IIBA CBDA IIBA - CBDA Exam Practice Test Instant Access

Question 1

A large telecommunications company wants to increase their Average Revenue Per User per month by 5%, by end of year, to increase revenue in a highly competitive market. From a SMART target perspective, what is missing?

AT - The increase should be seen sooner

BA - It is too easy of a target to attain

CR - Since competition is high, focus should be on increasing customer base and not on
ARPU

DS - There is no mention of which product group/line the target pertains to

Answer : D

A SMART target is one that is specific, measurable, achievable, relevant, and time-bound1. The target of increasing the Average Revenue Per User (ARPU) per month by 5%, by end of year, to increase revenue in a highly competitive market is missing the specificity criterion, as it does not mention which product group or line the target applies to. The target should be more specific and clear about the scope and context of the desired outcome, such as which segment, region, or service the target relates to23. Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 192: SMART Goals: How to Make Your Goals Achievable, MindTools, 2021, 13: How to Set SMART Marketing Goals, CoSchedule, 2021, 2.

Question 2

An analyst at a phone manufacturing company is preparing a dashboard for Senior Executives that will cover past year's performance. It will be used in the upcoming senior leadership team meeting to make strategic decisions for the new year. While analyzing the data, the analyst found a lot of interesting revelations related to performance. What should the analyst keep in mind when preparing the Executive dashboard?

AKeep some sections high-level, and some sections detailed

BKeep it detailed if there is a lot of good information to share

CKeep it high-level, summarizing key insights and metrics

DKeep it detailed so one dashboard can be shared to all levels of the organization

Answer : C

When preparing an executive dashboard, the analyst should keep in mind that the purpose of the dashboard is to provide a quick and clear overview of the past year's performance and to support strategic decision making for the new year. Therefore, the analyst should keep the dashboard high-level, summarizing the key insights and metrics that are relevant and meaningful for the senior executives. The analyst should avoid cluttering the dashboard with too much detail or information that is not essential for the executives. The analyst should also use visual features, such as charts, graphs, and colors, to display the data in an organized and appealing way12 Reference: 1: Executive Dashboards: 10 Reporting Tips and Examples [2023] * Asana 2: How to Create Executive Dashboard & Reports - Ubiq BI

Question 3

A research marketer is interested in collecting information about the spending habits of families in North Americ

a. Concerned about the volume of data required to conduct the research, they choose to use sampling. The dataset is sourced using all credit card transactions from a leading North American credit card company for Quarter 1 of the prior year. The sample used is:

AStatistically representative

BNot relevant

CToo large to be helpful

DBiased

Answer : D

The sample used in this case is biased, meaning that it is not representative of the population of interest. The population of interest is the families in North America, but the sample is drawn from only one source of data: the credit card transactions from a leading North American credit card company. This sample excludes the families who do not use credit cards, or who use other credit card companies, or who use other payment methods. Therefore, the sample is not random or fair, and it may introduce sampling bias into the research results12 Reference: 1: Sampling Methods | Types, Techniques & Examples 2: Sampling Bias - an overview | ScienceDirect Topics

Question 4

There were 7 students enrolled in the Introduction to Artificial Intelligence course. These were the student's scores from the final exam: 64, 70, 80, 80, 90, 98, 100

What is the mean and mode for the outlined scores?

A83.14, 80

B79.84, 81.40

C80,80

D80, 83.14

Answer : A

The mean is the average of all the scores, which is found by adding them up and dividing by the number of scores. The mode is the most frequent score, which is the one that occurs the most times. To find the mean and mode for the outlined scores, we can use the following steps:

* Arrange the scores in ascending order: 64, 70, 80, 80, 90, 98, 100

* Add up the scores: 64 + 70 + 80 + 80 + 90 + 98 + 100 = 582

* Divide the sum by the number of scores: 582 / 7 = 83.14

* The mean is 83.14

* Count how many times each score occurs: 64 occurs once, 70 occurs once, 80 occurs twice, 90 occurs once, 98 occurs once, 100 occurs once

* The score that occurs the most times is 80

* The mode is 80

Therefore, the mean and mode for the outlined scores are 83.14 and 80, respectively12 Reference: 1: Mean, median, and mode review (article) | Khan Academy 2: Mean, Median, and Mode: Measures of Central Tendency - Statistics By Jim

Question 5

A movie production company wants to use analytics to decide which customers would choose to watch or not watch a particular movie after seeing a promotional teaser. The business analysis professional suggests they could make that prediction by identifying characteristics of the new movie and determining if the customer has watched other movies with similar characteristics. This is an example of using the following technique:

ALogistic regression

BOuster analysis

CInteger programming

DAnalysis of variance
Explanation:
Logistic regression is a technique that can be used to model the probability of a binary outcome, such as choosing to watch or not watch a movie, based on one or more predictor variables, such as the characteristics of the movie and the customer's viewing history. Logistic regression can help the business analysis professional to identify the factors that influence the customer's decision and to estimate the likelihood of each customer's preference. Logistic regression can also be used to test hypotheses and to evaluate the performance of the predictive model.
Reference: [Guide to Business Data Analytics], page 55; [Business Data Analytics: A Practical Guide], page 93; [Introduction to Business Data Analytics: A Practitioner View], page 14.

Answer : A

Question 6

An analyst is looking at a particular dataset that includes the scores across all 8th grade students, across three schools. The analyst is trying to determine which type of statistics average to use to best represent the results. On looking through the dataset, the analyst has identified a few extreme outliers. As a result, the analyst was led to use the following type of average:

AMedian

BRange

CMean

DMode

Answer : A

The median is the type of statistics average that the analyst should use to best represent the results, because it is a measure of central tendency that divides the data set into two equal halves. The median is the middle value of the data set when it is arranged in ascending or descending order. The median is not affected by extreme outliers, unlike the mean, which is the arithmetic average of the data set. The median can give a more accurate representation of the typical score of the 8th grade students across the three schools. Options B, C, and D are not types of statistics average, but types of statistics measures that describe other aspects of the data set. The range is a measure of dispersion that shows the difference between the highest and the lowest values of the data set. The mean is a measure of central tendency that shows the sum of the values of the data set divided by the number of values. The mode is a measure of central tendency that shows the most frequent value of the data set. Reference:

* Business Analysis Certification in Data Analytics, CBDA | IIBA, CBDA Competencies, Domain 3: Analyze Data

* Understanding the Guide to Business Data Analytics, page 17

* Business Data Analytics (IIBA-CBDA Exam preparation) | Udemy, Section 3: Analyze Data, Lecture 13: Descriptive Statistics

Question 7

A business analyst constructs a model they would like to review with key business stakeholders but decides to review the model first with the data scientist who has performed the data analysis. The data scientist provides some suggestions on how to reduce the complexity in the model. One suggestion is to use color to group objects needing to be associated. The data scientist is

encouraging using which Gestalt Principle of Perception with regards to data visualization?

AConnection

BProximity

CSimilarity

DEnclosure

Answer : C

The data scientist is encouraging using the Gestalt Principle of Similarity with regards to data visualization. This principle states that the brain groups objects together that are similar in appearance, such as color, shape, size, or orientation. By using color to group objects needing to be associated, the data scientist is suggesting a way to reduce the complexity in the model and make it easier for the viewers to perceive the patterns and relationships among the data12 Reference: 1: Gestalt Principles For Data Visualization - Topcoder 2: Introduction to Data Visualization: Gestalt Principles

IIBA Certification in Business Data Analytics CBDA IIBA - CBDA Exam Practice Test