According to the text, fear appeals are generally effective except when they scare people without providing constructive advice for avoiding the feared consequences. Four theories have been used to explain the occasional failure of fear appeals.
 

The first theory is Witte’s extended parallel process model (EPPM; 1992). According to EPPM, fear appeal messages provoke two different responses from an audience. One possible response is the tendency to control the danger. This response occurs when a person perceives the danger but at the same time feels capable of acting against it. Accordingly, the person is persuaded by the fear appeal and takes the recommended steps to reduce his or her risk.
 

The other possible response is the tendency to control the fear. This response occurs when the person perceives the danger but does not see a clear way to avoid the risk in the message. As a result, the person tries to control the fear elicited by the message by not thinking about it or by denying its importance. Accordingly, the person is not persuaded by the fear appeal and takes no steps to reduce risk.
 

The second theory is Lerner’s just world hypothesis (1965). Believing that the world is fair leads people to assume that everyone gets what they deserve. Such a belief allows an individual to disengage from the message in a fear appeal. In essence, the person believes that bad things are just not going to happen because he or she hadn’t done anything bad. So, the message delivered by a fear appeal is likely to be ignored when a person believes in a just world.
 

The third theory is protection motivation theory (Rogers, 1975). The theory states that when an individual comes across a fear appeal, he or she assesses the severity of the situation, the probability of something bad happening, the likelihood that the recommended actions of the message will help, and his or her ability to follow the message’s advice. When the threat is high and when the recommended actions are clear and doable, it’s likely that the fear appeal will work. When any of those conditions do not exist, the appeal will fail to convince.
 

The fourth theory is terror management theory (Shehryar & Hunt, 2005). According to this perspective, the fact that human beings have strong survival instincts coupled with their sense of their own vulnerability produces feelings of terror whenever they are reminded of their mortality. This terror is managed by means of an anxiety buffer that is made up of a cultural worldview defined by a set of values and the belief that one is living up to those self-imposed standards. It follows that when fear appeals remind people of impending death, people who are highly committed to their worldview are more likely to feel high anxiety and defend their worldview by rejecting the message.
 

Apply each one of the theories to explain why a smoker may reject a message that features another cigarette smoker who is dying of lung cancer.

Microsoft adheres to a defense-in-depth principle to ensure protection of its cloud services, such as Microsoft Office 365. Built-in security features include threat protection to reduce malware infections, phishing attacks, distributed denial of service (DDoS) attacks, and other types of security threats.Answer the following question(s):

• Would an organization need to apply security controls to allow safe use of those applications? Why or why not?

Fully address the question(s) in this discussion; provide valid rationale for your choices, where applicable, be sure to include three questions in your thread 

500 words

APA format with references needed.

One of the most difficult tasks for an internet vendor is deciding what to sell. It might be more difficult than you think to find out what things to offer, but with web scraping, this is no longer an issue. Scraping the internet is a cutting-edge technique that is here to stay. With the emergence of big data, more companies are realising the value of having detailed information on their customers and, more significantly, their rivals. You don’t have to depend on random data or statistics you get online if you use a web scraping programme. In most cases, this kind of data has minor inaccuracies or variances. As a result, relying on this while determining what to sell would be dangerous. (url href=”https://it-s.com/our-services/data-tranformation-services/web-scraping-services/”]Web Scraping Services  [/url] are the  technologies that are preferable to eliminate any second-guessing since you will be collecting the accurate data firsthand. Furthermore, a web scraping tool allows you to scrape data from any eCommerce site, such as Amazon. When it comes to choosing a product to sell online, price is crucial. As important as it is to price your items properly enough to generate a profit, it is as critical not to overprice them. Pricing research is a must-do before you choose a product to market.

Many clients will entirely disregard your goods if you price it too high. On the other hand, if you price it too low, customers may believe your product is inferior or unimportant. As a result, you must get the ideal price. How can you figure out which pricing is ideal? When you have a pricing database for the items on the market, together with sales data, you can figure out how price sensitive clients are and where the profit will be maximised. You need to know what your consumers desire as a vendor. And you won’t know until you pay attention to them. Scraping product reviews is the most efficient technique to learn what people are saying about various items. This manner, you may learn about the benefits and drawbacks of various items and be well-informed about the things that people are eager to acquire. You should check the market volume before you start selling a product. To put it another way, you want to make sure that consumers desire whatever you’re selling. You should scrape data to observe how many individuals buy the product on a daily or monthly basis. This may prevent you from selling a product that no one wants to purchase. You should only try to market items that people desire and will pay for. Web scraping eCommerce sites to track rival items over time might give valuable information about product and market trends. You can examine how consumers behaved when prices were raised if you have historical market data. During instances of great demand, you might notice items that prosper or suffer. Overall, historical market data may assist you in gaining a better understanding of the industry and predicting future patterns. The information on a product’s rating simply informs you how people feel about a brand’s product. If there is just one shop with a high average rating and very high sales, the product is offered by a monopoly. Competing against a billionaire of this kind is not a smart idea for a newcomer.

