
Apply statistical testing to drive data driven decision making in sales and marketing, revealing customer preferences, measuring campaign impact, and optimizing ROI with A/B testing and significance tests.
Transform sales and marketing strategies by mastering data-driven decisions through statistical testing, interpreting reports, and applying essential techniques with Python in Jupyter notebooks for actionable insights.
Explore how to use contingency tables to display discrete or categorical data, convert counts to relative frequencies, and interpret cross-tabulations with pandas crosstab in a Jupyter notebook.
Define the null hypothesis as no effect and the alternative as the expected difference. Use data to test and decide between two-tailed or one-sided alternatives in marketing analytics.
Examine the p value, the probability of observing data under the null hypothesis, and how small values support rejecting the null in hypothesis testing; explore significance levels.
Explore how a p value guides the rejection of the null hypothesis and how the significance level, alpha, sets the threshold for significance in sales and marketing.
Explain the independent variable as the manipulated predictor and the dependent variable as the measured outcome, illustrating cause-and-effect links with examples like sales volume and advertising expenditure.
Apply the Shapiro-Wilk test to assess normality in sales data, using p-values and an alpha of 0.05 to determine if old and new display data follow a normal distribution.
Apply the paired samples t test to compare means of related data using pairwise differences, verify assumptions (dependence, random sampling, normality), and interpret p-values to assess significance.
Examine a Wilcoxon signed rank test on 30 consumers at 0.05 to show no difference in purchase intent between two package designs, guiding an objective choice.
Demonstrate a chi-square goodness-of-fit test in Python, verify categorical data conditions, and interpret results to conclude footfall consistency at 0.05 while considering alpha adjustments for marketing insights.
Do you want to advance your career in Sales and Marketing?
Are you eager to leverage data for informed decision-making?
Well, you’ve come to the right place!
Statistics for Sales and Marketing is here for you!
This is the only course you need to take to start using statistical tests for informed business decisions. In no time, you will acquire the fundamental skills that will enable you to perform statistical tests applicable to real-life sales and marketing scenarios. We have created a course that is:
Easy to understand
Thorough
Hands-on
Concise
Loaded with practical exercises and resources
Focused on 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.
You will acquire practical skills in employing statistical tests, interpreting results, and deriving actionable insights with Python. The Statistics for Sales and Marketing course 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.
Learn from the best instructors
Olivier Maugain and Aastik Mahotra, seasoned industry experts, have joined forces to deliver a top-tier learning experience through this course. Both instructors bring a wealth of knowledge from their tenure at leading global corporations and are passionate about sharing their skills with those looking to elevate their data-driven decision-making capabilities. This course offers a unique chance to benefit from their extensive expertise as they guide you through the processes of performing statistical tests, leveraging the same techniques they've successfully applied at internationally acclaimed companies.
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