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IIBA CBDA Exam (page: 3)
IIBA Certification in Business Data Analytics
Updated on: 25-Dec-2025

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CBDA PDF 150 Questions

The marketing department for a major restaurant chain is interested in testing a Kids Eat Free campaign to determine if it will help to increase sales. They are interested in piloting the campaign to determine which day of the week will improve sales the most. The campaign is launched across 7 cities with each city promoting a different day of the week. The sales data is collected and provided to a team for analysis.
What concern might the analytics team have regarding data quality across cities?

  1. Normality
  2. Heteroskedacity
  3. Linearity
  4. Variation

Answer(s): D

Explanation:

Variation is the degree to which the data values differ from each other or from a central tendency measure, such as the mean or median. Variation can affect the data quality across cities, as it can indicate the presence of outliers, errors, noise, or inconsistency in the data collection or processing methods. Variation can also influence the statistical analysis and interpretation of the results, as it can affect the significance, confidence, and validity of the findings12.


Reference:

1: Guide to Business

Data Analytics, IIBA, 2020, p. 302: Statistics for Business and Economics, David R. Anderson et al., 2014, p. 83.



A call center has requested to review their sales conversion data for the month. The analyst working on this request is trying to identify the chart that will effectively present the data, which includes: the number of leads, the number of calls made, the number of calls completed, the number of customers interested and the number of sales.
What chart should the analyst use to show the values across each stage of the pipeline?

  1. Pie chart
  2. Funnel chart
  3. Bar chart
  4. Bullet chart

Answer(s): B

Explanation:

A funnel chart is a type of chart that shows the values of different stages of a process, such as a sales pipeline, where each stage represents a subset of the previous one. A funnel chart is useful for showing the conversion rate, the drop-off rate, and the potential revenue or profit at each stage12. A funnel chart would be an effective way to present the data requested by the call center, as it would show the number of leads, calls, customers, and sales, as well as the percentage of change between each stage.


Reference:

1: Guide to Business Data Analytics, IIBA, 2020, p. 662: Data Visualization: A Practical Introduction, Kieran Healy, 2018, p. 233.



A government agency is conducting a study on the performance of 12th grade students' in mathematics across the country. In particular, they want to understand if there is a relationship between intelligence and scores, as well as the difference in performance between various locations.
Which combination of inferential statistics procedures should be used?

  1. Range, standard deviation
  2. Mean, median
  3. Correlation co-efficient, analysis of variance
  4. Frequency distribution, time-series

Answer(s): C

Explanation:

A correlation co-efficient is a measure of the strength and direction of the linear relationship between two variables, such as intelligence and scores. A correlation co-efficient can range from -1 to 1, where -1 indicates a perfect negative relationship, 0 indicates no relationship, and 1 indicates a perfect positive relationship12. An analysis of variance (ANOVA) is a procedure that tests whether the means of two or more groups are significantly different from each other, such as the performance of students across various locations. ANOVA can compare the variation within each group and the variation between groups to determine if there is a statistically significant difference among the group means34.


Reference:

1: Guide to Business Data Analytics, IIBA, 2020, p. 582:

Statistics for Business and Economics, David R. Anderson et al., 2014, p. 7133: Guide to Business Data Analytics, IIBA, 2020, p. 594: Statistics for Business and Economics, David R. Anderson et al., 2014, p.
849.



An organization's customers are categorized based on the amount of purchases completed over the last 12 months. The analytics team would like to ensure the accuracy of their survey results and decide to randomly select 500 customers to participate in a survey from this large pool of customers.
This is an example of:

  1. Stratified sampling
  2. Quota sampling
  3. Purposive sampling
  4. Snowball sampling

Answer(s): A

Explanation:

Stratified sampling is a technique that divides the population into homogeneous subgroups (strata) based on a relevant characteristic, such as the amount of purchases, and then randomly selects a proportional number of elements from each subgroup to form the sample. Stratified sampling ensures that the sample is representative of the population and reduces the sampling error and bias12.


Reference:

1: Guide to Business Data Analytics, IIBA, 2020, p. 312: Statistics for Business and Economics, David R. Anderson et al., 2014, p. 262.



The results of the data analytics work led to some clear and strongly supported outcomes and the analytics team is very confident in their recommendations; particularly given that the payback on the required changes are a short 3 months. However, there is concern because the organization operates in a highly regulated environment and some new regulatory changes are being considered with announcements and implementation in the next 6 months. Under these conditions the team decides to:

  1. Recommend no action be taken at this time and revisit in 6 months
  2. Reassess their results to ensure their validity and then decide what to do
  3. Identify and carefully document assumptions for their recommendation
  4. Postpone recommendations for 6 months until the announcements are made

Answer(s): C

Explanation:

The best option for the team under these conditions is to identify and carefully document the assumptions for their recommendation, such as the expected impact of the regulatory changes, the risks and benefits of implementing the changes before or after the announcements, and the sensitivity of the results to different scenarios. This way, the team can communicate their findings and recommendations clearly and transparently, while also acknowledging the uncertainty and limitations of their analysis. This can help the decision makers to evaluate the trade-offs and make informed choices12.


Reference:

1: Guide to Business Data Analytics, IIBA, 2020, p. 242: Data-Driven Decision Making: A Primer for Beginners, Anand Rao, 2018, 1.



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SPriyak 3/17/2025 11:08:37 AM

can you please provide the CBDA latest test preparation
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