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Which is the correct ordering of the CRISP-DM phases?

Data Understanding, Business Understanding, Data Preparation, Modeling, Evaluation, Deployment

Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment

Modeling, Evaluation, Data Preparation, Deployment, Business Understanding, Data Understanding

Business Understanding, Data Preparation, Modeling, Data Understanding, Evaluation, Deployment

to track

2026 Statistics

Key Facts: CDSP (DSP-110) Exam

Exam Questions

CertNexus

120 min

Exam Duration

CertNexus

60-70%

Passing Score

CertNexus (scaled)

$400

Exam Fee

CertNexus

3 years

Validity

CEC renewal

Vendor-neutral

Format

Stack-agnostic

The CDSP (DSP-110) exam has 80 questions in 120 minutes with a 60-70% scaled passing score. Domains span the data science process (CRISP-DM, OSEMN), descriptive and inferential statistics, hypothesis testing, regression and time series, NLP basics, visualization (Matplotlib, Seaborn, Tableau, Power BI), data engineering (ETL, warehouses/lakes, dimensional modeling), big data (Spark, Kafka, Flink), cloud data (BigQuery, Synapse, Redshift, Databricks), and data quality. Exam fee is $400. Valid 3 years.

Sample CDSP (DSP-110) Practice Questions

Try these sample questions to test your CDSP (DSP-110) exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1Which is the correct ordering of the CRISP-DM phases?

A.Data Understanding, Business Understanding, Data Preparation, Modeling, Evaluation, Deployment

B.Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment

C.Modeling, Evaluation, Data Preparation, Deployment, Business Understanding, Data Understanding

D.Business Understanding, Data Preparation, Modeling, Data Understanding, Evaluation, Deployment

Explanation: CRISP-DM (Cross-Industry Standard Process for Data Mining) defines six phases in order: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment. The process is iterative — phases can loop back as needed.

2What does the OSEMN framework stand for?

A.Observe, Sample, Estimate, Model, Notify

B.Obtain, Scrub, Explore, Model, iNterpret

C.Optimize, Sample, Engineer, Model, Normalize

D.Order, Save, Evaluate, Maintain, Negotiate

Explanation: OSEMN (Mason and Wiggins) is a popular data science workflow: Obtain data, Scrub (clean), Explore (EDA), Model, and iNterpret. It overlaps with CRISP-DM but emphasizes the iterative analyst workflow.

3Which measure of central tendency is most robust to outliers?

A.Mean

B.Median

C.Mode

D.Range

Explanation: The median (50th percentile) is unaffected by extreme values. The mean is pulled by outliers. The mode is the most frequent value. Range is a measure of dispersion, not central tendency.

4Standard deviation measures:

A.The most frequent value

B.The average distance of values from the mean

C.The middle value of an ordered dataset

D.The total sum of values

Explanation: Standard deviation is the square root of variance and quantifies spread around the mean. Variance is in squared units, while SD is in the original units, making SD more interpretable.

5The interquartile range (IQR) is computed as:

A.Q4 - Q1

B.Q3 - Q1

C.Q2 - Q1

D.Q3 - Q2

Explanation: IQR = Q3 (75th percentile) - Q1 (25th percentile). It measures spread of the middle 50% of data and is robust to outliers. The 1.5*IQR rule is a common outlier detection threshold.

6A right-skewed distribution typically has:

A.Mean less than median

B.Mean greater than median (long right tail)

C.Mean equal to median

D.No mode

Explanation: In right-skewed (positively skewed) distributions, a long right tail pulls the mean above the median. Income, prices, and many real-world variables exhibit positive skew. Left-skewed distributions show the opposite.

7Kurtosis measures:

A.Symmetry of a distribution

B.Tail heaviness/peakedness of a distribution

C.Average value

D.Sample size

Explanation: Kurtosis quantifies tail heaviness. Excess kurtosis > 0 (leptokurtic) means heavier tails than normal; < 0 (platykurtic) means lighter tails. Skewness, not kurtosis, measures symmetry.

8The Central Limit Theorem (CLT) states that:

A.All data is normally distributed

B.The sampling distribution of the sample mean approaches a normal distribution as sample size increases, regardless of the population distribution

C.Population variance is always known

D.Samples must be at least 1000 in size

Explanation: The CLT enables inferential statistics on means even when the underlying distribution is non-normal. The rule of thumb n ≥ 30 is commonly cited but depends on population skew.

9A 95% confidence interval for a population mean means:

A.There is a 95% probability the true mean lies in this interval

B.If we repeated the sampling many times and constructed an interval each time, ~95% of those intervals would contain the true mean

C.95% of data points fall in this interval

D.The sample mean is 95% accurate

Explanation: Frequentist confidence intervals describe long-run capture rates of repeated samples, not the probability that the true parameter lies in any single interval. The Bayesian credible interval is the version that does have the probabilistic interpretation.

