This course aims to make statistical analysis approachable and practical, as you learn how to read and interpret statistical reports in a business environment, and how to communicate statistical results to stakeholders. First, you will practice assessing the statistical components and representations of statistical results in a case study. You will then identify the appropriate method and conduct a summary analysis of a data set. Finally, you will prepare an executive summary of the key statistical points identified through your analysis and create a narrative summary with supporting graphics.
In this course, you will practice making informed decisions based on statistical results. You will be introduced to the techniques you will use to view statistical tests critically and recognize the limitations of statistical conclusions. Next, you will examine statistical reports in order to identify the underlying research question. You will then use these insights to compare tests and rate their validity. Finally, you will prepare a report for stakeholders, providing recommendations based on your interpretation of statistical results.
Choosing the most appropriate statistical test to answer your research questions will affect every aspect of your report. This course will focus on identifying the right test for your question. You will explore the relationship between the data set and the results obtained through statistical tests. You will practice writing a memo to your data analyst specifying the appropriate statistical test to answer your question. In selecting your testing methods, you will also consider the ethical implications of the test results.
Making statistical predictions based on real-world data is complex and requires a more rigorous statistical model. In this course, you will learn to apply multivariate regression statistical models to make predictions. First, you will identify the variables that best explain your results and define the relationships between dependent and independent variables. You will then practice identifying and interpreting the results of a multiple regression model and making predictions based on that model.

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