Communicating Business Analytics Results Coursera Quiz Answers

All Weeks Communicating Business Analytics Results Coursera Quiz Answers

The analytical process does not end with models that can predict with accuracy or prescribe the best solution to business problems. Developing these models and gaining insights from data do not necessarily lead to successful implementations.

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Communicating Business Analytics Results Coursera Quiz Answers

Communicating Business Analytics Results Week 01 Quiz Answers

Q1. Which of the following statements correctly describes what happens in the last stage of an Information-Action Value Chain? Recall: there are 3 stages.

  • Analyze data set with statistical methods, clustering algorithms or advanced association to help make better decisions going forward
  • Summarize + interpret analytic results ⇒ model results with visual representations ⇒ develop action plan and alternatives ⇒ deliver the pitch
  • Apply prescriptive analytics to optimize business rules or financial models to figure out what choices should be made to achieve a specific outcome.
  • Identify an object or phenomena Access data on the object or phenomena Logically organize the data

Q2. Recall the concept of a data warehouse as an alternative to directly accessing data from a source system. Select all characteristics that pertain to the concept of a data warehouse:

  • Data is pulled from multiple data warehouses to create a source system
  • Data is organized in the data warehouse before it is used in an analysis
  • Data is organized in the source system BEFORE being pulled into a data warehouse
  • A data warehouse serves as a common location for data pulled from one or more source systems
  • You can selectively choose what type of data to extract from a data warehouse using a query language such as SQL

Q3. What properties are a desirable outcome of segmentation?

  • “homogeneity between” groups and “heterogeneity between” groups
  • “homogeneity within” groups and “heterogeneity between” groups
  • “homogeneity between” groups and “heterogeneity within” groups
  • “homogeneity within” groups and “heterogeneity within” groups

Q4. What does a customer lifetime value represent?

  • The sum of all revenues and costs of a customer over time
  • The difference of all revenues and costs of a customer over time
  • The frequency of contact a business has with a customer over their lifetime
  • The number of years an individual is considered a customer to a particular business

Q5. Answer the following questions based on this diagram.

Who in the diagram has highest network centrality?

  • Lara
  • Jen
  • Harry
  • Zack
  • Dan

Q6. Which two individuals have the highest clustering coefficient centrality?

  • Lara
  • Jen
  • Tom
  • Jinny

Communicating Business Analytics Results Week 02 Quiz Answers

Q1. For each of the scenarios in question 1 – 3 , choose the best means (text, table, or graph) to display the quantitative information.

Your company just broke a sales record. You would like to show the new sales record on a big screen at the company entrance.

  • Text
  • Table
  • Graph

Q2. In an internal meeting, you would like to show the monthly sales amount of a few key products in the last ten years.

  • Text
  • Table
  • Graph

Q3. In a meeting with a sales team, you would like to show the quarterly units sold, sales amount, and market share for several products in the last year.

  • Text
  • Table
  • Graph

Q4. Which of the following are benefits of a table ? Select all that apply :

  • Can display very complex relationship
  • Can display precise values
  • Speeds up look up of individual values
  • Relates different units of measurements
  • Can present patterns of the data
  • Can clearly model billions of data values

Q5. Select all methods that can be used to represent single numerical values:

  • Points
  • Lines
  • Bars
  • Boxes
  • Shapes
  • Color Intensity

Q6. Which of the following graphs CANNOT be used to show the distribution of data? Select all that apply :

  • Strip plot
  • Line plot
  • Histogram
  • Density curve
  • Box plot
  • Scatter plot

Q7. Which of the following decreases the data-ink ratio? Select all that apply :

  • A large amount of points in a scatter plot
  • Large range intervals in histograms
  • 3D effects
  • Background images

Q8. The following table shows worldwide iPhone market share in the smartphone market from 2011 to 2015. Choose the best graph to show this data.

Answers

Q9. Visualization experts recommend against using points without trend lines to show time series data. Which of the following statement is the best explanation for this recommendation?

