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Request for
Statistical
Consulting

 Please fill out the form below. Name and e-mail address are required. Upon submission, the contents of the form will be encoded and e-mailed. Before submitting a request please review the statements of consulting policy and philosophy and make sure that you are comfortable with them. 

Name: 
Daytime Phone: 
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Rank: Dept.: 
Major Professor (If applicable): 
Project Name: 
Status of experiment: 
General subject matter area: 


Suggested Day and Time to meet:   Other:

Service Requested:

In the list below, please indicate the reason for contacting the SCC.  The list should not be interpreted as a list of services the SCC will perform for you, but as a list of possible areas consulting services have been requested in the past.
Limited help on these some of these issues can be found here, or by clicking on the appropriate topic headings.

Data Management

Handling of data in Excel Data manipulation in SAS Data manipulation in other software
Data conversion between programs

Exploratory Statistics

Descriptive Statistics Tests of Normality Measures of Dispersion
Measures of Location Measures of Correlation

Design of Experiments

Randomization Replication Blocking (Local control)
Development of experimental plan Translation of research hypothesis into analysis
Analysis of designed experiment Transformations Treatment design
Error-control design Design efficiency How many reps do I need?
Trend contrasts Covariance analysis Split-principle
Subsampling Design replications

Design or Analysis of

Completely Randomized Design Randomized Complete Block Design Latin Square
Incomplete Block Design Balanced Incomplete Block Design Partially Balanced Incomplete Block Design
Latin Rectangle Split-Plot Design Split-Split-Plot Design
Split-Block (Strip-Plot) Design Lattice Design
Includes repeated measures repeated treatment applications subsampling

ANOVA

Main effects and interactions Slicing of interactions Mean separation tests
Multiple error terms Contrasts Regression trends
Transformations Covariates Comparisons of cell means

Hypothesis Test and Confidence Intervals

One-sample tests Two-sample tests Confidence intervals
Comparing counts Comparing proportions Nonparametric tests

Regression Analysis

Simple linear regression Multiple regression Transformations
Model selection Variable selection Collineratity
Tests of assumptions Residual analysis Nonlinear regression
Treatment comparisons in nonlinear regression
Dose-Response curves LD50, ED50, GR50 Logistic regression

Categorical Data

Contingency Table analysis Chi-Square tests Tests of homogeneity
Tests of independence Log-linear models Exact tests

Multivariate Statistics

Factor Analysis Principal Component Analysis Cluster Analysis
Discriminant Analysis Repeated Measures MANOVA Eigenvector analysis

Spatial Statistics

Kriging Cokriging Universal Kriging
Semivariogram estimation Covariogram estimation Nearest-Neighbor Analysis
Median-Polishing Point Processes Measures of Clumping
Spatial trend removal
Statistical software used: 
Concise Description of problem:
 
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(C) 1998 CANR Biometry Group, Michigan State University.
The CANR BiG SCC is sponsored jointly by the Michigan Agricultural Experiment Station and the
College of Agriculture and Natural Resources at Michigan State University. The support is gratefully acknowledged.
Last updated July 21, 1998
If you have any questions or comments about this web page, please e-mail scc@perm.fw.msu.edu.