ILLUSTRATING RANDOM SAMPLING Background Information for Learners In this particular Learning Activity Sheet (LAS), you will be able to illustrate random sampling. Before answering the series of activities, take time to read the concepts that you need to know. Random Sampling Random Sampling In our everyday life, we are oriented with basic concepts in statistics. When you want to know the taste of food your mother is cooking, you only taste only a spoonful of it. On a wider scope, researchers aim to study, describe and infer patterns of behavior, properties and characteristics about a population. It is impractical and inconvenient to study the whole population that is why samples are only selected as representatives. A population is a group where members have something in common, that is, the total set of observations that can be made. Some examples include the population of women aged 20 and above, the population of registered voters in the province of Albay, and the population of daily maximum temperatures for the month of April in Baguio City. A sample is a smaller group or subset of the population that you want to examine. Sampling is a process used in statistical analysis in which a predetermined number of observations are taken from a larger population. When each element of the population has an equal chance of being selected, it is called random sampling. There are different sampling methods that allow all the units in the population to have an equal chance of being selected. no bigmis o al sterIT . siteltote bellog 1. Simple Random/Lottery Sampling - a sampling technique by which every member of the population has an equal chance to be chosen as sample. It can be done through Sample lottery method, table of random numbers or through the use 10 of computers. 10 11 12 2. Systematic Random Sampling - a sampling Population technique by which every member of the Population igm population is selected with a random start. For example, in 240 grade 11 students, you can only choose 80 students as members of your sample. To select which students will be part of the sample, we just divide the population size 240 by the sample size 80, which results to 3. That means every 3rd student among the 240 Sample (every 3id) grade 11 students will be included in the sample. Mort S.S The researcher may also opt to start on any randomly selected number from 1 to 240 then select every 3rd element successively until the 2 30 12 Hfor Ob desired sample size is completed. 10 2 4 Sample 3. Stratified Random Sampling - a sampling technique that is used when the population can be 7 8 11 classified into groups or strata based on some characteristics. Common criterions used f stratification are gender, age, ethnicity, and socioeconomic status. 4. Clustered Sampling - a sampling method where the population is first divided into separate groups called clusters. Then a simple random sample of clusters from the available clusters in the population 6 s selected. This sampling technique is usually used when the elements of a population are spread over a wide geographical area. 11 12 For example, if the population is composed of all citizens residing in the Philippines, the clusters could 12 Sample be citizens from Luzon, Visayas, and Mindanao. (2 clusters) Cluster Population Data is then gathered from a selected cluster.DISTINGUISHING PARAMETER AND STATISTIC Background Information for Learners In the previous activity, you learned about random sampling, a process done in selecting an unbiased representative sample from a population. In this particular Learning Activity Sheet (LAS), you will be able to identify and distinguish measures about population and sample called parameter and statistic. Take time to read the examples below for you to be able to answer the succeeding activities. Parameter and Statistic A measure that describes a population is called a parameter. A measure that describes a sample is called statistic. There is a simple and straightforward way to remember what a parameter and statistic are measuring. All that we must do is look at the first letter of each word. A parameter measures something in a population and a statistic measures something in a sample. Examples: Parameter: the average IQ obtained from the entire population of grade 11 students Statistic: the average IQ obtained from a sample of grade 11 students Parameter: The average weekly allowance of all Grade 11 male students Statistic: The average weekly allowance of a sample of 60 male students Parameter: The average time spent by all the teachers at a certain school in sorting Self-Learning Modules is 2.2 hours. Statistic: A survey revealed that from the randomly selected sample of 400 high school students in the Albay Division, 75% do not have internet connection at home . In population parameter, mean is represented by M, 2 represents variance, and o represents standard deviation. " In sample statistics, sample mean is represented by X, $2 represents sample variance and s represents sample standard deviation.Activity 1 ACTIVITY 1. RANDOM SAMPLE OR NOT? Determine whether the process of getting a sample in each situation is by random sampling or not. 1. To determine the common T-shirt size his students have, Mr. Santos draw his sample from a bowl containing the names of his students with their T-shirt sizes . 2. To determine the most liked subject in their school, Sarah interviewed the president of each class. 3. To know the most preferred learning modality of his classmates, Joseph interviewed their class officers. 4. To determine the performance of of the SHS students in Statistics, the teacher draws 5 students from every SHS class to take the Statistics test. 9AT S YTIVITOA ACTIVITY 2: IDENTIFY ME! Identify the type of random sampling illustrated by the following situations. 1. A barangay chairman wants to know whether his constituents are in favor or not on putting satellite markets in their barangay. He wants to select a sample of 200 from his constituents, from the youths, adults and from the senior citizens. 2. A researcher selected the participants of his study by selecting every 5th member of the population. 3. A researcher used his computer in randomly selecting a sample of n = 240 from a population of 800. 4. A researcher surveyed all teachers in each of the 12 randomly selected secondary schools in Albay. rope 101 . meli rope ni Ybut? e eril of releg ACTIVITY 3: THINK ABOUT IT! Give one research situation where each of the random sampling methods is being applied. 1. Simple Random Samplingout mott atrebuke I sbpig to ego 2. Systematic Random Sampling 3. Stratified Random Sampling 4, Cluster SamplingActivity 2 A Learning Competency: The learner distinguishes between parameter and statistic. (M11/12SP-IIIc-3)VIA enimisled ACTIVITY 1: TRUE OR FALSE? Determine whether the statement is true or false. Write T if the statement is true and F if false on the blank provided before each item. 1. The given value in "The average score of all the TVL students in Statistics and Probability of a certain school is 83%%." is a parameter. 2015 dope to friebizgig 2. An example of a parameter is $2. I benelsig 3. The descriptive measure computed from the entire population of data is called parameter. 4. The average age of all the grade 11 students is an example of statistic. i enimmaisb o ACTIVITY 2: PARAMETER OR STATISTIC? ext of ablo 2H& vieve monl airsbute c zwoo Identify whether the given value is a parameter or a statistic. IBM YTITHEGI :S YTIVITOA Inebi 1. A researcher found out that the average salary of all the employees in a certain company is Php 16,240. 2. The average score of 36 out of 150 Grade 11 students in an examination is 46. no fort _3. Based on a sample of 400 students, it was found out that 78% of them do not have gadgets for online learning. _4. The teacher surveyed all 48 students in her advisory class about their preferred distance learning OAS delivery modality and found out that 83% of them wanted modular learning. ACTIVITY 3: WHICH IS WHICH? .008 to noitelugoq o moil it to rope ni merlobet llo beyeviug tendinezel A Read the statistical study in each item. For each study, identify both the parameter and the statistic. Refer to the example below. Example: A researcher wants to determine the average time spent by grade 11 students in reading answering Statistics modules. From a random sample of 60 grade 11 students, he obtained a sample mean time of 4.2 hours. eliggo Parameter: The average time spent by all grade 11 students in reading and answering Statistics modules Statistic: The average time of 4.2 hours from a sample of 60 grade 11 students 1. A teacher wants to determine the average age of grade 11 students. From a random sample of 40 students, the teacher obtained an average age of 17. Parameter: nobap pitometeyes Statistic: 2. A teacher wants to know the average time spent in playing online games of his advisory class. He surveyed a random sample of 30 students and found out that they spend an average of 4 hours per day in playing online games. Parameter: Statistics: 3. A researcher wants to determine the average time spent by Statistics teachers in preparing learning activity sheets. She randomly selected 50 teachers and obtained an average time of 2.5 hours. Parameter:_ Statistic