Statistics Questions

Description

  • Chapter Review Problems (Statistics for Managers Using Microsoft Excel): Complete the Exercise Problems below.
    • Chapter 3, Problems 3.68, 3.70
    • Chapter 4, Problems 4.38, 4.39
  • Requirements: Submit your work to Canvas in Word and/or Excel format, as necessary
  • Exercise Problem 3.68::::: Call centers today play an important role in managing day-to-day business communications with customers. It’s important, therefore, to monitor a comprehensive set of metrics, which can help businesses understand the overall performance of a call center. One key metric for measuring overall call center performance is service level which is defined as the percentage of calls answered by a human agent within a specified number of seconds. The file Service Level contains the following data for time, in seconds, to answer 50 incoming calls to a financial services call center:
    16 14 16 19 6 14 15 5 16 18 17 22 6 18 1015 12 6 19 16 16 15 13 25 9 17 12 10 5 1523 11 12 14 24 9 10 13 14 26 19 20 13 24 2815 21 8 16 12 Calculate the mean, median, range, and standard deviation for the speed of answer, which is the time to answer incoming calls.
    List the five-number summary.
    Construct a boxplot and describe its shape.
    What can you conclude about call center performance if the service level target is set as “75% of calls answered in under 20 seconds?”
  • Exercise Problem 3.70:::::: Data were collected on the typical cost of dining at American-cuisine restaurants within a 1-mile walking distance of a hotel located in a large city. The file Bundle contains the typical cost (a per transaction cost in $) as well as a Bundle score, a measure of overall popularity and customer loyalty, for each of 40 selected restaurants.
    Source: Data extracted from www.bundle.com via the link on-msn.com/MnlBxo.
    For each variable, compute the mean, median, first quartile, and third quartile.
    For each variable, compute the range, interquartile range, variance, standard deviation, and coefficient of variation.
    For each variable, construct a boxplot. Are the data skewed? If so, how?
    Calculate the coefficient of correlation between Bundle score and typical cost.
    What conclusions can you reach concerning Bundle score and typical cost?
  • Exercise Problem 4.38:::::: To better understand the website builder market, Clutch surveyed individuals who had created a website using a do-it-yourself (DIY) website builder. Respondents, categorized by the type of website they built—business or personal—were asked to indicate the primary purpose for building their website. The following table summarizes the findings:
    TYPE OF WEBSITE PRIMARY PURPOSE Business Personal TotalOnline Business Presence 52 4 56Online Sales 32 13 45Creative Display 28 54 82Informational Resources 9 24 33Blog 8 52 60Total 129 147 276Source: Data extracted from “How Businesses Use DIY Web Builders: Clutch 2017 Survey,” bit.ly/2qQjXiq.If a website builder is selected at random, what is the probability that he or she
    indicated creative display as the primary purpose for building his/her website?
    indicated creative display or informational resources as the primary purpose for building his/her website?
    is a business website builder or indicated online sales as the primary purpose for building his/her website?
    is a business website builder and indicated online sales as the primary purpose for building his/her website?
    Given that the website builder selected is a personal website builder, what is the probability that he/she indicated online business presence as the primary purpose for building his/her website?
  • Exercise Problem 4.39:::::: The CMO Survey collects and disseminates the opinions of top marketers in order to predict the future of markets, track marketing excellence, and improve the value of marketing in firms and in society. Part of the survey is devoted to the topic of marketing analytics and understanding what factors prevent companies from using more marketing analytics. The following findings are based on responses from 272 senior marketers within B2B firms and 114 senior marketers within B2C firms.
    Source: Data extracted from “Results by Firm & Industry Characteristics,” The CMO Survey, February 2017, p. 148. bit.ly/2qY3Qvk.
    LACK OF PROCESS/TOOLS TO MEASURE SUCCESS FIRM Yes No TotalB2B 90 182 272B2C 35 79 114Total 125 261 386
    LACK OF PEOPLE WHO CAN LINK TO PRACTICE FIRM Yes No TotalB2B 75 197 272B2C 36 78 114Total 111 275 386What is the probability that a randomly selected senior marketer indicates that lack of process/tools to measure success through analytics is a factor that prevents his/her company from using more marketing analytics?
    Given that a randomly selected senior marketer is within a B2B firm, what is the probability that the senior marketer indicates that lack of process/tools to measure success through analytics is a factor that prevents his/her company from using more marketing analytics?
    Given that a randomly selected senior marketer is within a B2C firm, what is the probability that the senior marketer indicates that lack of process/tools to measure success through analytics is a factor that prevents his/her company from using more marketing analytics?
    What is the probability that a randomly selected senior marketer indicates that lack of people who can link to marketing practice is a factor that prevents his/her company from using more marketing analytics?
    Given that a randomly selected senior marketer is within a B2B firm, what is the probability that the senior marketer indicates that lack of people who can link to marketing practice is a factor that prevents his/her company from using more marketing analytics?
    Given that a randomly selected senior marketer is within a B2C firm, what is the probability that the senior marketer indicates that lack of people who can link to marketing practice is a factor that prevents his/her company from using more marketing analytics?
    Comment on the results in (a) through (f).

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