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Statistics for Marketing

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This course takes a deep dive into the statistical foundation upon which Marketing Analytics is built. The first part of this course is all about getting a thorough understanding of a dataset and gaining insight into what the data actually means. The second part of this course goes into sampling and how to ask specific questions about your data. Finally, the third part is about answering those questions with analyses. Many of the mistakes made by Marketing Analysts today are caused by not understanding the concepts behind the analytics they run, which causes them to run the wrong test or misinterpret the results. This course is specifically designed to give you the background you need to understand what you are doing and why you are doing it on a practical level. By the end of this course you will be able to: • Understand the concept of dependent and independent variables • Identify variables to test • Understand the Null Hypothesis, P-Values, and their role in testing hypotheses • Formulate a hypothesis and align hypotheses with business goals • Identify actions based on hypothesis validation/invalidation • Explain Descriptive Statistics (mean, median, standard deviation, distribution) and their use cases • Understand basic concepts from Inferential Statistics • Explain the different levels of analytics (descriptive, predictive, prescriptive) in the context of marketing • Create basic statistical models for regression using data • Create time-series forecasts using historical data and basic statistical models • Understand the basic assumptions, use cases, and limitations of Linear Regression • Fit a linear regression model to a dataset and interpret the output using Tableau and statsmodels • Explain the difference between linear and multivariate regression • Run a segmentation (cluster) analysis • Describe the difference between observational methods and experiments This course is designed for people who want to learn the basics of descriptive and inferential statistics and analytics in marketing. Learners don't need marketing or data analysis experience, but should have basic internet navigation skills and be eager to participate. Ideally learners have already completed course 1 (Marketing Analytics Foundation) and course 2 (Introduction to Data Analytics) in this program.

الوحدات

Introduction to the Meta Marketing Analytics Certificate Program

    • 4 Videos
    • 4 Readings
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4 Videos

  • Introduction to the Program
  • Introduction to Statistics Foundations
  • Introduction to Speaker
  • Careers in Marketing and Marketing Analytics

4 Readings

  • Statistics for Marketing Course Syllabus
  • Join the Meta Marketing Analytics Community or the Meta Data Analyst Community!
  • How to be Successful in this Program
  • Community Guidelines

Measures of Central Tendency

    • 5 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Measures of Central Tendency

5 Videos

  • Capstone Introduction
  • Introduction: Measures of Central Tendency
  • Using Measures of Central Tendency to Find the Middle
  • When to Use Different Measures of Central Tendency
  • Finding the Middle with Spreadsheets

1 Readings

  • Measures of Central Tendency Review

Measures of Dispersion

    • 5 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Measures of Spread

5 Videos

  • Introduction: Measures of Spread
  • Variance and Range in Data Analytics
  • Standard Deviation in Data Analytics
  • Using Z-Scores to Judge a Value
  • Standard Deviation in Spreadsheets

1 Readings

  • Measures of Spread Review

Frequency Tables

    • 6 Videos
    • 1 Readings
    • 2 Assignment
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2 Assignment

  • Graded Quiz: Descriptive Statistics
  • Capstone Module 1: Getting to Know the Data

6 Videos

  • Introduction: Frequency Tables
  • Frequency Tables in Marketing Analytics
  • How to Use Contingency Tables
  • Conditional Probability: Bayesian Statistics
  • Understanding Scatter Plots and Correlation
  • Week 1 Review

1 Readings

  • Frequency, Contingency, and Scatterplots Review

Sampling

    • 4 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Sampling

4 Videos

  • Introduction: Sampling
  • Why Use Sampling?
  • Sample Size in Statistics
  • Practical Sampling Techniques

1 Readings

  • Sampling Review

Distributions

    • 5 Videos
    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Distributions

5 Videos

  • Introduction: Distributions
  • Finding a Distribution
  • Finding a Distribution in a Spreadsheet
  • Common Distributions in Data Analytics
  • Data Shapes

2 Readings

  • Reshaping Data with Transformations
  • Distribution Review

Variable Types

    • 5 Videos
    • 1 Readings
    • 3 Assignment
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3 Assignment

