Understanding Data and Information - Business Decision Making - ثاني ثانوي

Chapter 9 Using Data to Support the Decision Making Process There are many different ways to make a decision or approach a problem. Some decisions are made by tossing a coin in the air. Other decisions are made on the basis of instinct and "gut feeling". Important decisions should be made objec- tively and, ideally, supported with measurable data. In this chapter, you will be introduced to data-driven decision making and problem solving. After finishing school, Ahmed begins working for a company that produces a variety of temperature gauges and sensors. These precision instruments are used in a variety of industrial, manufacturing, and medical applications. Each quarter, the accounting department produces financial statements and production reports for the company. LEARNING OBJECTIVES Once you have completed this chapter, you should be able to: 1 Understand Data and Information 2 Follow the Data Analysis Process 3 Collect Data to Support Decision Making 4 Describe Data with Statistics 5 Describe a Dataset's Variability 35.91 6 Work with Spreadsheets 7. ::: Creat Create an Excel Spreadsheet Using Data to Support the Decision Making Process 283 وزارة التعليم Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 283 5418.835 66300 -29 30/06/2023 14:28

284 9 Chapter رة ا Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 284 During the past three months, the number of sensors that failed quality-con- trol testing has increased significantly. This, in turn, has had an adverse effect on the company's profits. Ahmed's manager asks him to determine what the prob- lem is and recommend solutions to fix the situation. During his lunch break, Ahmed mentions this project to several coworkers. "Oh, that's an obvious problem," remarks a colleague, Ali. "The company has steadily increased its production quota for those sensors, but they haven't hired any additional assembly workers. No wonder there is a quality problem. Everyone on that assembly line is scrambling to keep up with orders." Is this really the underlying cause of the company's quality-control issues? Based on this anecdotal feedback, should Ahmed feel comfortable presenting this to his manager? Might there be other issues to consider? If so, how could he determine what they are? In most businesses and organizations, problems routinely arise and call for informed decisions to be made. The way that people examine, evaluate, and address these matters impacts the quality of the solutions. Learning how to objectively and quantitatively assess and evaluate available data will help you to become a more effective problem solver. In this chapter, we will explore the fundamentals of data and data analysis to support the decision making process. As a result of this transition into "hard skills", the figures and illustrations are integrated into the examples throughout the chapter to aid understanding of the processes. Definition boxes are also introduced to explain key terminology, while Q&A boxes provide additional step-by-step hints in the final lesson. 30/06/2023 14:28

Lesson 1 Chapter 9 www.ien.edu.sa Understanding Data and Information 1-1 Why Data? There is an old saying that "without data, you are just another person with an opinion." While anecdotes and coincidences may make for interesting stories, you wouldn't want to make important decisions on the basis of anecdotes alone. For example, just because a friend of a friend ate 16 apricots and then experi- enced relief from joint pain doesn't mean that this is all you need to know to help one of your parents choose a treatment for arthritis! Before recommending that they start eating apricots, you would definitely want to consider relevant data—that is, data that would allow you to investigate the effectiveness of apricots as a treatment for arthritis. It is challenging to function in today's world without a basic understanding of data analysis and statistics. Studying statistics will also enable you to collect data in a sensible way and then use the data to answer questions of interest. In addition, studying data analysis will allow you to critically evaluate the work of others by providing you with the tools you need to make informed judgments. Let's start by developing an under- standing of data collection, data, different types of data, and information. وزارة التعليم Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 285 DEFINITIONS Data: Known facts used as a basis for analysis. Data analysis: The different methods used to interpret data. Statistics: The collection and analysis of numerical data. 1-2 Collecting Data Before you can analyze your data, you first need to collect it. There are many methods of data collection. They include: Surveys: Researchers and businesses all use surveys to gather data. This method of data collection is typically used to generate responses about individuals' prefer- ences, opinions, and habits. Respondents will usually be asked "closed" ques- tions, designed to provide simple answers such as "yes" or "no", or multiple-choice questions, so answers can be grouped together for analysis and comparison. Using Data to Support the Decision Making Process 285 30/06/2023 14:28

