Human Resource Management  ·  Level 5
Business Mathematics And Statistics
Chapter 7: Apply Basic Probability Theory
📚 6 Topics
What you will be able to do

By the end of this chapter, you will be able to:

  • Identify different probability events correctly based on workplace needs.
  • Determine various types of probability events accurately following workplace requirements.
  • Apply the rules of probability using both additive and multiplicative methods correctly.
  • Use Bayes’ Theorem accurately by following its rules step-by-step.
  • Draw clear and detailed probability trees to represent different events.
  • Solve real business problems effectively by applying key probability concepts.

Mastering these skills will help you make smarter decisions and solve problems confidently in any business setting.

Probability theory is fundamental for human resource professionals who analyze workforce data and make decisions under uncertainty. Understanding probability allows HR managers to assess risks, predict outcomes such as employee turnover or recruitment success, and optimize resource allocation. This chapter introduces basic probability concepts and event types relevant to HR contexts in Kenya, such as evaluating the likelihood of hiring qualified candidates or predicting absenteeism patterns.

7.1 Probability events

Probability events describe possible outcomes of an experiment or situation relevant to HR decisions. In HR, events could be selecting an employee with a certain skill, or an applicant passing a test. The probability of an event quantifies how likely it is to occur, expressed as a number between 0 (impossible) and 1 (certain). The basic formula for probability of an event \(E\) is:

$$ P(E) = \frac{\text{Number of favorable outcomes}}{\text{Total number of possible outcomes}} $$

Worked Examples

Example 1: In a recruitment drive, a bank has 10 applicants, 4 of whom have a diploma. What is the probability of selecting an applicant with a diploma?

Given:
Number of favorable outcomes = 4
Total outcomes = 10

$$ P(\text{Diploma}) = \frac{4}{10} $$

$$ = 0.4 $$

Answer: 0.4

Example 2: A SACCO has 15 employees, 5 are female. What is the probability of randomly selecting a female employee?

Given:
Favorable outcomes = 5
Total outcomes = 15

$$ P(\text{Female}) = \frac{5}{15} $$

$$ = \frac{1}{3} \approx 0.333 $$

Answer: 0.333

Example 3: At a hotel, 12 applicants took a test; 3 scored above 80%. What is the probability of randomly selecting an applicant with a score above 80%?

Given:
Favorable outcomes = 3
Total outcomes = 12

$$ P(\text{Score} > 80\%) = \frac{3}{12} $$

$$ = 0.25 $$

Answer: 0.25

Example 4: In a county government office, 7 out of 20 employees are on leave on a particular day. What is the probability a randomly chosen employee is on leave?

Given:
Favorable outcomes = 7
Total outcomes = 20

$$ P(\text{On leave}) = \frac{7}{20} $$

$$ = 0.35 $$

Answer: 0.35

Example 5: A cooperative has 50 members; 10 are new recruits. What is the probability of selecting a new recruit as a committee member randomly?

Given:
Favorable outcomes = 10
Total outcomes = 50

$$ P(\text{New recruit}) = \frac{10}{50} $$

$$ = 0.2 $$

Answer: 0.2

Practice Questions

  1. A retail store has 30 employees; 6 have undergone customer service training. What is the probability of selecting an employee who has received training? (2 marks)

  2. In a university, 25 out of 100 employees are in the HR department. Calculate the probability of randomly selecting an HR employee. (2 marks)

  3. During recruitment, 8 out of 40 applicants passed the written test. What is the probability of selecting an applicant who passed? (3 marks)

  4. A bank has 60 employees; 15 are on probation. Find the probability of selecting an employee on probation. (2 marks)

  5. At a farm, 12 out of 50 workers are seasonal workers. Determine the probability of choosing a seasonal worker. (2 marks)

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🔒7.2 Types of events

In HR probability analysis, different types of events describe how outcomes relate to each other. Understanding event types helps in modeling recruitment, training success, or absenteeism scenarios accurately. This section covers simple, compound, mutually exc…

🔒7.3 Application of rules of probability

In Human Resource management, understanding the probability of various events such as employee turnover, recruitment success, or training effectiveness is crucial for decision-making. Rules of probability help HR professionals quantify uncertainties and make i…

🔒7.4 Application of Bayes' Theorem

Bayes' Theorem is a powerful tool for updating probabilities based on new information, widely used in HR for decisions like predicting employee turnover based on observed behaviours or test results. It allows HR professionals to revise the likelihood of an eve…

🔒7.5 Drawing probability trees

In Human Resource management in Kenya, probability trees are essential for visualizing and calculating the likelihood of sequential events such as recruitment outcomes, employee retention, or training success. By mapping out possible scenarios and their probab…

🔒7.6 Application of probability

Probability theory is widely used in Human Resource management in Kenya for decision-making under uncertainty. Applications include predicting employee turnover, assessing recruitment success, estimating training outcomes, and evaluating risks related to absen…

Chapter Summary

This chapter introduced the concept of probability events as the foundation for understanding chance in business mathematics and statistics. It explored various types of events including simple, compound, mutually exclusive, independent, and dependent events, highlighting their characteristics and differences. The chapter then demonstrated how to apply fundamental rules of probability to calculate the likelihood of different outcomes. Bayes' Theorem was presented as a powerful tool for revising probabilities based on new information. Techniques for drawing probability trees were explained to visually represent complex event sequences and aid in systematic probability calculation. Finally, the chapter emphasized practical applications of probability theory in decision-making processes, reinforcing its relevance in real-world business contexts.

Self-Assessment

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Written Assessment

  1. In a company, the probability that a randomly selected employee is from the Human Resource department is 0.2. What is the probability that the employee is not from the HR department? (2 marks)

  2. The probability that an employee is skilled in payroll management is 0.4, and the probability that an employee is skilled in recruitment is 0.3. Assuming these skills are mutually exclusive, what is the probability that a randomly selected employee has either payroll management skills or recruitment skills? (3 marks)

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Chapter Examination Questions

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SECTION A (40 Marks) - Answer ALL Questions

  1. A Human Resource manager at a Nairobi-based retail company knows that 60% of employees have completed a training program. If one employee is selected at random, what is the probability that the employee has completed the training? (4 marks)
  2. In a recruitment exercise, the probability that a candidate has a diploma is 0.7, and the probability that the candidate has work experience is 0.5. If the events are independent, find the probability that a candidate has both a diploma and work experience. (4 marks)
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Am I competent?

At the start of this chapter we promised you would be able to:

  • Identify different probability events correctly based on workplace needs.
  • Determine various types of probability events accurately following workplace requirements.
  • Apply the rules of probability using both additive and multiplicative methods correctly.
  • Use Bayes’ Theorem accurately by following its rules step-by-step.
  • Draw clear and detailed probability trees to represent different events.
  • Solve real business problems effectively by applying key probability concepts.

Tick each one you can genuinely do.

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