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Statistics Probability Q3 Mod1 Random Variables and Probability Distributions

Statistics and Probability Alternative Delivery Mode Quarter 3 – Modul...

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Statistics and

Probability

Quarter 3 – Module 1:

Random Variables and

Probability Distributions

Statistics and Probability Alternative Delivery Mode Quarter 3 – Module 1: Random Variables and Probability Distributions First Edition, 2020

Republic Act 8293, section 176 states that: No copyright shall subsist in any work of the Government of the Philippines. However, prior approval of the government agency or office wherein the work is created shall be necessary for exploitation of such work for profit. Such agency or office may, among other things, impose as a condition the payment of royalties.

Borrowed materials (i., songs, stories, poems, pictures, photos, brand names, trademarks, etc.) included in this module are owned by their respective copyright holders. Every effort has been exerted to locate and seek permission to use these materials from their respective copyright owners. The publisher and authors do not represent nor claim ownership over them.

Published by the Department of Education Secretary: Leonor Magtolis Briones Undersecretary: Diosdado M. San Antonio

SENIOR HS MODULE DEVELOPMENT TEAM

AUTHOR : Chelsea Mae B. Brofar Co-Author – Language Editor : Mee Ann Mae Loria - Tungol Co-Author – Content Evaluator : Haren B. Valencia Co-Author – Illustrator : Chelsea Mae B. Brofar Co-Author – Layout Artist : Chelsea Mae B. Brofar

TEAM LEADERS School Head : Reycor E. Sacdalan, PhD LRMDS Coordinator : Pearly V. Villagracia

SDO-BATAAN MANAGEMENT TEAM Schools Division Superintendent : Romeo M. Alip, PhD, CESO V OIC- Asst. Schools Division Superintendent : William Roderick R. Fallorin, CESE Chief Education Supervisor, CID : Milagros M. Peñaflor, PhD Education Program Supervisor, LRMDS : Edgar E. Garcia, MITE Education Program Supervisor, AP/ADM : Romeo M. Layug Education Program Supervisor, Senior HS : Danilo C. Caysido Project Development Officer II, LRMDS : Joan T. Briz Division Librarian II, LRMDS : Rosita P. Serrano

REGIONAL OFFICE 3 MANAGEMENT TEAM Regional Director : May B. Eclar, PhD, CESO III Chief Education Supervisor, CLMD : Librada M. Rubio, PhD Education Program Supervisor, LRMS : Ma. Editha R. Caparas, EdD Education Program Supervisor, ADM : Nestor P. Nuesca, EdD

####### Introductory Message

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.

In addition to the material in the main text, Notes to the Teacher are also provided to our facilitators and parents for strategies and reminders on how they can best help you on your home-based learning.

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.

If you have any questions in using this SLM or any difficulty in answering the tasks in this module, do not hesitate to consult your teacher or facilitator.

Thank you.

####### What I Need to Know

After going through this module, you are expected to:

Illustrate a random variable (discrete or continuous). M11/12SP-IIIa-
Distinguish between a discrete and continuous random variable. M11/12SP- IIIa-
Find possible values of a random variable. M11/12SP-IIIa-
Illustrate a probability distribution for a discrete random variable and its properties. M11/12SP-IIIa-
Compute probabilities corresponding to a given random variable. M11/12SP- IIIa-

B. Classify the following random variables as discrete or continuous****.

The weight of the professional wrestlers
The number of winners in lotto for each day
The area of lots in an exclusive subdivision
The speed of a car
The number of dropouts in a school per district

C. Determine the values of the random variables in each of the following distributions.

Two coins are tossed. Let T be the number of tails that occur. Determine the values of the random variable T.
A meeting of envoys was attended by 4 Koreans and 2 Filipinos. If three envoys were selected at random one after the other, determine the values of the random variable F representing the number of Filipinos.