 On the other hand, if all of the items have a very low average rating, it is unlikely that you will be able to sell them since clients do not value them. While this is a fantastic time to look into it and see where you can distinguish your product, it’s also a good time to be creative. Not every website is the same. Every website has its own structure and design. As a result, a single scraper will not be able to scrape data from two separate websites. To put it another way, each website need its own crawler. In reality, anytime a website’s content is updated, the scraper must be updated as well. As a result, a web scraper’s ability to alter itself becomes a concern. Some online scrapers go around this by imitating human behaviour while engaging with various websites. Anti-scraping tools are programmes that are installed on websites to prevent web scraping. When a website observes a significant number of queries from the same IP address, for example, the IP address of a web scraper might be banned. Another “inconvenient” anti-scraping method is CAPTCHA. It’s used by websites to tell the difference between people and bots by showing logical questions that only humans can answer. Because site scrapers are run by bots, this might be problematic. Web scrapers, on the other hand, have been able to construct bots that use CAPTCHA solvers to avoid any unwanted blocks. Trying to scrape hundreds of records from an eCommerce website with that much information isn’t going to happen in a matter of seconds. It might take a long time, and even if the task is completed, the data’s accuracy may have been compromised. As a result, huge data might be problematic at times. Cloud extraction is used by most web scrapers to counteract this. Cloud extraction allows you to extract data from many servers using different IP addresses in the cloud. That manner, you can reliably extract vast amounts of data at a quick pace. It may be difficult to arrange a large volume of data into a clean format that is valuable to you once it has been scraped. Web scrapers, on the other hand, may sanitise extracted data into the best format you desire using re-format choices. When fresh information becomes available, data scraped yesterday may become outdated today. This is particularly true in the news business. Obtaining real-time data on a regular basis might be difficult; the data amount would be high, and more work would be required to review the changes. There is, however, a remedy to this problem. All of this tedious effort will be automated by scraping on a regular basis.

Exp19_Excel_Ch03_ML2_Grades

Exp19 Excel Ch03 ML2 Grades

Excel Chapter 3 Mid-Level 2 – Grades 

Project Description:

You are a teaching assistant for Dr. Elizabeth Croghan’s BUS 101 Introduction to Business class. You have maintained her gradebook all semester, entering three test scores for each student and calculating the final average. You created a section called Final Grade Distribution that contains calculations to identify the number of students who earned an A, B, C, D, or F. Dr. Croghan wants you to create a chart that shows the percentage of students who earn each letter grade. Therefore, you decide to create and format a pie chart. You will also create a bar chart to show a sample of the students’ test scores. Furthermore, Dr. Croghan wants to see if a correlation exists between attendance and students’ final grades; therefore, you will create a scatter chart depicting each student’s percentage of attendance with his or her respective final grade average.

Start Excel. Download   and open the file named Exp19_Excel_Ch03_ML2_Grades.xlsx.   Grader has automatically added your last name to the beginning of the   filename.

A pie chart is an   effective way to visually illustrate the percentage of the class that earned   A, B, C, D, and F grades.
  Use the Insert tab to create a pie chart from the Final Grade Distribution   data located below the student data in the range F35:G39 and move the pie   chart to its own sheet named Final Grade Distribution.

You should enter a   chart title to describe the purpose of the chart. You will customize the pie   chart to focus on particular slices.
  •Apply the Style 12 chart style.
  •Type BUS 101 Final Grades: Fall 2021 for the chart title.
  •Explode the A grade slice by 7%.
  •Change the F grade slice to Dark Red.
  •Remove the legend.

A best practice is to   add Alt Text for accessibility compliance.
  Add Alt Text: The pie chart shows percentage of students who earned   each letter grade. Most students earned B and C grades. (including the   period).

You want to add data   labels to indicate the category and percentage of the class that earned each   letter grade
  Add centered data labels. Select data label options to display Percentage and   Category Name in the Inside End position. Remove the Values data labels. 

