A professor at a university has received a few complaints of the exams being too difficult. The professor is looking at exam performance results over the past 5 years to understand the normal tendency and outliers. Which chart should the professor use?
A scatterplot is a type of chart that shows the relationship between two variables by plotting data points on a two-dimensional plane. A scatterplot can help the professor to understand the normal tendency and outliers of exam performance results over the past 5 years by displaying the distribution, trend, and correlation of the data. For example, the professor can use the x-axis to represent the year and the y-axis to represent the exam score, and see how the scores vary over time and across different exams. Outliers can be identified as data points that are far away from the main cluster or the line of best fit12 Reference: 1: Scatter Plot - Statistics How To 2: Scatterplots - IIBA BABOK Guide v3
A business analyst is conducting a series of interviews to understand the research questions that will be explored within a new analytics project. Which of the following is true about interviews?
Interviews are a technique to elicit information from stakeholders and subject matter experts. Interviews can be planned or unplanned, structured or unstructured, depending on the context and purpose of the interview. However, regardless of the type of interview, it is important to have clear goals for the interview, such as what information is needed, what questions will be asked, and how the information will be used. Having clear goals for the interview helps the interviewer to prepare, conduct, and follow up the interview effectively, and also helps the interviewee to understand the expectations and provide relevant and accurate information. Reference:Guide to Business Data Analytics, page 25;Certification in Business Data Analytics Handbook, page 9;How to Ace Your Next Business Analysis Job Interview
Operation managers are concerned about the increasing attrition rates in the call center. A series of interviews is being conducted with call center agents to collect information to better understand the problem. Interviewees will ask open and closed ended questions that are both quantitative and qualitative. Which of the following is considered a qualitative open-ended question?
A qualitative open-ended question is a question that allows the respondent to express their thoughts, feelings, or opinions in their own words, without being constrained by predefined options or categories. A qualitative open-ended question can help the interviewer explore the underlying reasons, motivations, or perceptions of the respondent. Option A is a qualitative open-ended question, because it asks the respondent to explain how call volume affects their job satisfaction and well-being, which may vary from person to person and require elaboration. Options B, C, and D are not qualitative open-ended questions, because they ask the respondent to choose between two alternatives (B and D) or provide a numerical value , which are quantitative and closed-ended responses. Reference:
* Business Analysis Certification in Data Analytics, CBDA | IIBA, CBDA Competencies, Domain 2: Source Data
* Understanding the Guide to Business Data Analytics, page 14
* CERTIFICATION IN BUSINESS DATA ANALYTICS HANDBOOK - IIBA, page 8, CBDA Exam Sample Questions and Self-Assessment, Question 9
What type of data model describes the highest level of relationship between entities and represents how a business perceives its information?
A large number of text messages are received by Twitter each year making Twitter one example of Big Data. What data characteristic represents this large number of text messages?
Velocity is one of the four V's of Big Data, along with Volume, Variety, and Veracity. Velocity refers to the speed at which data is generated, collected, and processed. A large number of text messages received by Twitter each year is an example of high-velocity data, as it requires real-time or near-real-time processing and analysis to extract insights and value from it. High-velocity data poses challenges and opportunities for business data analytics, as it requires efficient and scalable data infrastructure, streaming analytics, and timely decision-making.
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