286 9 Chapter رة ا Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 286 . Interviews: When an organization wants to collect more detailed information, they may use interviews to gather data. An interview often uses a more "open" form of question, allowing the respondent to answer more fully and even, in some cases, to direct the flow of the conversation. Interviews can be structured, semi-structured, or unstructured, depending on the objectives of the interviewer. The data this method produces requires more detailed analysis as it is usually less statistical. Focus groups: Like an interview, the questions in a focus group can be more open, but in this case multiple respondents are asked the questions at the same time, and are invited to share their responses with each other, and even to discuss their ideas between themselves. Many businesses use focus groups to "test" a new product or idea and use the data they collect to influence its ongoing development. Tracking: Tracking is an increasingly common method in the modern world, although it has been in use for a long time. Tracking involves collecting data about a customer's behavior, habits, and purchases in "real time". For instance, supermarkets record information about customer purchases to inform all sorts of choices: if a product is selling well, they may increase their order; if the store is busier at certain times of the day, they may increase the number of staff working at that time; if a particular product is popular with a specific group of people, they may use that information to change their marketing. Tracking is also used online: Web sites record how many visitors they have, who is clicking on their advertisements, and even what device they are using. 1-3 Data Sets The individuals or objects in any particular population might possess many characteristics that could be studied. DEFINITION Population: Any finite or infinite collection of items under discussion. Consider a group of students currently enrolled in a math class: One characteristic of the students in the population is the brand of calculator they use. Another characteristic is the number of textbooks used that semester, and yet another is the distance from the school to each student's home. A variable is any characteristic whose value may change from one individual or object to another. For example, calculator brand is a variable, and so are number of textbooks used and distance to the school. Data results from making observations either on a single (univariate) variable or on two or more (multivariate) variables at the same time. 30/06/2023 14:28

QUICK TIP It's important to remember that you can easily perform mathematical calculations on numerical data. Categorical data can only be sorted and counted. . DEFINITION Variable: Any characteristic (of a population) whose value may change from one individual object to another. There are two types of univariate data sets: categorical (sometimes also called qualitative or nominal) and numerical (sometimes also called quantitative). In the previous example, calculator brand is a categorical variable, because each stu- dent's response to the query, "What brand of calculator do you use?" is a cate- gory. The collection of responses from all these students forms a categorical data set. The other two variables, number of textbooks purchased and distance to the school, are both numerical in nature. Determining the values of a numerical vari- able (by counting or measuring) results in a numerical data set. There are two different types of numerical data: discrete and continuous. Consider a number line for locating values of a numerical variable. Each possible number (2, 3.125, 8.12976, etc.) corresponds to exactly one point on the num- ber line. Suppose that the variable of interest is the number of courses in which a student is enrolled. FIGURE 9-1: A number line representing the number of courses in which a student is enrolled 0 1 2 3 4 5 6 7 8 QUICK TIP In general, data are contin- uous when observations involve making measure- ments, as opposed to counting. If no student is enrolled in more than eight courses, the possible values are 1, 2, 3, 4, 5, 6, 7, and 8. These values are identified in Figure 9-1 by the dots at the points marked 1, 2, 3, 4, 5, 6, 7, and 8. Because students either take a class, or they don't, the values for this variable are discrete. A student cannot take 4.32167 classes. On the other hand, the line segment in Figure 9-2 identifies a plausible set of possible values for the time (in seconds) it takes for the first kernel in a bag of microwave popcorn to pop when heated. Here the possible values can be any point on the number line. These time values are said to be continuous. This is because each kernel of popcorn will pop when its internal tempera- ture reaches a critical point. This doesn't necessarily happen at discrete times (in seconds). FIGURE 9-2: A number line representing the times taken for the first kernel in a bag of popcorn to pop when heated وزارة التعليم Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 287 10 11 12 13 14 15 16 17 18 Using Data to Support the Decision Making Process 287 30/06/2023 14:28

