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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?

A.
Pie chart
A.
Pie chart
Answers
B.
Funnel chart
B.
Funnel chart
Answers
C.
Bar chart
C.
Bar chart
Answers
D.
Bullet chart
D.
Bullet chart
Answers
Suggested answer: 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?

A.
Range, standard deviation
A.
Range, standard deviation
Answers
B.
Mean, median
B.
Mean, median
Answers
C.
Correlation co-efficient, analysis of variance
C.
Correlation co-efficient, analysis of variance
Answers
D.
Frequency distribution, time-series
D.
Frequency distribution, time-series
Answers
Suggested answer: 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:

A.
Stratified sampling
A.
Stratified sampling
Answers
B.
Quota sampling
B.
Quota sampling
Answers
C.
Purposive sampling
C.
Purposive sampling
Answers
D.
Snowball sampling
D.
Snowball sampling
Answers
Suggested answer: 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:

A.
Recommend no action be taken at this time and revisit in 6 months
A.
Recommend no action be taken at this time and revisit in 6 months
Answers
B.
Reassess their results to ensure their validity and then decide what to do
B.
Reassess their results to ensure their validity and then decide what to do
Answers
C.
Identify and carefully document assumptions for their recommendation
C.
Identify and carefully document assumptions for their recommendation
Answers
D.
Postpone recommendations for 6 months until the announcements are made
D.
Postpone recommendations for 6 months until the announcements are made
Answers
Suggested answer: 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.

A colleague proposes measuring job satisfaction by asking the question 'What is your salary?'. What is the concerning factor about this question?

A.
Validity
A.
Validity
Answers
B.
Clarity
B.
Clarity
Answers
C.
Reproducibility
C.
Reproducibility
Answers
D.
Subjectivity
D.
Subjectivity
Answers
Suggested answer: A

Explanation:

Validity is the extent to which a measure or a question accurately captures the intended concept or construct1. The question ''What is your salary?'' is not a valid measure of job satisfaction, as it does not reflect the various aspects of job satisfaction, such as work environment, recognition, autonomy, growth, etc. Salary is only one possible factor that may influence job satisfaction, but it is not a direct or comprehensive indicator of it23. Therefore, the question is not valid for measuring job satisfaction.

Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 302: Job Satisfaction: Application, Assessment, Causes, and Consequences, Paul E. Spector, 1997, p. 23: Job Satisfaction Survey, 1.

A marketing director has asked the question 'How many product purchases are expected this coming year given the current marketing campaign?'. What type of analytics would be performed to answer this question?

A.
Descriptive
A.
Descriptive
Answers
B.
Predictive
B.
Predictive
Answers
C.
Diagnostic
C.
Diagnostic
Answers
D.
Prescriptive
D.
Prescriptive
Answers
Suggested answer: B

Explanation:

Predictive analytics is a type of analytics that uses historical and current data, as well as statistical and machine learning techniques, to forecast future events or outcomes, such as product purchases, customer behavior, or market trends12. To answer the question 'How many product purchases are expected this coming year given the current marketing campaign?', predictive analytics would be performed to estimate the demand and sales based on the existing data and the marketing campaign variables.

Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 182: Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, Eric Siegel, 2016, p. 3.

An insurance company has seen an upward trend in winter-related accidents over the past three years. The company has just completed an analytics study to better understand the primary reasons for these accidents and assess how many of the drivers were using winter tires. This analysis will help the company decide how to move forward with drivers not taking precautionary measures during winter. What type of analysis will help in determining the primary reasons and percentage of those drivers with winter tires?

A.
Prescriptive
A.
Prescriptive
Answers
B.
Descriptive and Predictive
B.
Descriptive and Predictive
Answers
C.
Descriptive
C.
Descriptive
Answers
D.
Descriptive and Diagnostic
D.
Descriptive and Diagnostic
Answers
Suggested answer: D

Explanation:

Descriptive analytics is a type of analytics that summarizes and visualizes the data to provide an overview of what has happened or is happening, such as the trend of winter-related accidents over the past three years, or the percentage of drivers using winter tires12. Diagnostic analytics is a type of analytics that explores and analyzes the data to understand why something has happened or is happening, such as the primary reasons for these accidents, or the factors that influence the drivers' decisions13. To answer the question, both descriptive and diagnostic analytics would be needed to provide the relevant information and insights for the company.

Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 182: Business Analytics: Data Analysis & Decision Making, S. Christian Albright and Wayne L. Winston, 2015, p. 53: Data Science for Business, Foster Provost and Tom Fawcett, 2013, p. 13.

A Human Resource manager recently learned that their competitor reduced employee attrition rates by 20% after implementing personality tests as part of their screening process. Intrigued by the idea, the manager suggests collecting data on personality tests and attrition rates over the next year. The data from this year is then analyzed to explore possible relationships. What type of analytics has the team been asked to perform?

A.
Predictive
A.
Predictive
Answers
B.
Descriptive
B.
Descriptive
Answers
C.
Prescriptive
C.
Prescriptive
Answers
D.
Diagnostic
D.
Diagnostic
Answers
Suggested answer: B

Explanation:

Descriptive analytics is a type of analytics that summarizes and visualizes the data to provide an overview of what has happened or is happening, such as the attrition rates and the personality test scores of the employees12. The team has been asked to perform descriptive analytics to explore possible relationships between the data variables, without making any predictions or prescriptions for the future.

Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 182: Business Analytics: Data Analysis & Decision Making, S. Christian Albright and Wayne L. Winston, 2015, p. 5.

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?

A.
T - The increase should be seen sooner
A.
T - The increase should be seen sooner
Answers
B.
A - It is too easy of a target to attain
B.
A - It is too easy of a target to attain
Answers
C.
R - Since competition is high, focus should be on increasing customer base and not on ARPU
C.
R - Since competition is high, focus should be on increasing customer base and not on ARPU
Answers
D.
S - There is no mention of which product group/line the target pertains to
D.
S - There is no mention of which product group/line the target pertains to
Answers
Suggested answer: D

Explanation:

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.

An analytics team has completed some initial data analysis but is considering revising their research question based on their analysis findings. The team was concerned the original question was too broad. What outcome would lead the team to have this concern?

A.
Data once analyzed had significant data quality issues
A.
Data once analyzed had significant data quality issues
Answers
B.
Data the team had planned to use was not available
B.
Data the team had planned to use was not available
Answers
C.
Difficult to identify the KPIs to measure
C.
Difficult to identify the KPIs to measure
Answers
D.
The source data sets could not be merged
D.
The source data sets could not be merged
Answers
Suggested answer: C

Explanation:

A research question is a clear and focused question that guides the data analytics process and defines the expected outcome or value of the analysis1. A research question that is too broad may lead to the concern of being difficult to identify the key performance indicators (KPIs) to measure, as KPIs are specific, quantifiable, and relevant metrics that indicate the progress and success of the analysis in relation to the research question23. A broad research question may also result in too much or too little data, unclear or conflicting objectives, or irrelevant or ambiguous results4.

Reference: 1: Guide to Business Data Analytics, IIBA, 2020, p. 202: Guide to Business Data Analytics, IIBA, 2020, p. 233: Key Performance Indicators: Developing, Implementing, and Using Winning KPIs, David Parmenter, 2015, p. 34: How to Write a Good Research Question, ThoughtCo, 2021, 1.

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