INSTRUCTOR’S SOLUTIONS@W
MANUAL
@W
DIRK TEMPELAAR
@W
Masstricht University
@w
BUSINESS STATISTICS @ W
THIRD EDITION @ W
Robert A. Donnelly
@w @w
, Table of @w
Contents
@w
Chapter @ w 1: @ w An @ w Introduction @ w to @ w Business @ w Statistics ......................................................... 1-1
Chapter @ w 2: @ w Displaying @ w Descriptive @ w Statistics ....................................................................... 2-1
Chapter @ w 3: @ w Calculating @ w Descriptive @ w Statistics ...................................................................... 3-1
Chapter @ w 4: @ w Introduction @ w to @ w Probabilities................................................................................ 4-1
Chapter @ w 5: @ w Discrete @ w Probability @ w Distributions ...................................................................... 5-1
Chapter @ w 6: @ w Continuous @ w Probability @ w Distributions................................................................. 6-1
Chapter @ w 7: @ w Sampling @ w and @ w Sampling @ w Distributions............................................................. 7-1
Chapter @ w 8: @ w Confidence @ w Intervals .............................................................................................. 8-1
Chapter @ w 9: @ w Hypothesis @ w Testing @ w for @ w a @ w Single @ w Population .............................................. 9-1
Chapter @ w 10: @ w Hypothesis @ w Tests @ w Comparing @ w Two @ w Populations ....................................... 10-1
Chapter @ w 11: @ w Analysis @ w of @ w Variance @ w (ANOVA) @ w Procedures ........................................... 11-1
Chapter @ w 12: @ w Chi-Square @ w Tests ................................................................................................ 12-1
Chapter @ w 13: @ w Hypothesis @ w Tests @ w for @ w the @ w Population @ w Variance ...................................... 13-1
Chapter @ w 14: @ w Correlation @ w and @ w Simple @ w Linear @ w Regression ............................................... 14-1
Chapter @ w 15: @ w Multiple @ w Regression @ w and @ w Model @ w Building................................................. 15-1
Chapter @ w 16: @ w Forecasting .............................................................................................................. 16-1
Chapter @ w 17: @ w Decision @ w Analysis .............................................................................................. 17-1
Chapter @ w 18: @ w Nonparametric @ w Statistics ....................................................................................18-1
, CHAPTER
1.1 . 1 @w
An Introduction to Business Statistics
1.2 Quantitative/Interval. The differences between average monthly temperatures are
meaningful, but there is no true zero point, i.e., absence of temperature.
1.3 Quantitative/Ratio. The differences between average monthly rainfalls are meaningful,
and there is a true zero point, because there may be a month without any rainfalls.
1.4 Qualitative/Ordinal. You can rank education level, but the differences between
different educational levels cannot be measured.
1.5 Qualitative/Nominal. The marital status is just a label without a meaningful difference,
or ranking.
1.6 Quantitative/Ratio. The differences between ages of respondents are meaningful and there
is a true zero point: an age of the respondents that equals zero represents the absence of age.
1.7 Qualitative/Nominal. The genders are merely labels with no ranking or meaningful
difference.
1.8 Quantitative/Interval. The differences between birth years are meaningful, but there is no true
zero point with calendar years.
1.9 Qualitative/ Nominal. The political affiliations are merely labels with no ranking or
meaningful difference.
1.10 Qualitative/ Nominal. The races of the respondents are merely labels with no ranking
or meaningful difference.
1.11 Qualitative/ Ordinal. You can rank the performance rating, but the differences between
different performance ratings cannot be measured.
1.12 Qualitative/ Nominal. The uniform numbers of each member of the school’s sport team are
labels with no ranking or meaningful difference.
1.13 Qualitative/ordinal. The differences in the data values between class ranks are not
meaningful.
, 1-2 Chapter 1
1.14 Quantitative/Ratio. The differences between final exam scores for your statistics class
are meaningful, and there is a true zero point because a student who did not take the exam
would have a score of zero.
1.15 Qualitative/Nominal. The state in which the respondents in a survey reside is a label and it
is meaningless to talk about the rating of this value.
1.16 Quantitative/Interval. The differences between SAT scores for graduating high school
students are meaningful, but there is no true zero point because a student with an SAT score
equal to zero does not indicate the absence of a score.
1.17 Qualitative/Ordinal. You can rank movie ratings, but the differences between
different ratings cannot be measured.
1.18 Qualitative/ordinal. The differences in the data values between ratings are not meaningful.
1.19 Qualitative/ordinal. The differences in the data values between ratings are not meaningful.
1.20 Cross-sectional
1.21 Time series
1.22 Time series: Men weekly earnings over the five years.
Time series: Women weekly earnings over the five years.
1.23 Cross-sectional data: Men and women workers weekly earnings for any one particular year.
1.24 Cross-sectional: The number of 8x10, 11x14 and 13x19 prints sold over a particular year.
1.25 Time series: the number of 8x10 prints sold over the four years.
Time series: the number of 11x14 prints sold over the four years.
Time series: the number of 13x19 prints sold over the four years.