288 9 Chapter رة ا Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 288 DEFINITIONS Discrete data: Where values are whole; or yes/no. Continuous data: Data that can take any value, such as height, weight, temperature. Some numerical data is logically organized in a particular order or sequence. This data is said to use an ordinal scale. For example: you might construct a custom- er-satisfaction survey to measure your clients' opinions on their shopping experi- ence. The questionnaire would ask, "On a scale of 1-5, how would you rate your shopping experience?" (1 - Unsatisfactory, 3 - Neutral, 5 - Very Satisfactory). Because there is a rank ordering associated with the responses, they fall on an ordinal scale. DEFINITION Ordinal scale: Where data is organized in a particular order or sequence. Information is broadly defined as data that has been organized, analyzed, or visualized in a way that makes it more valuable. By themselves, individual ele- ments of a data set are of limited value. However, when a statistical analysis is performed on the data, the results are more useful. As a general rule, raw data by itself is seldom informative enough to be actionable. We wouldn't make decisions or solve problems based on the data alone. When the data is transformed into information, it is more likely to be actionable. DEFINITION Information: Data that has been organized, analyzed, or visualized in a way that makes it more valuable. Let's look at another example. The number of text messages sent on a partic- ular day is recorded for each of 12 students. The resulting data set is: 23 0 14 13 15 0 60 82 0 40 41 22 Possible values for the variable number of text messages sent are 0, 1, 2, 3, These are isolated points on the number line, so this data set consists of discrete numerical data. 30/06/2023 14:28

YOU TRY IT Suppose that instead of the number of text messages sent, the time spent texting had been recorded. Even though time spent may have been reported rounded to the nearest minute, the actual time spent could have been 6 minutes, 6.2 minutes, 6.28 minutes, or any other value in an entire interval. So, recording values of time spent texting would result in continuous data. 1-4 Representing Data Sets How to Construct a Dot Plot 1. Draw a horizontal line and mark it with an appropriate measurement scale. 2. Locate each value in the data set along the measurement scale, and represent it by a dot. If there are two or more observations with the same value, stack the dots vertically. Dot plots convey information about: • A representative or typical value in the data set. • The extent to which the data values vary. • The shape of the distribution of values along the number line. • The presence of unusual values in the data set. How to Construct a Bar Chart 1. Draw a horizontal axis, and write the category names or labels below the line at equally spaced intervals. 2. Draw a vertical axis, and label the scale using either frequency or relative fre- quency. 3. Place a rectangular bar above each category label. The height is determined by the category's frequency or relative frequency, and all bars should have the same width. With the same width, both the height and the area of the bar are propor- tional to frequency and relative frequency. Carry out online research to find an example of categorial data and an example of numerical data. With each example, explain the characteristics that have helped you to classify which type of data it is. For the numerical data example, explain whether the data is discrete or continuous, giving reasons for your answer. وزارة التعليم Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 289 Using Data to Support the Decision Making Process 289 30/06/2023 14:28

REVIEW QUESTIONS 1. If an organization wants to collect a large amount of data from multiple customers at the same time, they should use: a. interviews b. focus groups c. surveys d. tracking 2. Classify each of the following variables as either categorical or numerical. a. number of students in a class of 35 who submit an assignment before the due date b. gender of the next baby born at a particular hospital c. amount of fluid (in centiliters) dispensed by a machine used to fill bottles with soda pop d. thickness of the gelatin coating of a vitamin E capsule 3. For the following numerical variables, state whether each is dis- crete or continuous. a. the length of a one-year-old snake b. the latitude of a location in Saudi Arabia selected by pointing a finger on a map of the Kingdom while blindfolded c. the distance from the left edge at which a 30cm plastic ruler snaps when bent sufficiently to break d. the price per liter paid by the next customer to buy gas at a particular station 4. In a survey of 100 people who had recently purchased motorcycles, data on the following variables were recorded: • age of the purchaser (in years) • brand of motorcycle purchased • number of previous motorcycles owned by purchaser • telephone area code of purchaser • weight of motorcycle as equipped at purchase. a. Which of these variables are categorical? b. Which of these variables are discrete? c. Which graphical display would be an appropriate choice for summariz- ing the age data: a bar chart or a dot plot? d. Which graphical display would be an appropriate choice for summariz- ing the weight data: a bar chart or a dot plot? 290 9 Chapter رة ا Ministry of Education 2024-1446 Business Decision Making S1 S2 S3.indb 290 30/06/2023 14:28