10In hypothesis testing, the p-value represents:

A.The probability the null hypothesis is true

B.The probability of observing data at least as extreme as the sample if the null hypothesis were true

C.The size of the effect

D.The power of the test

Explanation: P-value = P(data | H0). It is NOT the probability the null is true. Small p-values cast doubt on H0. Convention rejects H0 when p < alpha (typically 0.05). Effect size and confidence intervals complement p-values.

About the CDSP (DSP-110) Exam

Certified Data Science Practitioner (CDSP / DSP-110) is CertNexus's vendor-neutral data science certification. CDSP validates the end-to-end data science process: problem framing (CRISP-DM, OSEMN), descriptive and inferential statistics, regression and time series modeling, NLP basics, data visualization, data engineering and big-data fundamentals, cloud data services, and data quality.

Questions

80 scored questions

Time Limit

120 minutes

Passing Score

60-70% (scaled)

Exam Fee

$400 USD (CertNexus / Pearson VUE)

CDSP (DSP-110) Exam Content Outline

~15%

Data Science Process

CRISP-DM phases (Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment), OSEMN workflow, role distinctions (data scientist, data engineer, BI, MLOps)

~25%

Statistics and Probability

Descriptive stats (mean, median, IQR, variance, kurtosis, skewness), inferential stats (CLT, confidence intervals, p-value, t-test, ANOVA, chi-square, Wilcoxon), Bayes' theorem, distributions (normal, binomial, Poisson, Bernoulli, exponential)

~25%

Modeling: Regression, Time Series, NLP

Linear/logistic/polynomial regression, regularization (Ridge, Lasso, ElasticNet), assumptions, multicollinearity, time series (stationarity, ARIMA, SARIMA, Prophet, ACF/PACF), NLP basics (tokenization, lemmatization, TF-IDF, Word2Vec, GloVe, sentiment)

~15%

Data Visualization and Communication

Chart selection (histogram, box plot, scatter, line, heatmap, violin), Matplotlib, Seaborn, Plotly, Tableau, Power BI, Tufte's data-ink ratio, Stephen Few principles

~20%

Data Engineering and Big Data

ETL/ELT, data warehouses vs lakes vs lakehouses, dimensional modeling (star/snowflake, fact/dim), OLAP vs OLTP, Hadoop/HDFS/Spark/PySpark, Kafka, Flink, cloud data (BigQuery, Synapse, Redshift, Databricks, Athena, Glue), data quality dimensions

How to Pass the CDSP (DSP-110) Exam

What You Need to Know

Passing score: 60-70% (scaled)
Exam length: 80 questions
Time limit: 120 minutes
Exam fee: $400 USD

Keys to Passing

Complete 500+ practice questions
Score 80%+ consistently before scheduling
Focus on highest-weighted sections
Use our AI tutor for tough concepts

CDSP (DSP-110) Study Tips from Top Performers

1Memorize CRISP-DM phases in order and what each delivers

2Master hypothesis testing: when to use t-test, ANOVA, chi-square, or non-parametric alternatives

3Know regression assumptions and how to diagnose violations (residual plots, VIF)

4Understand time series stationarity and how to test for it (ADF, KPSS)

5Practice choosing the right chart for the question — avoid pie charts and 3D

6Distinguish data warehouses, lakes, and lakehouses, and when each fits

7Learn the data quality dimensions: completeness, accuracy, consistency, timeliness, validity, uniqueness

Frequently Asked Questions

What is the CDSP (DSP-110) exam?

The Certified Data Science Practitioner (CDSP / DSP-110) is CertNexus's vendor-neutral data science certification. It validates the ability to apply the end-to-end data science process: framing problems with CRISP-DM/OSEMN, applying descriptive and inferential statistics, building regression/time series/NLP models, communicating with effective visualizations, and operating across modern data engineering and big-data tooling.

How many questions are on the CDSP exam?

The CDSP (DSP-110) exam has 80 questions to complete in 120 minutes. Questions are multiple-choice and scenario-based. The passing score is scaled and typically corresponds to roughly 60-70% of items correct.

Are there prerequisites for the CDSP exam?

There are no formal prerequisites. CertNexus recommends approximately 6+ months of hands-on data science experience using Python (pandas, NumPy, scikit-learn, Matplotlib/Seaborn) and SQL, plus exposure to a BI tool such as Tableau or Power BI.

What is the difference between CDSP and CAIP?

CDSP (DSP-110) emphasizes the broader data science workflow including statistics, exploratory analysis, regression, time series, visualization, and data engineering. CAIP (AIP-210) emphasizes applied AI/ML with stronger coverage of neural networks, MLOps, and responsible AI. Many practitioners pursue both.

How long is CDSP valid?

CDSP certification is valid for 3 years from the date you pass. To renew, you must earn Continuing Education Credits (CECs) through training, conferences, publications, or professional activities and pay a CertNexus renewal fee.

How should I prepare for CDSP?

Plan for 60-100 hours of study over 6-10 weeks. Build hands-on projects covering EDA, hypothesis testing, regression with diagnostics, a time series forecast (Prophet/ARIMA), an NLP classification task, and a Tableau or Power BI dashboard. Read CRISP-DM and review Tufte/Few visualization principles. Complete 100+ practice questions scoring 80%+ before scheduling.