Statistics and Probability Module: Illustrating the Nature of Bi-variate Data

This Self-Learning Module (SLM) is prepared so that you, our dear learners, can continue your studies and learn while at home. Activities, questions, directions, exercises, and discussions are carefully stated for you to understand each lesson.

Each SLM is composed of different parts. Each part shall guide you step-by-step as you discover and understand the lesson prepared for you.

Pre-tests are provided to measure your prior knowledge on lessons in each SLM. This will tell you if you need to proceed on completing this module or if you need to ask your facilitator or your teacher’s assistance for better understanding of the lesson. At the end of each module, you need to answer the post-test to self-check your learning. Answer keys are provided for each activity and test. We trust that you will be honest in using these.

Please use this module with care. Do not put unnecessary marks on any part of this SLM. Use a separate sheet of paper in answering the exercises and tests. And read the instructions carefully before performing each task.

Making sound decisions is a very important skill that needs to be developed among individuals. Some people even claim that life is the product of every decision he makes. Thus, the data and variables involved should be carefully examined and studied before making decisions. In this ADM module, you will be introduced to different nature of data that we usually encounter in real life.

After going through this module, you are expected to:

1. describe the nature of bivariate data;

2. differentiate bivariate data from univariate data; and

3. determine the variables involved in the given bivariate data.

Are you ready now to study bivariate data using your ADM module? Good luck and may you find it helpful.

Statistics and Probability Quarter 4 Self-Learning Module: Illustrating the Nature of Bi-variate Data


Can't Find What You'RE Looking For?

We are here to help - please use the search box below.

Leave a Comment