Multiple Select Question Select all that apply Select three...

Labs

Want to see this concept in action?

NEW

Explore this concept interactively to see how it behaves as you change inputs.

View Labs

Recommended Videos

2-required-select-the-scale-of-categorical-or-numerical-data-type-appropriate-to-its-data-examples_-25-points-data-examples-data-type-sat-score-total-assets-gold-silver-bronze-audit-report-e-69541

Required: Select the scale of categorical or numerical data type appropriate to its data examples. Data Examples Data Type SAT score Total assets Gold, silver, bronze Audit report (e.g., unqualified, qualified, disclaimer, adverse) Depreciation method (declining balance, straight-line, etc.) Conference call transcript Inventory method (FIFO, LIFO, etc.) Blogs Sales Interval data Nominal Data Ordinal data Ratio data Unstructured Data

Supreeta N.

1-what-can-be-said-about-determining-causation-between-two-factors-from-a-business-standpoint-when-you-have-a-well-thought-out-datasetselect-an-answera-identifying-a-causal-factor-does-not-r-38892

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 sale 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 median 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 =MODE.MULT, highlight the cells, then click Shift + Ctrl + Enter at the same time. B. Use the formula =MODE.MULT, 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

Qbs E.

classify-each-variable-of-the-dataset-based-on-the-following-types-of-data-discussed-in-the-lectures-n-nominal-o-ordinal-q-interval-quantitative-interval-q-ratio-quantitative-ratio-it-is-pos-10378

Texts: Classify each variable of the dataset, based on the following types of data discussed in the lectures: N: Nominal O: Ordinal Q (Interval): Quantitative (Interval) Q (Ratio): Quantitative (Ratio) It is possible that one variable can be classified as different types of data. All are accepted, providing that the classification is well supported with more details or examples. Order ID Order Date Ship Date Ship Mode Customer ID Customer Name Segment Country City State Postal Code Region Product ID Category Sub-Category Product Name Sales Quantity Discount Profit

Sri K.

Transcript

00:01 Hello students, here data examples and data types are as follows.

00:19 Sat score, so it is interval level data.

00:34 Second one, total assets, it is ratio data, that is ratio level.

00:49 Third one, gold, silver, bronze, so that is ordinal data.

01:06 We can order that levels.

01:09 Fourth one, audit report, so it is a unstructured data...

Question

Multiple Select Question Select all that apply Select three examples of information in contrast to data. Order date Best customer Worst customer Best selling product Price

Please give Ace some feedback