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BU6015 - Business Analytics

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Which common visualization type would be used to evaluate the composition of values?

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Based on these time series analysis results from Lab 5.3 Excel, Forecasting Product Demand using Time Series Analysis, what is the maximum amount of product demand that can be expected in 2026-12-01?

The columns headers are: month, monthly product demand, forecast (monthly product demand), lower confidence bound (monthly product demand), and upper confidence bound (monthly product demand). The entry for 2026-12-01 are as follow: monthly product demand, blank; forecast (monthly product demand), 308.99; lower confidence bound (monthly product demand), 292.45; upper confidence bound (monthly product demand), 325.53.

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Diagnostic Analytics emphasizes “What happened?”.

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Data with an equal and definitive interval between each data point and absolute “zero” in the point of origin measuring transactions amounts for revenues and expenses would be considered which type of data?
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Suppose a company has access to high quality data (not biased), but the data is five years old. Which quality of information might it be lacking?

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As compared to raw data, aggregated data gives the analyst the greatest ability to select the most relevant data.

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Assume that a company, UGrowIt, helps people who are new to growing vegetables or have not been successful at growing vegetables in the past. UGrowIt travels to people’s gardens and provides gardening advice on how to get started, eliminate pests and insects, or troubleshoot other gardening problems. The company sent a survey to each of its 10,000 customers to see how satisfied customers are with the company. 2,500 customers responded to the survey. Using the collected data, UGrowIT determined that the average satisfaction is 9.2 out of a possible 10.0 (the highest) for respondents. What is 9.2?

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A company’s descriptive statistics are appropriately compared to either 1) the economy as a whole, 2) the company’s respective industry, 3) competitors and 4) the company’s prior performance.

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What is the term for data about the data?

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Based on these regression results from Lab 5.6 Excel: Forecasting Product Demand Using Regression, which independent variables are significantly related to forecast demand?

Under regression statistics, the following values are shown: Multiple R, 0.891401552. R square, 0.794596727. Adjusted R square, 0.780591959. Standard error, 4.286745807. Observations, 48. In the ANOVA table at the center, values are shown as follows: Regression: d f, 3. S S, 3127.861777. M S, 1042.621. F, 56.73758. Significance F, 3.6376E minus 15. Residual: d f, 44. S S, 808.5523431. M S, 18.37619. Total: d f, 47. S S, 3936.41412. In the table at the bottom, the entries are shown as follows: Intercept: Coefficients, negative 123.7576339. Standard error, 22.11431598. t Stat, negative 5.59627. P value, 1.32E minus 06. Lower 95 percent, negative 168.3261093. G D P: Coefficients, 2.162221318. Standard error, 0.212246208. t Stat, 10.18733. P value, 3.76E minus 13. Lower 95 percent, 1.734467193. Weather (average Fahrenheit): Coefficients, 0.202019743. Standard error. 0.043196935. t Stat, 4.676715. P value, 2.78E minus 05. Lower 95 percent, 0.114962041. Holiday: Coefficients, 7.513785459. Standard error. 1.745077976. t Stat, 4.305702. P value, 9.17E minus 05. Lower 95 percent, 3.99681189.

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