  • Points are generally not a good way to encode numerical values.
  • Points cannot show precise values of numerical data.
  • Points have small visual weight and do not help show the sequential nature of the data
  • None of the above

Q10. Consider the following monthly sales data. Choose the best graphical design for this data.

Answer

Q11. Which of the following statements regarding small multiple design are correct? Select all that apply :

  • In general, the same chart type should be used in a small multiple design.
  • In general, small multiple design is preferred whenever it is feasible.
  • In general, the same axis scale and color scheme should be used in a small multiple design.
  • In a small multiple design, the graphs should be arranged following some natural order whenever possible.

Q12. Which of the following statements best explains why stacked area charts should be avoided?

  • Stacked area charts are not aesthetically pleasing.
  • Stacked area charts are difficult to construct with commonly available software tools.
  • Stacked area charts may mask the trend of data series except for the one in the bottom.
  • Stacked area charts cannot represent numerical values accurately.

Communicating Business Analytics Results Week 03 Quiz Answers

Q1. In addition to analyzing data well, a data analyst may also need to

  • Pitch their ideas to one or more decision makers
  • Ensure isolation between the data and the customer
  • Organize and processes data as efficiently as possible
  • Take account of bad or questionable data

Q2. Who or what is the best option to appeal your ideas to?

  • The process
  • The period
  • The people
  • The place

Q3. Telling compelling stories about the data analytic results requires (Select all that apply)

  • The story to be simple
  • The story to be short
  • The story to be true
  • The story to be informative

Q4. What is the relevance of knowing your audience for selling your story?

  • To present results in a way that resonates with the audience
  • To present data that is familiar to the audience
  • To give input to audience opinion
  • To help present abstract concepts in a easy matter.

Q5. What is an important principle to remember when preparing or giving a presentation?

  • Slides are the only effective way of presenting ideas
  • The presentation is about the problem you’re trying to solve – not about you
  • Slides should contain as much information as possible
  • Occasionally use specific materials to keep the presentation concise.

Q6. What is the pyramid principle?

  • Ideas can be broken into steps and then recombined together.
  • Always start from underdeveloped ideas and work towards a marketable one.
  • Writing and thinking can be structured to nest supporting ideas under one common point.
  • Give ideas a sufficient proof-of-concept using deductive analysis

Q7. In preparing presentation materials, the materials should be

  • Well-rounded slides and graphs.
  • At least 3-5 items
  • Colorful for visual aid
  • Correct and good quality

Q8. Although delivering the pitch requires conciseness and clarity, it must

  • Accommodate all possible audiences.
  • Be delivered to the audience as quickly as possible
  • Fit into the time allotted
  • Be delivered via power point slides.

Q9. Numerical patterns and trends are best understood when

  • Presented in some context
  • Plotted as concisely as possible
  • Compared and contrasted against current ideas
  • Organized and analyzed very thoroughly

Q10. A good rule of thumb when presenting with slides is

  • To use note cards sparingly
  • To allot about 5 minutes per slide
  • Construct a familiar scenario to the audience
  • To present complex ideas first

Q11. True or False: We identify correlation by specifically looking for a linear relationship when two data sets are plotted against each other?

  • True
  • False

Q12. Consider the following two sets of measures:

∎ Temperature in degrees celsius for each day in November, 2011 in Boulder, Colorado

∎ Hot chocolate sales in dollars for each day in November, 2011 in Boulder, Colorado

Say you calculate the Pearson correlation coefficient for the two sets of measures. If your r-value is equal to 0, what can you say about the relationship between sales of hot chocolate versus temperature based off of these two data sets? Select all that apply:

  • The data sets are not correlated at all
  • The data sets are perfectly negatively correlated
  • The data sets are perfectly positively correlated
  • There is no linear relationship between temperature and sales of hot chocolate

Q13. Which of the following statements about causality and correlation are true? Select all that apply:

  • Causality is always implied if two data sets are found to be correlated
  • If correlation is present between two data sets, causality is just one possible explanation for the identified relationship
  • There can never be both correlation AND causality present between two data sets, they are mutually exclusive concepts
  • Two sets of measurements can have a causal relationship AND also have no correlation present

Q14. Pretend a study is performed on the following two sets of data:

∎ Number of engineering degrees awarded in 2012

∎ Number of kittens adopted in 2012

A very high degree of correlation is found between the two almost unrelated data sets. What is the most likely explanation for this high degree of correlation?

