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Course Content


Diploma in Probability & Statistical Analysis

  • Introduction to Statistical Analysis and SAS

    In this lesson we will be introduced to statistical analysis. We will discuss what the difference between this course and the data analysis course is and who this course is aimed at. Thereafter, we will introduce the tool we will utilize throughout this module, called SAS. We will end today’s lesson with a fun practical demonstration in SAS.

  • Getting to Know Your Data

    This lesson will be all about study design, data types and a sneak peak into summarizing data. Understanding the study design and the type of scales that are used to measure data, is a crucial step in analyzing the data accurately. only after we know the pros and cons of the way the data was gathered, can we start describing the data.

  • Summarizing Data

    This lesson will mainly focus on the different methods of summarizing data. The previous lesson introduced measures of central tendency to the student. Lesson 3 will elaborate on that concept with measures of spread as well as various ways of visualizing data through plots in SAS Studio. Each topic will be consolidated through a practical demonstration in SAS Studio.

  • Probability Theory

    This lesson will introduce the student to the concepts of probability theory. This lesson includes concepts like samples and populations. The lesson will define the basic definitions and rules of probability. This lesson will end by touching on more advanced concepts like mutually exclusive events, independent events, non independent events, and non mutually exclusive events.

  • Distributions

    Lesson 5 aims to initiate the student's understanding of random variables and a various number probability distributions known and identified. Together with these concepts, this lesson will showcase the famous Central Limit Theorem (a fundamental concept to the understanding of sample sizes to be discussed in the next lesson).

  • Sample Sizes and Sampling

    This lesson will answer the well known question of "how many observations does the study need in order to be statistically significant?". Many studies skip this fundamental step and end up not being able to prove statistical significance as a result. Lesson 6 will understand what it means for a result to be statistically significant and why it is so important for the sample to be large enough.

  • Project execution & Leadership

    In this lesson you will learn about the different tasks involved in executing a project, as well as different leadership styles that can be applied.

  • Hypothesis Testing

    Lesson 7 will focus on questions about a single group. This lesson starts to uncover the concepts of inferential statistics; statistical methods used to draw conclusions from the sample in order to make conclusion about the population. Prior lessons focused on descriptive statistics, because they helped the student to describe and summarize the data through various methods like plots and summary statistics.

  • Practical Module Recap

    The last lesson in module 1, will recap on all the principles covered in module 1 through a practical example.

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