####### Lesson

1

Random Variables and

Probability Distribution

You have learned in your past lessons in junior high school Mathematics that an experiment or trial is any procedure or activity that can be done repeatedly under similar conditions. The set of all possible outcomes in an experiment is called the sample space. The concept of probability distribution is very important in analyzing statistical data especially in hypothesis testing.

In this lesson, you will explore and understand the random variable.

Before we discuss probability distribution, it is necessary to study first the concept of random variable. Try to do the next activity to prepare you for this lesson. Stay focused.

####### What’s In

A. Identify the term being described in each of the following: 1. Any activity which can be done repeatedly under similar conditions 2. The set of all possible outcomes in an experiment 3. A subset of a sample space 4. The elements in a sample space 5. The ratio of the number of favorable outcomes to the number of possible outcomes B. Answer the following questions.

In how many ways can two coins fall?
If three coins are tossed, in how many ways can they fall?
In how many ways can a die fall?
In how many ways can two dice fall?
How many ways are there in tossing one coin and rolling a die?

Notes to the Teacher This part aims to assess if the students have prior knowledge about the topic. Also, it prepares the students to absorb the lesson.

Example 1

Suppose two coins are tossed and we are interested to determine the number of tails that will come out. Let us use T to represent the number of tails that will come out. Determine the values of the random variable T.

Solution:

Steps Solution

List the sample space S = {HH, HT, TH, TT}
Count the number of tails in each outcome and assign this number to this outcome.

Outcome Number of Tails (Value of T) HH 0 HT 1 TH 1 TT 2

Conclusion The values of the random variable T (number of tails) in this experiment are 0, 1 and 2.

Example 2

Two balls are drawn in succession without replacement from an urn containing 5 orange balls and 6 violet balls. Let V be the random variable representing the number of violet balls. Find the values of the random variable V.

Solution:

Steps Solution

List the sample space S = {OO, OV, VO, VV}
Count the number of violet balls in each outcome and assign this number to this outcome.

Outcome Number of Violet balls (Value of V) OO 0 OV 1 VO 1 VV 2 3. Conclusion The values of the random variable V (number of violet balls) in this experiment are 0, 1, and 2.

Example 3

A basket contains 10 red balls and 4 white balls. If three balls are taken from the basket one after the other, determine the possible values of the random variable R representing the number of red balls.

Solution:

Steps Solution

List the sample space S = {RRR, RRW, RWR, WRR, WWR, WRW, RWW, WWW}
Count the number of red balls in each outcome and assign this number to this outcome.

Outcome Number of Red balls (Value of R) RRR 3 RRW 2 RWR 2 WRR 2 WWR 1 WRW 1 RWW 1 WWW 0 3. Conclusion The values of the random variable R (number of red balls) in this experiment are 0, 1, 2, and 3.

Example 5

A pair of dice is rolled. Let X be the random variable representing the sum of the number of dots on the top faces. Find the values of the random variable X.

Solution:

Steps Solution

List the sample space S = {(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (2, 1), (2, 2), (2, 3), (2, 4), (2, 5), (2, 6), (3, 1), (3, 2), (3, 3), (3, 4), (3, 5), (3, 6), (4, 1), (4, 2), (4, 3), (4, 4), (4, 5), (4, 6), (5, 1), (5, 2), (5, 3), (5, 4), (5, 5), (5, 6), (6, 1), (6, 2), (6, 3), (6, 4), (6, 5), (6, 6)}
Count the sum of the number of dots in each outcome and assign this number to this outcome.

Outcome Sum of the number of dots (Value of X) (1, 1) 2 (1, 2), (2, 1) 3 (1, 3), (3, 1), (2, 2) 4 (1, 4), (4, 1), (2, 3), (3, 2)

(1, 5), (5, 1), (2, 4), (4, 2), (3, 3)

(1, 6), (6, 1), (2, 5), (5, 2), (4, 3), (3, 4)

(3, 5), (5, 3), (2, 6), (6, 2), (4, 4)

(5, 4), (4, 5), (6, 3), (3, 6)

(6, 4), (4, 6), (5, 5) 10 (5, 6), (6, 5) 11 (6, 6) 12

Conclusion The values of the random variable X (sum of the number of dots) in this experiment are 2, 4, 5, 6, 7, 8, 9, 10, 11, and 12.

