Learning Outcomes

Introduction to Datasets

Measuring Centre of a Dataset

Comparing Univariate Data in a Dataset

Introduction to Multivariate Data

Transformations to Achieve Linearity

Lesson Summary

To start, this module will introduce you to data exploration. You will learn about the important metrics used in measuring the centre of a data set. You will also be introduced to how transformations are used as a technique for linear and non-linear models.

Methods of Data Collection

Planning and Conducting Surveys

Planning and Conducting Experiments

To start, this module will introduce you to how samples are selected from populations and conclusions made about those populations based on the samples. The module also introduces how surveys are used as an instrument for asking questions from a selected group of people.

Diploma in AP Statistics - First Assessment

In order to pass this assessment, you will need to score 80 per cent or above. Remember, if you do not achieve the required standard after the first attempt, you can re-take the assessment until a successful outcome is achieved.

Introduction to Probability

Discrete Random Variables and their Probability Distributions

Normal Distribution

Sample Distributions

Central Limit Theorem

To start, this module will introduce you to several methods used in interpreting relative frequency. The module also covers the notion of dependence versus independence in probability and how they are used in statistics

Introduction to Estimation

Tests of Significance

Large Sample Confidence Interval for a Proportion

Test for a Mean

To start, this module will introduce you to the relationship between estimation and statistical inferences. You will learn about estimating population parameters and margin errors. You will also be introduced to the properties of the point estimator.

Diploma in AP Statistics - Second Assessment

Diploma in AP Statistics - Course Assessment

An introductory college-level course that looks at probability in data exploration and dataset characterization.

Diploma in AP Statistics

This course covers anticipating patterns involving the exploration of random phenomena using probability and simulation. It also describes data exploration as a statistical concept in data analysis where analysts use visualization and statistical techniques to describe dataset characterizations. By the end of this course, you should be ready to apply statistical reasoning in various fields of learning.

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