Apply 20-pt size and   apply Black, Text 1 font color to the data labels.

You want to create a   bar chart to depict grades for a sample of the students in the class.
  Create a clustered bar chart using the ranges A5:D5 and A18:D23 in the Grades   worksheet. Move the bar chart to its own sheet named Sample   Student Scores 

Customize the bar   chart with these specifications: Style 5 chart style, legend on the right   side in 11 pt font size, and Light Gradient – Accent 2 fill color for the   plot area.

Type Sample   Student Test Scores for the chart title.

Displaying the exact   scores would help clarify the data in the chart.
  Add data labels in the Outside End position for all data series. Format the   Final Exam data series with Blue-Gray, Text 2 fill color.

Select the category   axis and display the categories in reverse order in the Format Axis task pane   so that O’Hair is listed at the top   and Sager is listed at the bottom   of the bar chart.
  Add Alt Text: The chart shows test scores for six students in the   middle of the list. (including the period).

You want to create a   scatter chart to see if the combination of attendance and final averages are   related.
  Display the Grades worksheet. Select the range E5:F31 and create a scatter   chart. Cut the chart and paste it in cell A42. Set a height of 5.5″ and a width of 5.96″.

Add Alt Text: The   scatter chart shows the relationship of each student’s final grade and his or   her attendance record. (including the period).

Titles will help   people understand what is being plotted in the horizontal and vertical axes,   as well as the overall chart purpose.
  Make sure the scatter chart is selected. Type Final Average-Attendance   Relationship as the chart title, type Percentage of Attendance as the primary   horizontal axis title, and type Student Final Averages as the primary   vertical axis title.

To distinguish the   points better, you can start the plotting at 40 rather than 0.
  Make sure the scatter chart is selected. Apply these settings to the vertical   axis of the scatter chart: 40 minimum bound, 100   maximum   bound, 10 major units, and a number format with zero decimal   places.

Make sure the scatter   chart is selected. Apply these settings to the horizontal axis: 40   minimum   bound, 100 maximum bound, automatic units.

Adding a fill to the   plot area will add a touch of color to the chart.
  Make sure the scatter chart is selected. Add the Parchment texture fill to   the plot area.

You want to insert a   trendline to determine trends.
  Make sure the scatter chart is selected and insert a linear trendline.

You want to add   sparklines to detect trends for each student.
  Select the range B6:D31 on the Grades sheet, create a column Sparkline, and   type H6:H31 in the Location Range box. Display the Low Point.   Set the Vertical Axis Minimum and Maximum Values to be the same for all   Sparklines.

To make the   Sparklines more effective and easier to read, you will increase the row   height.
  Change the row height to 22 for rows 6 through 31.

Insert a footer with Exploring   Series   on the left, the sheet name code in the center, and the file name code on the   right on all the sheets. Group the two chart sheets together to insert the   footer. Then insert the footer on the Grades sheet. Change to Normal view

Save and close Exp19_Excel_Ch03_ML2_Grades.xlsx. Exit   Excel. Submit the file as directed.

Your initial post should be based upon the assigned reading for the week, so the textbook must be the only source utilized and listed in your reference section (and properly cited within the body of the text). Other sources are not required and are a waste of time to search and utilize. Only use the textbook.

Do not provide a Reflection or Chapter Overview. Provide only a graduate-level response to each of the following questions:

1. The project manager and sponsor need to act in the best interest of which three constituencies?
2. Describe how to use project documents to help a team progress through the stages of development.
3. Describe each method of decision making a project team may use. Using examples, tell when each is most appropriate.

Your post must be substantive and demonstrate insight gained from the course material. Postings must be in the student’s own words – do not provide quotes!

Must be minimum 600 words in APA format.

Text

Title: Contemporary Project Management ISBN: 9781337406451 Authors: Timothy Kloppenborg, Vittal S. Anantatmula, Kathryn Wells Publisher: Cengage Learning Publication Date: 2018-02-08 Edition: 4th 

Develop and apply an appropriate and useful inheritance hierarchy.

