# Data Analytics for Business Professionals (2018)

Question 1 of 2
Raj reviews performance scores for a department’s employees on a 1 to 10 scale, with 1 being the lowest. What would a mean of 7.8, a median of 4, and a mode of 6 suggest to Raj?

• The average score is skewed to a small number of high-performing employees. 🗸
• The score in the middle of the range seems correct for an even distribution of data points.
• The most occurring score suggests there are too many below-average employees.
• There are outliers, and the outliers reside at the low end of the scale.

Question 2 of 2
Which statement is correct about analytics?

• Qualitative data is information that can be measured in numerical form.
• The tools used to draw conclusions are the same for quantitative and qualitative data.
• Quantitative data is information that is typically descriptive.
• All analytics are based on data that has been derived from observations. 🗸

Question 1 of 3
Data analytics does not have to be complex and confusing. If you have a command of _, you can help your company identify patterns that can be explored further.

• central tendency
• predictive statistics
• summary statistics 🗸
• normal distributions

Question 2 of 3
You own a florist shop where your revenue depends on how many flowers each customer buys. If the average sale for roses is a dozen, and one standard deviation is three, what does this tell you?

• For two-thirds of your sales, customers will buy between nine and fifteen roses. 🗸
• Two-thirds of the roses you prepare for sale should be bunched in a dozen.
• For two-thirds of your sales, customers will buy either a half-dozen or a full-dozen roses.
• Two-thirds of the rose sales you make will be for three dozen roses.

Question 3 of 3
Which statement is most accurate about “one standard deviation” in a normal distribution?

• Roughly one-third of data points are beyond one standard deviation from the mean. 🗸
• Roughly one data point exists for every percentage away from the mean.
• Roughly one-third of all data points are contained in each standard deviation.
• Roughly two-thirds of data points are beyond one standard deviation from the mean.

Question 1 of 3
If you had to choose between having a high level of business acumen or being an expert statistician, which choice would provide more value to your company and why?

• Business acumen will allow you to know the answer before the data is even examined.
• Business acumen will let you formulate questions because they align with business strategy. 🗸
• Being an expert statistician will let you use data to answer any business question.
• Business acumen will let you properly frame questions as “what is the answer I am looking for?”

Question 2 of 3
To properly use data analytics tools, which two things must you always do?

• You must adapt the data to the questions you want to have answered.
• You must never have any type of question in mind when you analyze the data.
• You must understand the data, and you must focus on the questions you want to have answered. 🗸
• You must understand the data, and you must be flexible about the questions you want to have answered.

Question 3 of 3
What is most likely to cause a delay and adversely impact a company’s deadline in performing a data analysis of a particular business problem?

• More questions come up as data results come in.
• Too many departments are involved.
• You did not begin by forming a business question.

Question 1 of 3
ABC has recently changed its data platform. You notice that some data does not seem right. Which data fail is likely the reason?

• the “Fat Finger” problem
• missing data
• accounting conventions
• migration issues 🗸

Question 2 of 3
Lisa Roberts Wedding Planner is the largest customer at your florist shop. When you run your sales report for the year, you immediately know that not all the sales appear. What is the most likely reason?

• a migration issue
• the “Fat Finger” problem
• a customer aggregation issue 🗸
• an accounting conventions issue

Question 3 of 3
You have been asked to provide a recommendation for lowering product costs in the next year. Which issue can result in the data you need not being combined in your company’s current datasets?

• There is a lack of a structured data governance protocol. 🗸
• There is the issue of the backward compatibility of data.
• Your IT department has restricted data accessibility.
• There are too many costs involved in a product cost.

Question 1 of 2
The mean sales conversion rate for a FarmCo retail store is 50%. The median conversion rate is 40%. Which conclusion can you meaningfully draw from this data?

• This data tells you that half your stores are performing well below the median of all FarmCo stores.
• This data tells you the stores located in rural areas perform better than the stores in urban areas.
• This data alone tells you little if the stores are not all the same size and not all located in rural areas. 🗸
• This data alone tells you that your higher-performing stores can help the lower-performing stores.