1.26 Descriptive statistics, because it identifies a sample mean.
Inferential statistics, because the statements about comparing the average costs of a hotel room in two
states was based on results from samples taken from two populations
MANUAL
@W
DIRK TEMPELAAR
@W
Masstricht University
@w
BUSINESS STATISTICS @ W
THIRD EDITION @ W
Robert A. Donnelly
@w @w
, Table of @w
Contents
@w
Chapter @ w 1: @ w An @ w Introduction @ w to @ w Business @ w Statistics ......................................................... 1-1
Chapter @ w 2: @ w Displaying @ w Descriptive @ w Statistics ....................................................................... 2-1
Chapter @ w 3: @ w Calculating @ w Descriptive @ w Statistics ...................................................................... 3-1
Chapter @ w 4: @ w Introduction @ w to @ w Probabilities................................................................................ 4-1
Chapter @ w 5: @ w Discrete @ w Probability @ w Distributions ...................................................................... 5-1
Chapter @ w 6: @ w Continuous @ w Probability @ w Distributions................................................................. 6-1
Chapter @ w 7: @ w Sampling @ w and @ w Sampling @ w Distributions............................................................. 7-1
Chapter @ w 8: @ w Confidence @ w Intervals .............................................................................................. 8-1
Chapter @ w 9: @ w Hypothesis @ w Testing @ w for @ w a @ w Single @ w Population .............................................. 9-1
Chapter @ w 10: @ w Hypothesis @ w Tests @ w Comparing @ w Two @ w Populations ....................................... 10-1
Chapter @ w 11: @ w Analysis @ w of @ w Variance @ w (ANOVA) @ w Procedures ........................................... 11-1
Chapter @ w 12: @ w Chi-Square @ w Tests ................................................................................................ 12-1
Chapter @ w 13: @ w Hypothesis @ w Tests @ w for @ w the @ w Population @ w Variance ...................................... 13-1
Chapter @ w 14: @ w Correlation @ w and @ w Simple @ w Linear @ w Regression ............................................... 14-1
Chapter @ w 15: @ w Multiple @ w Regression @ w and @ w Model @ w Building................................................. 15-1
Chapter @ w 16: @ w Forecasting .............................................................................................................. 16-1
Chapter @ w 17: @ w Decision @ w Analysis .............................................................................................. 17-1
Chapter @ w 18: @ w Nonparametric @ w Statistics ....................................................................................18-1
, CHAPTER
1.1 . 1 @w
An Introduction to Business Statistics
1.2 Quantitative/Interval. The differences between average monthly temperatures are
meaningful, but there is no true zero point, i.e., absence of temperature.
1.3 Quantitative/Ratio. The differences between average monthly rainfalls are meaningful,
and there is a true zero point, because there may be a month without any rainfalls.
1.4 Qualitative/Ordinal. You can rank education level, but the differences between
different educational levels cannot be measured.
1.5 Qualitative/Nominal. The marital status is just a label without a meaningful difference,
or ranking.
1.6 Quantitative/Ratio. The differences between ages of respondents are meaningful and there
is a true zero point: an age of the respondents that equals zero represents the absence of age.
1.7 Qualitative/Nominal. The genders are merely labels with no ranking or meaningful
difference.
1.8 Quantitative/Interval. The differences between birth years are meaningful, but there is no true
zero point with calendar years.
1.9 Qualitative/ Nominal. The political affiliations are merely labels with no ranking or
meaningful difference.
1.10 Qualitative/ Nominal. The races of the respondents are merely labels with no ranking
or meaningful difference.
1.11 Qualitative/ Ordinal. You can rank the performance rating, but the differences between
different performance ratings cannot be measured.
1.12 Qualitative/ Nominal. The uniform numbers of each member of the school’s sport team are
labels with no ranking or meaningful difference.
1.13 Qualitative/ordinal. The differences in the data values between class ranks are not
meaningful.
, 1-2 Chapter 1
1.14 Quantitative/Ratio. The differences between final exam scores for your statistics class
are meaningful, and there is a true zero point because a student who did not take the exam
would have a score of zero.
1.15 Qualitative/Nominal. The state in which the respondents in a survey reside is a label and it
is meaningless to talk about the rating of this value.
1.16 Quantitative/Interval. The differences between SAT scores for graduating high school
students are meaningful, but there is no true zero point because a student with an SAT score
equal to zero does not indicate the absence of a score.
1.17 Qualitative/Ordinal. You can rank movie ratings, but the differences between
different ratings cannot be measured.
1.18 Qualitative/ordinal. The differences in the data values between ratings are not meaningful.
1.19 Qualitative/ordinal. The differences in the data values between ratings are not meaningful.
1.20 Cross-sectional
1.21 Time series
1.22 Time series: Men weekly earnings over the five years.
Time series: Women weekly earnings over the five years.
1.23 Cross-sectional data: Men and women workers weekly earnings for any one particular year.
1.24 Cross-sectional: The number of 8x10, 11x14 and 13x19 prints sold over a particular year.
1.25 Time series: the number of 8x10 prints sold over the four years.
Time series: the number of 11x14 prints sold over the four years.
Time series: the number of 13x19 prints sold over the four years.
1.26 Descriptive statistics, because it identifies a sample mean.
Inferential statistics, because the statements about comparing the average costs of a hotel room in two
states was based on results from samples taken from two populations