Uuse multiple cpp and header files effectively to develop modular code. Background Assume that all baseball players, regardless of their position, have these two important statistics: • rbi – runs batted in, a whole number (so you must data type int) • batting average – real number percentage of hits per at-bat (a real number, so you must use data type double) Pitchers are baseball players with an additional statistic, era (earned run average), a real number for earned runs per nine innings pitched (so you must use data type double). Developing the Class Hierarchy A logical class hierarchy for these two types of objects would use a Player class as a parent (base) class for a derived (child) Pitcher class. The Pitcher class would include all the members of the Player class and have an additional (private) era data member, and, of course, appropriate (public) accessor, mutator and constructor methods. This relationship is sometimes called a tree, but is also called a hierarchy, more particularly in this case, a class hierarchy. Note that the arrow points from derived (child) class to parent (base) class, which indicates the search path for executing member methods; if the method is not found in the Pitcher class, the compiler looks back to the parent class, Player, to find it. File Organization (Class Header and Implementation Files, etc.) Each class (in this case Player and Pitcher) will have its own header (.h) and implementation (.cpp) file, and, of course, there needs to be an executable file that actually uses the class (an application .cpp file with a main function). As with the classes previously developed in the course, the application will be a “driver” program that executes each member function at least once with an arbitrary, but specific test case data set. Requirements Use the given Player class as a base class for Pitcher and add to the BaseballPlayerDriver file code to test the class with the data specified below. Player class requirements: 1. Create with separate header (Player.h) and implementation (Player.cpp) files. 2. Two private data members, rbi and battingAverage. 3. A parameterized constructor that receives and sets the initial values for both rbi and battingAverage. 4. Two accessor (get) methods that return the values of the data members: getRbi and getBattingAverage. 5. Two mutator methods: 5.1. setRbi that receives a whole number and writes it to the rbi data member. 5.2. setBattingAverage that receives a real number and writes it to the battingAverage data member. 6. showAll accessor method that displays the values of both data members as shown here for an arbitrary test case for a player who has 10 rbi and batting average 0.1234: rbi = 10 batting average = 123 Note that the battingAverage variable will be a floating point number (double), but it must be rounded and display as a digit integer. Pitcher class requirements: 1. Pitcher class must be derived from Player class. 2. Create with separate header (Pitcher.h) and implementation (Pitcher.cpp) files. 3. One private data member, era. 4. A parameterized constructor that receives and sets the initial values for all three data members, rbi, battingAverage and era. 5. getEra accessor method that returns the value of era. 6. setEra mutator method that receives a real number and writes it to the era data member. 7. showAll function to over-ride the base class’s showAll function and do the following: call the base class’s showAll function to display the inherited data members’ values and, in addition, output the additional value, the pitcher’s era, as shown for an arbitrary test case for a pitcher who has 10 rbi, batting average 0.1234 and era of 3.456: rbi = 10 batting average = 123 era = 3.46 Note that the era variable will be a floating point number (double), but it must be rounded and display to decimal places. BaseballPlayerDriver class requirements: 1. Tell the user you’re creating a Pitcher with 10 rbi, batting average 0.1234 and era 3.456. 2. Use the parameterized constructor to create to instantiate a Pitcher variable, p1 with initial values 10 rbi, batting average 0.1234 and era 3.456. 3. Tell the user you’re using the get methods to display the values of the data members. 4. Use cout and the three get methods to display the values. 5. Tell the user you’re using the showAll method to display the values of the data members. 6. Call the showAll method. 7. Tell the user you’re using setRbi to change it to 9. 8. Use setRbi to change it to 9. 9. Use showAll to display the data values. 10. Tell the user you’re using setBattingAverage to change it to 0.2345. 11. Use setBattingAverage to change it to 0.2345. 12. Use showAll to display the data values. 13. Tell the user you’re using setEra to change it to 5.678. 14. Use setEra to change it to 5.678. 15. Use showAll to display the data values. Additional Requirement: Use the const modifier for member functions that do not write to a data member to guarantee the data members are protected. Report Put all five files (Player.h, Player.cpp, Pitcher.h, Pitcher.cpp and BaseballPlayerDriver.cpp ) in a folder called FirstNameLastNameLab3Pitcher, zip it into a file named FirstNameLastNameLab3Pitcher.zip and submit it to the Week 3 Drop Box by the deadline.

must be deliver in 16 hours

Application:

The Galaxy Hotel asks you to write a Windows application that computes the occupancy rate of the hotel. Occupancy rate is a percentage that is equal to the number of rooms sold divided by the total number of rooms available. The hotel has seven floors. The user should use an InputBox Function to respond to two questions about each floor: How many rooms are occupied on that floor? How many rooms on the floor are vacant? Display which floor you are asking about in each question. Display how many rooms are occupied and vacant on each floor in a ListBox object. After the user has entered all the information, display the following results: the total number of rooms at the hotel, the number of occupied rooms, and the number of vacant rooms. Also display the occupancy rate as a percentage, such as 61%. Non-numeric values should not be accepted. Do not accept negative numbers. Publish the application after testing the application.