  • The event of receiving an engineering degree is the cause of the second event, the purchasing of a kitten
  • No real relationship exists between the two data sets, it is coincidence
  • There is no arguing with the data, the two types of events are related in the real world
  • A third factor is likely causing the trends in both data sets

Q15. Define cognitive biases:

  • A concentration on or interest in one particular area or subject
  • A mode of altering information to deviate from reality
  • The mental action of acquiring knowledge and understanding through thought, experience, and the senses
  • Using thought or rational judgment

Q16. It is a data analyst’s responsibility to :

  • Take into consideration external pressure to show favorable results
  • Remain objective
  • Support the agenda of the sponsor of a study
  • Draw different conclusions from information based on how it’s presented

Q17. The lie of average distorts data by:

  • Using summary statistics to find correlated data sets
  • Using summary statistics to conceal data distribution
  • Using the average of a data set to hide variance
  • Using correlation to prove causation

Q18. What is the basic idea behind chart myopia?

  • Showing data in a way that puts it into perspective and shows it in the right context
  • Using only summary statistics can misrepresent the underlying nuances of our data
  • Leaving out the ‘out of how many’ value when counting the frequency of a specific event
  • Zooming in or out on data visualization results to make insignificant things look significant or vice versa

Q19. Select all characteristics of a properly conducted controlled market experiment:

  • Apply a predetermined treatment to the control group
  • Only control group members are selected randomly
  • Both control group and treatment group participants are selected at random
  • Differences in behaviour between group should be attributable to the treatment
  • Differences between groups are measurable and quantifiable

Communicating Business Analytics Results Week 04 Quiz Answers

Q1. What are advantages of the “Baseball Card” approach to showing options in slides (select all that apply)?

  • Allows different types of information about an option to be displayed in one place
  • Focuses attention on the speaker by only showing the most relevant bullet points
  • Facilitates comparisons of options to each other
  • Is optimal when the analysis involves mostly math and figures

Q2. Why might we consider using a segmentation schema provided by a third party instead of building our own (select the best answer)?

  • Third party schemas are usually better because they incorporate information we don’t have
  • They can help us to target customers in the market for which we may not have information
  • They are the experts and are better at segmentation analytics
  • It’s a better option when we planning efforts to retain our current customers

Q3. Which of the following describes a fully factorialized experiment?

  • An experiment designed to provide maximum insight with the fewest number of test groups
  • An experiment that has a separate control group for each test group
  • An experiment that uses a before and after comparison for each test group
  • An experiment where all combinations of all factors are tested

Q4. In the Customer Acquisition Strategy case study, why did we evaluate so many options (select all that apply)?

  • Different constituencies had different opinions on what the strategy should be
  • There were significant tradeoffs among different approaches
  • Because it’s always better to have as many options as possible
  • The preferred number of strategic options is the magic number seven plus or minus two

Q5. Consider the following slide from our Customer Acquisition Strategy case study:

What kind of ideograms are used in this slide?

  • Harvey Balls
  • Pie Charts
  • Death Stars
  • Pac Man Circles

Q6. This question refers to the graph in the previous question. Which options show the best performance for Avg. Revenue and Desirability combined (check all that apply)?

  • Max. Customers
  • Avg. Revenue
  • Revenue
  • Profitability
  • Growth Segment
  • Balanced

Q7. To make use of a Customer Lifetime Value
calculation, it’s necessary to have all revenues and costs for each customer
readily available.

  • True
  • False

Q8. Why do you think that
the internal and external analyses in the Customer Acquisition Strategy case study
were done in parallel?

  • They relied largely on different data and used different techniques, so they could be done independently
  • Doing the analyses in parallel allowed the project to be completed more rapidly
  • It allowed the team to avoid biases that could be introduced by doing the internal
    or external analysis first
  • All of these are reasonable reasons to do the analyses in parallel
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