Solutions Manual - Excel 2010 Updated Second Edition Judith Skuce ...

Solutions Manual

For Analyzing Data and Making Decisions

Statistics for Business Microsoft Excel 2010 Updated Second Edition

Judith Skuce

Part 1: Page 1-454

Part 2: Page 455-732 1 / 4

Contents

Part I: Introduction

Chapter 1: Using Data to Make Better Decisions................................................................1

Part II: Descriptive Statistics

Chapter 2: Using Graphs and Tables to Describe Data .......................................................9 Chapter 3: Using Numbers to Describe Data.....................................................................51

Part III: Building Blocks for Inferential Statistics

Chapter 4: Calculating Probabilities..................................................................................65 Chapter 5: Probability Distributions..................................................................................88 Chapter 6: Using Sampling Distributions to Make Decisions.........................................108

Part IV: Making Decisions

Chapter 7: Making Decisions with a Single Sample .......................................................129 Chapter 8: Estimating Population Values........................................................................161 Chapter 9: Making Decisions with Matched Pairs Samples, Quantitative or Ranked Data..........................................................................194

Chapter 10: Making Decisions with Two Independent Samples,

Quantitative or Ranked Data..........................................................................234

Chapter 11: Making Decisions with Three or More Samples,

Quanitative Data—Analysis of Variance (ANOVA) ....................................275

Chapter 12: Making Decisions with Two or More Samples,

Qualitative Data .............................................................................................321

Part V: Analyzing Relationships

Chapter 13: Analyzing Linear Relationships, Two Quantitative Variables ....................351 Chapter 14: Analyzing Linear Relationships, Two or More Variables ...........................389 2 / 4

Instructor’s Solutions Manual - Chapter 1 Chapter 1 Solutions

Develop Your Skills 1.1

• You would have to collect these data directly from the students, by asking them. This would be difficult and time-consuming, unless you are attending a very small

school. You might be able to get a list of all the students attending the school, but privacy protection laws would make this difficult. No matter how much you tried, you would probably find it impossible to locate and interview every single student (some would be absent because of illness or work commitments or because they do not attend class regularly). Some people may refuse to answer your questions. Some people may lie about their music preferences. It would be difficult to solve some of these problems. You might ask for the school's cooperation in contacting students, but it is unlikely they would comply. You could offer some kind of reward for students who participate, but this could be expensive. You could enter participants' names in a contest, with a music-related reward available. None of these approaches could guarantee that you could collect all the data, or that students would accurately report their preferences. One partial solution would be to collect data from a random sample of students, as you will see in the discussion in Section 1.2 of the text. Without a list of all students, it would be difficult to ensure that you had a truly random sample, but this approach is probably more workable than a census (that is, interviewing every student).

• Because you need specific data on quality of bicycle components, you would need to

collect primary data. Customer complaints about quality are probably the only source of secondary data that you would have.

• Statistics Canada has a CANSIM Table 203-0010, Survey of household spending

(SHS), household spending on recreation, by province and territory, annual, which contains information on purchases of bicycles, parts and accessories.

There is a U.S. trade publication called "Bicycle Retailer & Industry News", which

provides information about the industry. See http://www.bicycleretailer.com/

. Access is provided through the Business Source Complete database.Industry Canada provides a STAT-USA report on the bicycle industry in Canada, at

http://strategis.ic.gc.ca/epic/internet/inim

r-ri.nsf/en/gr105431e.html . Somewhat

outdated information is also available at http://www.ic.gc.ca/eic/site/sg-

as.nsf/eng/sg03430.html.Canadian Business magazine has a number of articles on the bicycle industry. One of the most recent describes the purchase of the Iron Horse Co. of New York by Dorel Industries (a Montreal firm). http://www.canadianbusiness.com/markets/headline_news/article.jsp?content=b1560 9913

Copyright © 2011 Pearson Canada Inc. 1 3 / 4

Instructor’s Solutions Manual - Chapter 1

• Although Statistics Canada takes great care in its data collection, errors do still occur,

and data revisions are required. An interesting overview of GDP data quality for seven OECD countries is available at

http://www.oecd.org/dataoecd/20/26/34350524.pdf

You should be able to locate other information about data revisions. See also

http://www.statcan.ca/english/about/policy/infousers.htm

which describes Statistics Canada’s policy on informing users about data quality.

• At least some of the secondary data sources listed in Section 1.1 should help you. If

you cannot locate any secondary data, get help from a librarian.Develop Your Skills 1.2

• The goal for companies is to create population data, but it is unlikely that every

customer is captured in any CRM database. There are many examples of companies using CRM data. A search of the CBCA database on August 7, 2009 produced a list of 102 articles (for 2009) that contained “customer relationship management” as part of their citation and indexing. For example, the publication called "Direct Marketing" regularly writes about database marketing, data mining, and web analytics. See

http://www.dmn.ca/index.html

.

• This is a nonstatistical sample, and could be described as a convenience sample. The

restaurant presumably has diners on nights other than Friday, and none of these could be selected for the sample. The owner should not rely on the sample data to describe all of the restaurant's diners, although the sample might be useful to test reaction to a new menu item, for example.

• These are sample statistics, as they are based on sample data. It would be impossible

to collect data from all postsecondary students.

• Follow the instructions for Example 1.2c. The random sample you get will be

different, but here is one example of the 10 names selected randomly.

AVERY MOORE

EMILY MCCONNELL

HARRIET COOGAN

DYLAN MILES

TERRY DUNCAN

GEORGE BARTON

JAMES BARCLAY

AVA WORTH

PAIGE EATON

JORDAN BOCK

• First, Calgary Transit will probably find it impossible to establish a frame for its

target population, which is people with disabilities who use Calgary Transit. It will also have to carefully define what it means by “people with disabilities”. If this Copyright © 2011 Pearson Canada Inc. 2

• / 4