requirements

1. At least one loop (since there are seven floors, which type of loop will you use?)

2. Validate no non-numeric data and/or negative numbers

3. Displays the following:

1. List box showing each floor occupied and vacant

2. Total rooms

3. Occupied rooms

4. Occupancy rate as a percentage

Exp22_Excel_AppCapstone_IntroAssessment_Travel  

Exp22 Excel AppCapstone IntroAssessment Travel

Excel Application Capstone Assessment 

Project Description:

You are considering several cities for a vacation. In particular, you are interested in Washington DC, Philadelphia, and Boston. You will format a list of memorials in DC, add Sparklines to compare the number of visitors over a 15-year period, and create a bar chart to illustrate annual visitors at each memorial. In addition, you will create a table of sightseeing locations, sort and filter the data, apply conditional formatting, and add a total row to display average time needed to spend at each memorial. Finally, you will complete a worksheet by adding formulas to compare estimated major expenses for each city.

Start Excel. Download and open   the file named Exp22_Excel_AppCapstone_IntroAssessment_Travel.xlsx.   Grader has automatically added your last name to the beginning of the   filename.

One worksheet has the original   default name, Sheet1. You want to give the worksheet a meaningful name.
 

  Rename Sheet1 as DC2017.

You want to move the Year   Completed column between the Memorial and 2002 columns.
 

  Select and cut column F. Insert cut cells in cell B1.

Now you want to separate the   worksheet title and source from the dataset with a blank row.
 

  Insert a blank row between rows 2 and 3.

Now you are ready to work with   the DC2020 worksheet. Your first task is to correct spelling errors.
 

  Display the DC2020 worksheet. Check the spelling and correct all misspelled   words.

Continue using the DC2020   worksheet. You will format the headings on row 4.
 

  Select the range A4:G4, wrap the text, apply Center horizontal alignment, and   apply Blue, Accent 5, Lighter 60% fill color.

You now want to format the title   so that it is more prominent.
 

  Merge and center the title in the range A1:G1. Apply Blue, Accent5 cell style   and bold to the title.

The first column is too narrow   for the names of the memorials. You will increase the width to display the   full memorial names.
 

  Change the width of column A to 34.

Sparklines provide visual   representations of data. You will insert sparklines for the dataset.
 

  Select the range C5:F10 and insert Line Sparklines in the range G5:G10.

Now you will format the   sparklines.
 

  Select the range G5:G10, display the high point sparkline marker, and change   the color of the high point markers to Dark Red.

You want to create a chart that   compares the number of visitors for each memorial.
 

  Select the ranges A4:A10 and C4:F10 and create a clustered column chart.   Apply the Monochromatic Palette 12 chart color. Apply the gradient fill to   the chart area. Do not change the default gradient options.

The chart displays over the   data. You will move it below the dataset and adjust its size. In addition,   you will add Alt Text for accessibility compliance.
 

  Cut the chart and paste it in cell A13. Change the chart height to 6″   and the chart width to 7″. Add Alt Text The chart shows the number of visitors to   each memorial for four years. (including the period).

The chart needs a meaningful   title. In addition, you want to format the axes and add gridlines.
 

  Change the chart title to Annual Visitors. Apply Blue, Accent 5, Darker 25% font color to   the chart title and category axis labels. Change the value axis display units   to Millions. Add Primary Minor Vertical gridlines to the chart.

You want to add data labels for   one data series.
 

  Apply data labels to the outside end position of the 2020 data series. Apply   Number format with 1 decimal place to the data labels.

Now you are ready to focus on   the Places worksheet. First, you will find an abbreviation and replace it   with a city name.
 

  Display the Places worksheet. Find all occurrences of BOS and replace them with Boston.

You decide to convert the   dataset to a table, assign a name to the table, and apply a table style.
 

  Convert the data to a table, assign the table name Tourist_Attractions, and apply Blue, Table Style   Light 13.

The table on the Places   worksheet is large. As you scroll through the table, you want the headings to   remain onscreen.
 

  Freeze the top row.

You decide to rearrange the data   to cluster the memorials by city and then by location.
 

  Sort the table by City in alphabetical order and then within City, sort by   Sightseeing Locations in alphabetical order.

You want to insert a total row   to display the average time recommended to view the memorials.
 

  Add a total row. Change the total value to display the average of the Time   Needed column. Apply Number format with zero decimal places to the total.   Type Average   Time in cell   A41.

