Good Samaritan Colleges Math 100 Finals Lesson 1 PDF

Welcome to our MATH class! PROBABILITY AND STATISTICS in Daily Life Prepared by: VHERLINE A. DOROIN,LPT INSTRUCTOR I  OBJECTIVES Explain basic probability concepts, and data 1 collection methods. Recognize the importance of probability and 2 statistical a...

Welcome to our MATH class! PROBABILITY AND STATISTICS in Daily Life Prepared by: VHERLINE A. DOROIN,LPT INSTRUCTOR I  OBJECTIVES Explain basic probability concepts, and data 1 collection methods. Recognize the importance of probability and 2 statistical analysis in making informed decisions and assessing risks in daily life. Collect and analyze data, perform statistical 3 calculations, and use results to evaluate risks and support decision-making in practical scenarios.  BASIC CONCEPT OF PROBABILITY 1 Probability  It is branch of mathematics that deals with the likelihood or chance of different events occurring.  BASIC CONCEPT OF PROBABILITY 1 Probability  Probabilities are expressed as numbers between 0 and 1, where 0 represents impossibility and 1 represents certainty.  A probability of 0 means the event will not occur.  BASIC CONCEPT OF PROBABILITY 1 Probability  A probability of 1 means the event will certainly occur.  A probability of 0.5 suggests that the event has an equal chance of occurring or not.  BASIC CONCEPT OF PROBABILITY 1 Examples  Rolling a 5 on a six-sided die. = *The probability of getting 5 in a six-sided die is  BASIC CONCEPT OF PROBABILITY 1 Examples  Flipping a coin and getting head. = *The probability of getting head is  BASIC CONCEPT OF PROBABILITY 1 Statistics  The word “statistics” and “statistical” are derived from the Latin word status, means  It political state. is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. 2 DATA COLLECTION AND ANALYSIS DATA COLLECTION  It refers to the systematic process of gathering information or facts to answer research questions or test hypotheses.  Data can be categorized into two types. 2 DATA COLLECTION AND ANALYSIS Types of Data 1. Quantitative Data: This is numerical and can be measured, such as heights, weights, and scores. 2. Qualitative Data: This is descriptive and categorical, such as colors, names, or types of objects. 2 DATA COLLECTION AND ANALYSIS Methods of Data Collection 1. Surveys and Questionnaires: A popular method for collecting data from large groups. Surveys can be administered in person, by mail, or online. 2 DATA COLLECTION AND ANALYSIS Methods of Data Collection 2. Interviews: Qualitative in nature, interviews allow for in-depth exploration of a subject but can be time-consuming and subject to interviewer bias. 2 DATA COLLECTION AND ANALYSIS Methods of Data Collection 3. Experiments: Controlled environments where variables are manipulated to observe their effect on other variables. 2 DATA COLLECTION AND ANALYSIS Methods of Data Collection 4. Observational Studies: Observing and recording behavior or events without manipulating variables 5. Secondary Data: Using existing data collected by other researchers or organizations, such as government census data or industry reports 2 DATA COLLECTION AND ANALYSIS DATA ANALYSIS  Once data is collected, it must be analyzed to extract meaningful insights. STEPS IN DATA ANALYSIS 1. Data Cleaning: This involves checking for missing, incomplete, or inconsistent data and addressing these issues 2 DATA COLLECTION AND ANALYSIS DATA ANALYSIS 2. Descriptive Statistics: Summarizing the main features of a dataset using measures such as the mean, median, mode, range, variance, and standard deviation. 3. Inferential Statistics: Making predictions or inferences about a population based on a sample. 2 DATA COLLECTION AND ANALYSIS DATA ANALYSIS 4. Visualization: Graphical representations such as histograms, bar charts, and scatter plots are used to identify patterns, trends, or anomalies in the data. 3 APPLICATION IN RISK ASSESSMENT AND DECISION MAKING FINANCIAL RISK  Evaluating assessment opportunities assessing creditworthiness, and managing portfolio risk. 3 APPLICATION IN RISK ASSESSMENT AND DECISION MAKING OPERATIONAL RISK  Identifying and mitigating potential disruptions to business processes, such as supply chain interruptions or technology failures. 3 APPLICATION IN RISK ASSESSMENT AND DECISION MAKING ENVIRONMENTAL RISK  Assessing the potential impact of environmental factors on business operations, such as climate change or natural disasters. 3 INFORMED DECISION MAKING DATA-DRIVEN DECISIONS  Probability and statistics provide a framework for making informed decisions based on data analysis. This allows us to move beyond intuition and rely on evidence to guide our choices. 3 INFORMED DECISION MAKING RISK MANAGEMENT  Understanding probability helps us assess and manage risks effectively. We can use statistical techniques to identify potential risks, evaluate their likelihood, and implement strategies to mitigate them. 3 INFORMED DECISION MAKING STRATEGIC PLANNING  Probability and statistics are essential tools for strategic planning allowing us to forecast future trends, analyze market opportunities, and develop effective plans to achieve our objectives. 3 INFORMED DECISION MAKING CONTINOUS IMPROVEMENT  By using data analysis to monitor performance and identify areas for improvement, we can continuously refine our processes and make better decisions over time. THANK YOU!