Discrete and Continuous Random Variable

A random variable may be classified as discrete and continuous. A discrete random variable has a countable number of possible values. A continuous random variable can assume an infinite number of values in one or more intervals.

Examples:

Discrete Random Variable Continuous Random Variable Number of pens in a box Amount of antibiotics in the vial Number of ants in a colony Length of electric wires Number of ripe bananas in a basket Voltage of car batteries Number of COVID 19 positive cases in Hermosa, Bataan

Weight of newborn in the hospital

Number of defective batteries Amount of sugar in a cup of coffee

What is It

In the previous grade levels in studying Mathematics, we have learned how to make a frequency distribution table given a set of raw data. In this part, you will learn how to construct a probability distribution.

In the previous part of this module, you already learned how to determine the values of discrete random variable. Constructing a probability distribution is just a continuation of the previous part. We just need to include an additional step to illustrate and compute the probabilities corresponding to a given random variable.

Using Example 1 in the previous page,

Steps Solution

List the sample space S = {HH, HT, TH, TT}
Construct the probability histogram.

Using Example 2 in the previous page,

Steps Solution

List the sample space S = {OO, OV, VO, VV}
Count the number of violet balls in each outcome and assign this number to this outcome.

The values of the random variable V (number of violet balls) in this experiment are 0, 1, and 2.

Outcome Number of Violet Balls (Value of V) OO 0 OV 1 VO 1 VV 2

Construct the frequency distribution of the values of the random variable V.

Number of Violet Balls (Value of V)

Number of Occurrence (Frequency) 0 1 1 2 2 1

P(T)

0 1 2

Total 4 4. Construct the probability distribution of the random variable V by getting the probability of occurrence of each value of the random variable.

The probability distribution of the random variable V can be written as follows: V 2 1 0 P(V) 1/4 1/2 1/

Number of Violet balls (Value of V)

Number of Occurrence (Frequency)

Probability P(V)

0 1 1/ 1 2 2/4 or 1/ 2 1 1/ Total 4 1

Construct the probability histogram.

Using Example 4 in the previous page,

Steps Solution

List the sample space S = {HHHH, HHHT, HHTH, HHTT, HTHH, HTHT, HTTH, HTTT, THHH, THHT, THTH, THTT, TTHH, TTHT, TTTH, TTTT}

P(V)

0 1 2

Construct the probability distribution of the random variable T by getting the probability of occurrence of each value of the random variable.

The probability distribution of the random variable T can be written as follows: T 0 1 2 3 4 P(T) 1/16 1/4 3/8 1/4 1/

Number of Tails (Value of T)

Number of Occurrence (Frequency)

Probability P(T)

0 1 1/ 1 4 4/16 or 1/ 2 6 6/16 or 3/ 3 4 4/16 or 1/ 4 1 1/ Total 16 1

Construct the probability histogram.

Using Example 5 in the previous page,

Steps Solution

List the sample space S = {(1, 1), (1, 2), (1, 3), (1, 4), (1, 5), (1, 6), (2, 1), (2, 2), (2, 3), (2, 4), (2, 5), (2, 6), (3, 1), (3, 2), (3, 3), (3, 4), (3, 5), (3, 6), (4, 1), (4, 2), (4, 3), (4, 4), (4, 5), (4, 6), (5, 1), (5, 2), (5, 3), (5, 4), (5, 5), (5, 6), (6, 1), (6, 2), (6, 3), (6, 4), (6, 5), (6, 6)}

P(T) 8

0 1 2

3 4

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