This is a great course for anyone who wants to gain foundational and critical analysis and statistics skills with no prior background. In this course, we examine the statistical processes of understanding larger populations from smaller samples. We want to be able to answer questions like: How large a sample is needed to make a reasonable inference about my customer base? What are the upper and lower limits for the percentage of people who wear medium-sized t-shirts in a population? Is the income level of native citizens significantly different to that of people born overseas?
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To address questions like these, the course is divided into three topics:
In Topic 1, we examine the characteristics of point estimates – measurements that we take from samples to make inferences about a population.
Topic 2 deals with confidence intervals , which help us to establish upper and lower limits about where we think the “true” population characteristic lies, at a certain level of confidence.
In Topic 3, which is the largest and most important part of this course, we explore hypothesis testing. This includes one-, two- and many-sample forms of testing.
This course is part of the Statistics for Business Analytics Professional Certificate.
What you'll learn
Upon successful completion of this course, you will be able to:
- Describe the characteristics of point estimates and how they can be used to make inferences about a population.
- Calculate upper and lower bounds of confidence intervals for given levels of confidence.
- Describe the general process for conducting a hypothesis test using the Z-score or p-value methods.
- Conduct a hypothesis test and interpret the meaning of the result for: one mean or proportion against a predetermined standard; two means or proportions against one another; paired data from repeated measurements of the same sample or matched pairs of individuals; and many means using an analysis of variance (ANOVA).
