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Answer the following about data analytics:

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

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

2. 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?

Select an answer:
A. Acknowledge it will measure "success."
B. Define what "sales conversion" is.
C. Define how "success" is to be measured.
D. Define what a "sale" is.

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

Select an answer:
A. lack of randomness
B. confirmation bias
C. sampling error
D. selection bias

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

Select an answer:
A. removing bias from the sample
B. using a random sample of respondents
C. sampling too many individuals
D. introducing bias into the sample

5. 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?

Select an answer:
A. Variation is often hidden by averages, regardless of how good the dataset is.
B. Averages will provide you with the most meaningful results.
C. If you have a good dataset, you can draw conclusions from summary statistics.
D. Improbable outliers will be removed when you have a good dataset.

6. What can you do when there is a data fail?

Select an answer:
A. There is nothing you can do when there is a data fail.
B. A data fail only means you need to run the data again.
C. You can use advanced statistics to get better results.
D. You can use advanced statistics to massage the data.

7. 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?

Select an answer:
A. a central tendency
B. issue a data collection
C. issue a backward compatibility
D. issue a recency issue

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

Select an answer:
A. Keep your questions focused and actionable.
B. Keep your questions actionable.
C. Keep your questions vague so more questions can be answered.
D. Keep your questions focused, regardless of actionability.

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

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

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

Select an answer:
A. central tendency, summary statistics, and standard deviation
B. past events, current predictions, and business acumen
C. central tendency, past events, and future predictions
D. past events, future predictions, and business acumen

11. What does "standard deviation" tell you?

Select an answer:
A. the distance observations are from the media
B. the distance observations are from the mean
C. the distance observations are from each other
D. the distance observations are from the mode

12. 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?

Select an answer:
A. Use the formula =MULT.MODE, highlight the cells, then click Shift + Ctrl + Enter at the same time.
B. Use the formula =MULT.MODE, highlight the cells, then click Enter.
C. Use the formula =MODE.MULT, highlight the cells, then click Enter.
D. Use the formula =MODE.MULT, highlight the cells, then click Shift + Ctrl + Enter at the same time.

13. _____ are an example of qualitative data.

Select an answer:
A. Annual sales per year by state
B. Ratings of customer satisfaction on a scale of 1 to 10
C. Scores on an employee performance evaluation
D. Interviews with store managers

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

Select an answer:
A. qualitative analytics
B. descriptive analytics
C. prescriptive analytics
D. predictive analytics

Answer :

1. When you have a well-thought-out dataset Option B. Although it might not always be accurate, you can use good business judgment to identify a causal factor.

2. The first thing you must do before evaluating the new software is option C. Define how "success" is to be measured.

3. Cherry-picking mean in the context of data analytics is option D. Selection bias.

4. The most likely way for a sample selection to lead to inaccurate results is option D. Introducing bias into the sample.

5. Keep in mind about using averages is option A. Variation is often hidden by averages, regardless of how good the dataset is.

6. When there is a data fail is option D. You can use advanced statistics to massage the data.

7. When analyzing the data is option D. Issue a regency issue.

8. The key to how you frame your questions is option A. Keep your questions focused and actionable.

9. Draw viable conclusions from the dataset by is option B. You can draw viable conclusions from an existing dataset, provided you frame actionable and detailed questions.

10. The key areas at the intersection of finding answers and business questions option B. Past events, current predictions, and business acumen.

11. "standard deviation" tell you is option B. The distance observations are from the mean.

12. Option D. Use the formula =MODE.MULT, highlight the cells, then click Shift + Ctrl + Enter at the same time.

13. Option D. Interviews with store managers are an example of qualitative data.

14. Analytics type is the building block for all other types of business analytics is option B. Descriptive analytics.

1. When dealing with a well-thought-out dataset, suggests that despite potential inaccuracies, one can rely on good business judgment to identify a causal factor.

2. Before evaluating new software, emphasizes the importance of defining how "success" will be measured. Establishing clear metrics and criteria helps determine the effectiveness and value of the software

3. Selection bias Cherry-picking in the context of data analytics refers to the act of selectively choosing or emphasizing specific data points, samples.

4.The most likely way for sample selection to result in inaccurate results which involves introducing bias into the sample. Bias in sample selection can skew the representation of the population, leading to results that do not accurately reflect the true characteristics

5. Emphasizes that regardless of dataset quality, averages often conceal variation. By focusing solely on the average, important fluctuations and patterns within the data can go unnoticed, leading to an incomplete understanding of the underlying trends and characteristics.

6. Suggests that when there is a data fail, one can use advanced statistics to manipulate or "massage" the data. However, it is important to note that manipulating data to fit desired outcomes can compromise the integrity .

7. Refers to issuing a "regency issue" when analyzing data. However, without further context or clarification, it is not clear what a regency issue entails in the context of data analysis.

8.Emphasizes that the key to framing effective questions lies in keeping them focused and actionable. By ensuring that questions are clear, specific, and capable of generating practical insights, one can enhance the quality and usefulness of the resulting information.

9. Suggests that viable conclusions can be drawn from an existing dataset by framing actionable and detailed questions. By formulating specific inquiries that align with the dataset's context, one can extract meaningful insights.

10. Highlights three key areas at the intersection of finding answers and business questions: past events, current predictions, and business acumen. This involves leveraging historical data, making informed predictions based on current information, and applying business knowledge and expertise to drive decision-making.

11. States that "standard deviation" tells you the distance observations are from the mean. Standard deviation is a statistical measure that quantifies the dispersion or spread of data points in relation to the mean.12. Use the formula =MODE.MULT, highlight the cells, then click Shift + Ctrl + Enter at the same time. To search through values in column D and rows 1 to 27 to determine if there is more than one mean in Excel on a PC, you can use the formula =MODE.MULT.

13.Interviews with store managers. Interviews with store managers are an example of qualitative data. Qualitative data is non-numerical and typically consists of descriptions, opinions, or subjective information

14. Descriptive analytics. Descriptive analytics is the building boll other types of business analytics. It involves summarizing and interpreting historical data to gain insights and understand patterns, trends, and relationships within the data.

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