You want to apply conditional   formatting to highlight the times over 60 minutes to view the memorial.
 

  Select the values in the Time Needed column (range D2:D40) and apply   conditional formatting to highlight cells containing values greater than 60 with Light Red Fill.

Most memorials have free   admission, but some charge a small fee. You want to set a filter to display   only memorials that charge less than or equal to $10.
 

  Apply a filter to display only fees that are less than or equal to $10.

For the rest of the tasks, you   will work with the Cities worksheet. Your first task is to enter today’s   date.
 

  Display the Cities worksheet. Insert the TODAY function in cell B1.

You want to calculate the   estimated car rental cost.
 

  Click cell F4 and enter a formula that will subtract the Departure Date (B2)   from the Return Date (B3) and then multiply the result by the Rental Car per   Day value (F3).

Depending on the city, you will   either take a shuttle to/from the airport or rent a car. Your next task is to   enter the cost of the shuttle or rental car in the dataset using a logical   function.
 

  Click cell E14. Insert an IF function that compares to see if Yes or No is   located in the Rental Car? column for a city. If the cell contains No, display the shuttle value in   cell F2. If the cell contains Yes, display the value in the Rental Car Total   (cell F4). Copy the function from cell E14. Use the Paste Formulas option to   copy the function to the range E15:E19 without removing the border in cell   E19.

Next, you will enter a formula   to calculate the lodging. The lodging is based on a multiplier by City Type.   Some cities are more expensive than others. You coded cities 1, 2, 3, or 4   and a percentage of cost.
 

  Click cell F14. Insert a VLOOKUP function that looks up the City Type (cell   B14), compares it to the City/COL range (A8:B11), and returns the COL   percentage. Then multiply the result of the lookup function by the Total Base   Lodging (cell B6) to get the estimated lodging for the first city. Copy the   function from cell F14 and use the Paste Formulas option to copy the function   to the range F15:F19 without removing the border in cell F19.

You are now ready to calculate   the total expenses for each city.
 

  Click cell H14 and enter the function that calculates the total costs for the   first city, including airfare, shuttle or rental, lodging, and meals. Copy   the function in cell H14 and use the Paste Formulas option to copy the   function to the range H15:H19 without removing the border in cell H19.

You are considering taking out a   one-year (12 month) loan to pay for your vacation.
 

  In cell I14, insert the PMT function. Divide the APR (cell I7) by the number   of months in a year (cell I8). The   term is one year (12 months). Use a cell reference. The Total Cost for the   city is the present value. Use relative and mixed (or absolute) references   correctly. Make sure the result is a positive value. Copy the function from   cell I14 to the range I15:I19 and maintain the original border formatting.

You decide to format the values   in the dataset.
 

  Select the range E15:I19 and apply Comma Style with zero decimal places.   Select the range E14:I14 and apply Accounting Number format with zero decimal   places.

The Summary Trip Costs section   is designed to display average, lowest, and highest costs.
 

  In cell I2, enter a function that will calculate the average total cost per   city. In cell I3, enter a function that will identify the lowest total cost.   In cell I4 enter a function that will return the highest total cost.

The Lookup section (range D7:F8)   is designed to enable you to enter a city in cell D8 and return the   corresponding total cost for that vacation.
 

  In cell F8, insert the XLOOKUP function that looks up the city in cell D8,   compares it to the Destination City range and returns the applicable Total Cost. Use appropriate ranges. Enter Boston in cell D8 to make sure the function returns   the correct value.

On the Cities worksheet, select   Landscape orientation, set a 1″ top margin, and center the worksheet   data horizontally on the page.

Save and close Exp22_Excel_AppCapstone_IntroAssessment_Travel.xlsx.   Exit Excel. Submit the file as directed.

The Harvard Business School Publishing Coursepack is required for this discussion. You can purchase it on this link: Harvard Business course pack.

In recent years, many firms use algorithms to help make management group’s decisions and optimize operation processes and supply chains. When such algorithms produce unexpected outcomes, bias concerns may arise. Thus, removing these kinds of bias from the data is so critical in data-driven business. Based on this case anlaysis, please elaborate on the questions below.

Q1) Please address the concept of ‘algorithmic bias’ in a marketing context. What is the reason behind the bias in this case?

Q2) How might a firm acquire capability to analyze situations and detect whether algorithmic bias occurs and how it can be mitigated?

Q3) Algorithmic bias can occur even when demographic data is not used as a variable by the algorithm.  What would you play a role as an information sysem manager if a bias was brough to your attention?