Question 2 of 2
What do the descriptive statistics of mean, mode, and median do?

• They explain the contents of a dataset.
• They predict future occurrences.
• They reveal important information hidden in a dataset.
• They summarize the basic features of a dataset. 🗸

Question 1 of 3
You are interested in sales conversion rates. Which rule of thumb can best keep you from drawing incorrect conclusions about an already existing dataset you are presented?

• Ask how the data was collected.
• Ask when the data was collected.
• Ask who owns the data you are presented.
• Ask why the data was gathered in the first place. 🗸

Question 2 of 3

• The card will give you that data, provided every customer who enters the store is given a card.
• If everyone entering your store is given a card, the data will include many people who leave without buying. 🗸
• If everyone entering your store is given a card, it will capture how sales relate to where they heard about your store.
• The card will not give you the data you need, because you should have only given the card to a sample of people entering.

Question 3 of 3
You want to take a poll of your customers for their perceptions of customer service. How can you most accurately explain what is meant by a random sample in conducting your poll?

• Every customer has an equal chance of being included in your poll. 🗸
• You do not know how many customers will be polled.
• You do not know which of your customers will receive the polling questions.
• Every customer who is polled will be polled anonymously.

Question 1 of 2
If you are doing data analytics for an external stakeholder, what is the most damaging adverse effect of using cherry-picked data?

• You will undermine your credibility. 🗸
• You will not be able to derive results.
• You will be able to make conclusions.

Question 2 of 2
Your ice cream shop’s monthly sales show that sales have increased each year since you opened in 2013. If you remove data for July, you see your sales have actually remained steady. Was the data cherry-picked?

• The data was cherry-picked because it included data for the best-selling month.
• The data was not cherry-picked because you included all data for every month since you opened. 🗸
• The data was not cherry-picked because you can always work with a mean to determine annual sales.
• The data was cherry-picked because you removed a particular month’s data when you saw that sales were actually constant.

Question 1 of 4
Your online store’s sales are expanding while your in-store sales are declining. Which expensive error might you make if you use the online sales techniques in your retail store using this data alone?

• failing to consider random chance rather than the actual effect
• failing to consider extrapolation to your retail store properly 🗸
• failing to use a random sample in gathering your data
• failing to consider confounding variables in the data

Question 2 of 4
A before-and-after comparison of your online and in-store sales shows your online sales increased after an online promotion. What must you think about first before drawing conclusions about the promotion?

• Did your in-store sales also increase even though they were not part of the promotion? 🗸
• Did your online customers purchase more than they did during the last promotion?

Question 3 of 4
Which field of economics provides guidance to a company as to how a change of policy will affect a company’s bottom line?

• profit evaluation
• forecasting
• program evaluation 🗸
• macroeconomics

Question 4 of 4

• to increase the certain outcomes
• to predict outcomes in the short term
• to reduce the likelihood of certain outcomes 🗸
• to predict outcomes in the long term

Question 1 of 3
Profit margins for FarmCo’s top-end tractor line decreased in 2018 from 2017. What is the most likely cause-and-effect reason?

• Farming decreased from 2017 to 2018.
• Raw material costs decreased in 2018.
• Raw material costs increased in 2018. 🗸
• Customers went to a FarmCo competitor.

Question 2 of 3
Which of the following is an example of a negative correlation between Variable A and Variable B?

• The data shows an increase in Variable A and no change in Variable B.
• The data shows and increase in Variable A and an increase in Variable B.
• The data shows an increase in Variable A and a decrease in Variable B. 🗸
• The data shows a decrease in Variable A and a decrease in Variable B.

Question 3 of 3
Which of the following can you feel most comfortable classifying as a cause-and-effect relationship?

