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.
As you may recall, the Central Limit Theorem tells that if the sample size is sufficiently large, then the mean of the random sample from a population has a sampling distribution that is approximately normal, even when the original population is not normally distributed. This means that regardless of the shape of the original distribution, the sampling distribution of the mean approaches a normal distribution as long as the sample is large enough. Remember that the Central Limit Theorem is not limited to sample means only. It can also be applied to sample proportions.
This module deals on identifying the appropriate form of test statistics involving population proportion when the Central Limit Theorem is to be used. However, the activities are limited to estimating the population proportion and sample proportion as preparation in solving for the appropriate test statistics.
After going through this module, you are expected to:
1. define population proportion and sample proportion;
2. determine the value of the population proportion and sample proportion;
3. identify the appropriate form of the test statistic when the Central Limit Theorem is to be used; and
4. relate population proportion in real-life situations.