SAS statistical certifications (Statistical Business Analyst, Applied Statistics Associate, Statistics for Machine Learning)

USA / global · SAS Institute · professional

164practice questions written to this syllabus
4subjects

Format

Proctored online or test-centre exams per credential.

Sections

Over the years

Credential names read on the SAS certification page (October 2026). SAS remains common in agricultural research institutes and pharmaceutical and animal-health industries; exam content outlines were not read.

Official source: https://www.sas.com/en_us/certification.html

Subjects this exam draws on

Exploratory Data Analysis & Statistical Graphics54 questionsProgramming for Statistics & Data (R and Python)9 questionsData Analysis with Statistical Software & Reproducible Research8 questionsStatistical & Machine Learning for Agriculture93 questions

Five practice questions, worked

Original questions written to this exam's published syllabus and pattern. Not past papers.

1. For which variable is the coefficient of variation a meaningful summary?

  1. Milk yield per cow in litres per day
  2. Air temperature in degrees Celsius
  3. Calendar date of sowing
  4. Soil series coded 1 to 6
Answer and working

A. Milk yield per cow in litres per day

The CV divides the SD by the mean, which is meaningful only on a ratio scale with a true zero. With Celsius or dates, moving the zero changes the CV arbitrarily; codes for soil series are nominal.

Exploratory Data Analysis & Statistical Graphics · Types of data and measurement scales

2. In SAS, every statement must end with:

  1. A semicolon
  2. A full stop
  3. A comma
  4. A colon
Answer and working

A. A semicolon

Missing semicolons are the commonest beginner's error.

Programming for Statistics & Data (R and Python) · SAS DATA and PROC steps for agricultural analyses

3. In PROC GLM, the statement declaring classification factors is:

  1. CLASS
  2. MODEL
  3. BY
  4. VAR
Answer and working

A. CLASS

MODEL then lists the response and effects.

Data Analysis with Statistical Software & Reproducible Research · SAS: PROC GLM, MIXED, REG and SURVEYMEANS

4. A model predicts whether a leaf image shows rust or not. What kind of learning task is this?

  1. Dimensionality reduction of the image pixels
  2. Supervised regression on a numerical outcome
  3. Supervised classification
  4. Unsupervised clustering of leaf images into groups
Answer and working

C. Supervised classification

The outcome (rust or not) is a known category for training images, so this is supervised classification. Regression needs a numerical outcome; clustering has no outcome.

Statistical & Machine Learning for Agriculture · Supervised learning and the bias-variance trade-off

5. Plot yields have Q₁ = 2.8 and Q₃ = 3.6 t/ha. Where is Tukey's upper inner fence?

  1. 4.8 t/ha
  2. 1.6 t/ha
  3. 6.0 t/ha
  4. 4.4 t/ha
Answer and working

A. 4.8 t/ha

IQR = 0.8; upper inner fence = Q₃ + 1.5 IQR = 3.6 + 1.2 = 4.8. 6.0 is the outer fence (3 IQR); 1.6 is the lower inner fence; measuring from the median (3.2) gives 4.4.

Exploratory Data Analysis & Statistical Graphics · Five-number summaries, box plots and robust statistics (median, MAD, trimmed means)

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