• Sales from your online retail store increase every time you run a holiday promotion.
• Fights outside your lunch stand at City Park have gone up every month that your ice cream sales go up.
• Litter on the street your candy store is located on increased when you started selling individually-wrapped candies. 🗸

Question 1 of 14
What can be said about determining causation between two factors from a business standpoint, when you have a well-thought-out dataset?

• Identifying a causal factor does not require additional resources and time.
• Although it might not always be accurate, you can use good business judgment to identify a causal factor. 🗸
• If you apply your business judgment, you will always be able to identify a causal factor.
• If you have a well-thought-out dataset, a causal factor will appear in the data.

Question 2 of 14
The new software analyzes sales conversion per sales in a way intended to increase sales success. What is the first thing you must do before evaluating the new software?

• Acknowledge it will measure “success.”
• Define what “sales conversion” is.
• Define how “success” is to be measured. 🗸
• Define what a “sale” is.

Question 3 of 14
What does cherry-picking mean in the context of data analytics?

• lack of randomness
• confirmation bias 🗸
• sampling error
• selection bias

Question 4 of 14
What is the most likely way for a sample selection to lead to inaccurate results?

• removing bias from the sample
• using a random sample of respondents
• sampling too many individuals
• introducing bias into the sample 🗸

Question 5 of 14
You have used the best data available and framed the best and most focused questions you could. What must you keep in mind about using averages?

• Variation is often hidden by averages, regardless of how good the dataset is. 🗸
• Averages will provide you with the most meaningful results.
• If you have a good dataset, you can draw conclusions from summary statistics.
• Improbable outliers will be removed when you have a good dataset.

Question 6 of 14
What can you do when there is a data fail?

• There is nothing you can do when there is a data fail. 🗸
• A data fail only means you need to run the data again.
• You can use advanced statistics to get better results.
• You can use advanced statistics to massage the data.

Question 7 of 14
Last year your company compiled employee satisfaction results using employee retention data. This year, they will use the scores from employee surveys. Which problem will you face when analyzing the data?

• a central tendency issue
• a data collection issue
• a backward compatibility issue 🗸
• a recency issue

Question 8 of 14
When you are framing the questions you will use data analytics to answer, what is the key to how you frame your questions?

• Keep your questions focused and actionable. 🗸
• Keep your questions focused, regardless of actionability.

Question 9 of 14
Your company can only afford to use an existing dataset. Can you still draw viable conclusions from the dataset?

• You will not be able to use an existing dataset; you can only derive viable conclusions from data you collect yourself.
• You can draw viable conclusions from an existing dataset, provided you frame actionable and detailed questions. 🗸
• You will not be able to leverage existing data in any meaningful way that can lead to viable conclusions.
• You can draw viable conclusions from an existing dataset, provided you phrase broad questions.

Question 10 of 14
What are the key areas at the intersection of finding answers and business questions?

• central tendency, summary statistics, and standard deviation
• past events, current predictions, and business acumen
• central tendency, past events, and future predictions
• past events, future predictions, and business acumen 🗸

Question 11 of 14
What does “standard deviation” tell you?

• the distance observations are from the media
• the distance observations are from the mean 🗸
• the distance observations are from each other
• the distance observations are from the mode

Question 12 of 14
If you are using Excel on a PC, how can you search through the values in column D and rows 1 to 27 to determine if there is more than one mean?

• Use the formula =MULT.MODE, highlight the cells, then click Shift + Ctrl + Enter at the same time.
• Use the formula =MULT.MODE, highlight the cells, then click Enter.
• Use the formula =MODE.MULT, highlight the cells, then click Enter.
• Use the formula =MODE.MULT, highlight the cells, then click Shift + Ctrl + Enter at the same time. 🗸

Question 13 of 14
_ are an example of qualitative data.

• Annual sales per year by state
• Ratings of customer satisfaction on a scale of 1 to 10
• Scores on an employee performance evaluation
• Interviews with store managers 🗸

Question 14 of 14
Which analytics type is the building block for all other types of business analytics?

• qualitative analytics
• descriptive analytics 🗸
• prescriptive analytics
• predictive analytics