's online documentation will explain the
principles of the analysis to help you make appropriate
choices. Once you've made your choices, Prism
presents the results on organized, easy-to-follow
tables. If you need help understanding the statistical
terminology in the results table, Prism's unique
analysis checklists take you to analysis explanations
and help you check to make sure you chose an
analysis appropriate for your experimental design.
The
Prism documentation goes beyond anything you
would expect. More than half of it is devoted to thorough explanations
of basic statistics and nonlinear curve fitting, to teach you what
you need to know to appropriately analyze your data.
The Prism 5 help system is a wonderful resource for learning about statistics. Our Guided Examples teach you how to think about statistics, as well as how to use Prism. All the examples use sample data built-in to the program, so you can easily work through the examples without any tedious data entry. There are more than a dozen examples ranging from a simple unpaired t test to repeated measures two-way ANOVA, survival analysis, contingency tables and more.
Guided examples: Statistical
analyses
Available tests:
Statistical comparisons
- Paired or unpaired t tests
- Mann-Whitney or Wilcoxon tests
- Ordinary or repeated measures one-way ANOVA with
Tukey, Newman-Keuls, Dunnett or Bonferroni post
tests, or the post-test for trend
- Kruskal-Wallis or Friedman nonparametric one-way
ANOVA with Dunn's post test
- Fisher's exact test or the chi-square test. Calculate
the relative risk and odds ratio with confidence
intervals
- Two-way ANOVA, even with missing values with
some post tests
- Repeated measures two-way ANOVA with some post
tests
- Kaplan-Meier survival analysis. Compare curves
with the log-rank test (including test for trend)
Column statistics
- Calculate min, max, quartiles, mean, SD, SEM,
CI, CV, Geometric mean with Confidence Intervals
- Specify desired level of confidence
- Frequency distributions (bin to histogram), including
cumulative histograms.
- Kolmogorov-Smirnov normality test
- One sample t test or Wilcoxon test to compare
the column mean (or median) with a theoretical
value
- Skewness and Kurtosis
Linear regression and correlation
- Calculate slope and intercept with confidence
intervals
- Force the regression line through a specified
point
- Fit to replicate Y values or mean Y
- Test for departure from linearity with a runs
test
- Calculate and graph residuals
- Compare slopes and intercepts of two or more
regression lines
- Determine new points along the standard curve
- Pearson or Spearman (nonparametric) correlation
- Table of XY coordinates
Clinical (diagnostic) lab statistics
- Bland-Altman plots
- Receiver operator characteristic (ROC) curves
Deming regression (type ll linear regression) |