  • Practice Quiz: Variable Types
  • Graded Quiz: Sampling, Distribution, and Variables
  • Capstone Module 2: Understanding Your Data Samples

5 Videos

  • Introduction: Variable Types
  • Quantitative Variables
  • Qualitative Variables
  • Independent and Dependent Variables
  • Week 2 Review

1 Readings

  • Variable Types Review

Experiment Design and Hypotheses

    • 5 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Experimental Design and Hypotheses

5 Videos

  • Introduction: Experimental Design and Hypotheses
  • Research Question
  • Hypothesis Writing
  • Observational vs Experimental Studies
  • Experimental Design for Data Analysis

1 Readings

  • Experimental Design Review

Hypothesis and AB Testing

    • 6 Videos
    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Hypothesis and AB Testing

6 Videos

  • Introduction: Hypothesis and AB Testing
  • Hypothesis Testing and AB Testing
  • Understanding P-Values
  • Confidence Intervals in Data Analytics
  • Confidence Intervals in a Spreadsheet
  • Hypothesis Testing in a Spreadsheet

2 Readings

  • Hypothesis Testing in Spreadsheet Review
  • AB Testing Review

Common Mistakes in Statistics

    • 5 Videos
    • 2 Readings
    • 2 Assignment
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2 Assignment

  • Graded Quiz: Experimental Design and Testing
  • Capstone Module 3: Testing Your Hypothesis

5 Videos

  • Introduction: Common Mistakes in Statistics
  • Being Fair: Avoiding Bias
  • Types of Errors: Types I and II
  • Assumptions
  • Week 3 Review

2 Readings

  • Being Accurate: Avoiding Bias
  • False Positives and False Negatives Review

Statistical Modeling

    • 4 Videos
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Statistical Modeling

4 Videos

  • Introduction: Statistical Modeling
  • What is Statistical Modeling
  • Modeling in Data Analytics
  • Common Types of Statistical Modeling

Simple Linear Regression and Classification Methods

    • 5 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Simple Linear Regression

5 Videos

  • Introduction: Simple Linear Regression and Classification Methods
  • Simple Linear Regression
  • Simple Linear Regression in Tableau
  • Simple Linear Regression in Tableau - Screencast
  • Classification Methods in Data Modeling

1 Readings

  • Simple Linear Regression Review

Cluster Analysis

    • 3 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Cluster Analysis

3 Videos

  • Introduction: Cluster Analysis
  • Cluster Analysis
  • Cluster Analysis in Tableau

1 Readings

  • Cluster Analysis Review

Time Series

    • 3 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Time Series

3 Videos

  • Introduction: Time Series
  • Time Series
  • Time Series in Tableau

1 Readings

  • Time Series Analysis Review

Choosing a Model

    • 4 Videos
    • 2 Readings
    • 2 Assignment
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2 Assignment

  • Statistical Modeling Quiz
  • Capstone Module 4: Data Modeling

4 Videos

  • Introduction: Choosing a Model
  • Choosing a Model
  • Data Analysis Case Studies
  • Weekly Review: Data Modeling

2 Readings

  • Choosing a Model Review
  • Capstone Week 4: Show Me the Model

Capstone

    • 1 Videos
    • 1 Assignment
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1 Assignment

  • Finalize Your Capstone Project

1 Videos

  • Introduction: Capstone

Marketing Analyst Interview

    • 5 Videos
    • 1 Discussion
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1 Discussions

  • Share Your Thoughts!

5 Videos

  • Marketing Analyst on Descriptive Statistics
  • Marketing Analyst on Sampling, Distributions, and Variables
  • Marketing Analyst on Questions and Hypotheses
  • Marketing Analyst on Modeling
  • Course Summary & Congratulations

Auto Summary

"Statistics for Marketing" is an in-depth course designed for those looking to grasp the statistical foundations crucial for marketing analytics. Led by Coursera, this foundational course spans 1020 minutes and is available through Starter and Professional subscriptions. It covers key concepts like dependent and independent variables, hypothesis testing, descriptive and inferential statistics, regression models, and more, using tools like Tableau and statsmodels. Ideal for beginners in marketing analytics, it equips learners with practical skills to analyze and interpret data effectively.