Construct PivotTables showing the counts of gender versus carrier and type versus usage in the Excel file Cell Phone Survey. What might you conclude from this analysis? Note: You need to create two pivot tables: The first one gender and carrier. The second one type and usage. In both of them use signal strength in the sigma values box.

Construct PivotTables showing the counts of gender versus carrier and type versus usage in the Excel file Cell Phone Survey. What might you conclude from this analysis? Note: You need to create two pivot tables: The first one gender and carrier. The second one type and usage. In both of them use signal strength in the sigma values box.

Essentials of Business Analytics (MindTap Course List)

2nd Edition

ISBN:9781305627734

Author:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Publisher:Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann, David R. Anderson

Chapter3: Data Visualization

Section: Chapter Questions

Problem 16P: Consider the following survey results regarding smartphone ownership by age: a. Construct a...

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Consider the following survey results regarding smartphone ownership by age: a. Construct a stacked-column chart to display the survey data on type of cell-phone ownership. Use Age Category as the variable on the horizontal axis. b. Construct a clustered column chart to display the survey data. Use Age Category as the variable on the horizontal axis. c. What can you infer about the relationship between age and smartphone ownership from the column charts in parts a and b? Which column chart (stacked or clustered) is best for interpreting this relationship? Why?
What is answer for question b)
Consider an organization of your choosing that might be creating a survey for a product or service. Write two example questions that you would use to interpret descriptive statistics and two example questions that you would use to interpret inferential statistics.
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The Human Resources Manager for Optilytics LLC is evaluating applications for the position of Senior Data Scientist. The file OptilyticsLLC presents summary data of the applicants for the position. a. Use a PivotTable in Excel to create a joint probability table showing the probabilities associated with a randomly selected applicants sex and highest degree achieved. Use this joint probability table to answer the questions below. b. What are the marginal probabilities? What do they tell you about the probabilities associated with the sex of applicants and highest degree completed by applicants? c. If the applicant is female, what is the probability that the highest degree completed by the applicant is a PhD? d. If the highest degree completed by the applicant is a bachelors degree, what is the probability that the applicant is male? e. What is the probability that a randomly selected applicant will be a male whose highest completed degree is a PhD?
Consider the accompanying set of dependent and independent variables. The variable x3 is qualitative with M = Male and F = Female. Complete parts a and b below. Click the icon to view the set of variables. a. Using technology, construct a regression model using all three independent variables. (Let variable Gender be the dummy variable for x3. Assign a 1 to a male.) Complete the regression equation for the model below, where x3 represents the dummy variable Gender. + (Round to three decimal places as needed.) Variables y x1 X2 17 X3 M 651M 9116 9 16 15 17 20 5 5 9 7 11 13 11 F 127M 272F TIM D 34 24 28 15 21 7 4 M F Print Done - X
GIVEN THE FOLLOWING DATA, COMPUTE FOR THE FOLLOWING: 1. STRAIGHT LINE METHOD 2. ARITHMETIC GEOMETRIC CURVE 3. STATISTICAL PARABOLIC CURVE WRITE A RECOMMENDATION REGARDING THE RESULTS AND WHICH OF THE NETHOD IS BEST FIT FOR THE DATA. Nate: answer on a separate document. Use excel in compute. 2. Supposed this is Yc (straightline) 450,000 370,000 750,000 1,100,000 1,500,000 1,000,000 1,700,000 2,000,000 1,900,000 2,300,000 Yi + 1 (Geometric) YEAR SALES 415,000 1 356,000 703,556 1,023,400 1,308,905 900,573 1,504,789 1,705,932 1,895,890 2,094,256 450,000 370,000 750,000 1,100,000 1,500,000 1,000,000 1,700,000 2,000,000 1,900,000 2,300,000 2011 2012 2013 3 2014 4. 2015 2016 6. 2017 2018 8 2019 2020 10
You must use Excel to perform the regression analysis. Provide the answers under the space provided for each question. You must provide the Excel output for the question along with the answers. Round off the values on the output to three-five decimal places if appropriate.Conduct a simple linear regression analysis for each independent variable associated with the external factors, using house price as the dependent variable. Make sure to use the indicator variables for the categorical data. (Significance level of α = 0.05). For each regression:22) Report the p-value of the independent variable and indicate whether it is a significant predictor of house price (based on the p-value being less than 0.05). (4p)23) Report the explained variability (R-squared value) for each variable, whether it is significant based on the p-value. (4p)24) Identify and list any variables that are not significant predictors of house price (i.e., those with p-values greater than 0.05). (2p)Conduct a multiple…
What is the F- test statistic and p-value
Click the Chart sheet tab. This chart is based on the problem data and the two income statements. Answer the following questions about the chart: a. What is the title for the X-axis? b. What is the title for the Y-axis? c. What does data range A represent? d. What does data range B represent? e. Why do the two data ranges cross? f. What would be a good title for this chart? When the assignment is complete, close the file without saving it again. Worksheet. The VARCOST2 worksheet is capable of calculating variable and absorption income when unit sales are equal to or less than production. An equally common situation (that this worksheet cannot handle) is when beginning inventory is present and sales volume exceeds production volume. Revise the worksheet Data Section to include: Also, change actual production to 70,000. Revise the Answer Section to accommodate this new data. Assume that Anderjak uses the weighted-average costing method for inventory. Preview the printout to make sure that the worksheet will print neatly on one page, and then print the worksheet. Save the completed file as VARCOSTT. Check figure: Absorption income, 670,000. Chart. Using the VARCOST2 file, fix up the chart used in requirement 5 by adding appropriate titles and legends and formatting the X- and Y-axes. Enter your name somewhere on the chart. Save the file again as VARCOST2. Print the chart.
Suppose you're given a data set that classifies each sample unit into one of four categories: A, B, C, the data as A = 1, B=2, C = 3, and D=4. Are the data consisting of the classifications A, B, C, and D or quantitative? Are the data consisting of the classifications A, B, C, and D qualitiative or quantitative? OA. Qualitative, because they are measured on a naturally occuring numerical scale. B. Quantitative, because they are measured on a naturally occuring numerical scale. C. Quantitative, because they can only be classified into categories. D. Qualitative, because they can only be classified into categories. *** After the data are input as 1, 2, 3, or 4, are they qualitative or quantitative? OA. Qualitative, because they cannot be meaningfully added, subtracted, multiplied, or divided. B. Qualitative, because they are measured on a naturally occurring numerical scale. OC. Quantitative, because they are measured on a naturally occurring numerical scale. OD. Quantitative, because…
What is the median for the following data set? 4,5,9,3,10,11 show all work.