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Statistical Tests in Sales and Marketing
Master advanced statistics for Sales and Marketing: Leverage Python to make data-driven decisions and boost performance
1545 students already have enrolled
Skill level:
Basic
Duration:
3 hours
-
Lessons (3 hours)
-
Practice exams (20 minutes)
- Lessons (3 hours)
- Practice exams (20 minutes)
CPE credits:
5.5
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of
professionals must earn to maintain their licenses and stay current with regulations and best
practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's
official website: www.nasbaregistry.org
Accredited:
certificate
What You Learn
- Master advanced statistics to solve sales and marketing challenges.
- Use Python to make data-driven decisions and boost performance.
- Select, apply, and interpret various statistical tests independently.
- Improve your problem-solving skills with real-world business case studies.
- Advance your career with highly sought-after technical skills.
Topics & tools
theoryhypothesis testingprogrammingstatisticsdata analysisdata-driven decision-makingpythonmath & statisticsindustry specialization
Your instructor
Data Culturist | Data Governance Manager at IKEA
Track record
Bringing real-world expertise from leading global companies
Academic background
Doctorate (PhD), Business Administration
Media and recognition
- Frequent speaker on data culture and digital transformation
- Publications on AI and data in marketing & advertising
- Entrepreneurial track record in analytics consulting in China
AI & Data Science Course Creator | Sound Engineer
Track record
Bringing real-world expertise from leading global companies
Academic background
Master's degree, Sound Engineering
Media and recognition
- Author of Speech Recognition with Python on 365DS & Udemy
- Speaker at Power Platform Bootcamp 2025 on Audio AI
- Sound Engineer for TV/Film incl. The Bachelor & award-winners
Co-Founder of SemanticMap | Software & AI Manager
Track record
Bringing real-world expertise from leading global companies
Academic background
Master's degree, Mechatronics
Course OVERVIEW
Description
CPE Credits: 5.5
Field of Study: Information Technology
Delivery Method: QAS Self Study
Delivery Method: QAS Self Study
Our Statistical Tests in Sales and Marketing course explores how statistical analysis fuels data-driven decision-making. By delving into real-world case studies from sales and marketing, we demonstrate the practical use of statistical tools beyond crunching numbers.
The course details the process of understanding, selecting, applying, and interpreting different statistical tests like the chi-square test of independence, t-test, Mann–Whitney U test, and more.
Our premier data analysis course provides practical skills in employing statistical tests, interpreting results, and deriving actionable insights with Python. It focuses on applied knowledge rather than abstract theory—aiming to clarify statistics' role in solving sales and marketing challenges.
From decoding market segmentation to assessing campaign impacts, we guide you on applying statistical analysis in marketing and sales and aid effective decision-making. Ultimately, statistics become a crucial tool—enabling informed, data-driven decisions that lead to success.
Prerequisites
- Python (version 3.8 or later), pandas library, and a code editor or IDE (e.g., Jupyter Notebook, Spyder, or VS Code)
- Basic familiarity with Python programming is required.
- Familiarity with basic statistics and linear algebra is helpful but not mandatory.
Advanced preparation
Curriculum
49 lessons
41 exercises
2 exams
- 2. Case 1: Chi-Square Test of Independence57 MinDelve into fundamental concepts required to master statistical testing. Understand how the chi-square test of independence can reveal the relationships between categorical variables in sales and marketing contexts.Case Description: Packaging Uniqueness FreeResearch Question FreeExercise FreeOperationalization FreeSample FreeExercise FreeStatistic and Parameter FreeExercise FreeLevels of Measurement FreeContingency Table FreeExercise FreeHypothesis Testing – Introduction FreeNull and Alternative Hypothesis FreeExercise FreeTest Statistic FreeP-value FreeExercise FreeStatistical Significance FreeDegrees of Freedom FreeChi-Square Test - Introduction FreeChi-Square Test of Independence FreeExercise FreeCase Summary and Discussion on Chi-Square Test of Independence Free
- 3. Case 2: One-Sample t-test31 MinThe one-sample t-test assesses if a single sample's mean significantly differs from a known population mean. Learn how to apply this statistics technique to a marketing case study for informed decision-making.Case Description: Price per Volume (PPV) FreeMean and Median FreeExercise FreeStandard Deviation FreeNormal Distribution FreeExercise FreeHistogram FreeExercise FreeQ-Q plot FreeOne-Sample t-Test FreeExercise FreeOne- vs. Two-Tailed Tests FreeCase Summary and Discussion on One-Sample t-test Free
- 4. Case 3: Two-Sample t-Test21 MinDiscover how the two-sample t-test compares the means of two independent groups in the context of evaluating different marketing strategies.
- 5. Case 4: Paired Samples t-Test12 MinUncover the applications of the paired samples t-test in comparing the means of the same group at different times using sales data before and after a campaign.
- 6. Case 5: Mann-Whitney U Test15 MinLearn how to use the Mann-Whitney U test to compare two independent groups when data doesn't follow a normal distribution.
- 7. Wilcoxon Signed-Rank Test10 MinThe Wilcoxon signed-rank test is used to compare two related samples. Learn how to assess the impact of marketing adjustments utilizing this statistical analysis test.
- 8. Chi-Square Goodness-of-Fit Test10 MinUnderstand the chi-squared goodness-of-fit test's role in determining how well-observed data fit expected distributions, illustrated with sales data analysis.
- 9. Conclusion2 MinWe summarize the key takeaways of the Statistical Tests in Sales and Marketing course and recap the applications of statistical tests in data-driven decision-making in sales and marketing.
- 10. Course exam30 Min
Free preview
1.1 Welcome to the World of Statistical Tests!
4 min
1.2 The Importance of Statistical Testing in Sales and Marketing
5 min
1.3 Course Approach
3 min
2.1 Case Description: Packaging Uniqueness
4 min
2.2 Research Question
2 min
2.4 Operationalization
3 min
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