Solution Manual For Business Statistics 3rd Edition by Robert Donnelly, ISBN: 9780134685267, All Chapters 1 to 18 Covered, Verified Latest Edition
Solution Manual For Business Statistics 3rd Edition by Robert Donnelly All 1-18 Chapters Covered ,Latest Edition, ISBN:9780134685267
Solution Manual For Business Statistics 3rd Edition by Robert Donnelly, ISBN: 9780134685267, All 18 Chapters Covered, Verified Latest Edition
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BUSINESS STATISTICS 3RD EDITION BY DIRK TEMPELAAR
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SOLUTIONS MANUAL FOR BUSINESS STATISTICS
3RD EDITION BY DIRK TEMPELAAR , ROBERT A.
DONNELLY A+
CHAPTER 1
An Introduction to Business Statistics
1.1 Quantitative/Interval. The differences between average monthly temperatures are meaningful, but
there is no true zero point, i.e., absence of temperature.
1.2 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.
1.3 Qualitative/Ordinal. You can rank education level, but the differences between different
educational levels cannot be measured.
1.4 Qualitative/Nominal. The marital status is just a label without a meaningful difference, or ranking.
1.5 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.
1.6 Qualitative/Nominal. The genders are merely labels with no ranking or meaningful difference.
1.7 Quantitative/Interval. The differences between birth years are meaningful, but there is no true zero
point with calendar years.
1.8 Qualitative/ Nominal. The political affiliations are merely labels with no ranking or meaningful
difference.
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1.9 Qualitative/ Nominal. The races of the respondents are merely labels with no ranking or
meaningful difference.
1.10 Qualitative/ Ordinal. You can rank the performance rating, but the differences between different
performance ratings cannot be measured.
1.11 Qualitative/ Nominal. The uniform numbers of each member of the school’s sport team are labels
with no ranking or meaningful difference.
1.12 Qualitative/ordinal. The differences in the data values between class ranks are not meaningful.
1-2 Chapter 1
1.13 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.
1.14 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.
1.15 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.
1.16 Qualitative/Ordinal. You can rank movie ratings, but the differences between different ratings
cannot be measured.
1.17 Qualitative/ordinal. The differences in the data values between ratings are not meaningful.
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1.18 Qualitative/ordinal. The differences in the data values between ratings are not meaningful.
1.19 Cross-sectional
1.20 Time series
1.21 Time series: Men weekly earnings over the five years. Time series: Women weekly earnings over
the five years.
1.22 Cross-sectional data: Men and women workers weekly earnings for any one particular year.
1.23 Cross-sectional: The number of 8x10, 11x14 and 13x19 prints sold over a particular year.
1.24 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.
1.25 Descriptive statistics, because it identifies a sample mean.
1.26 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.
An Introduction to Business Statistics 1-3
1.27 Inferential statistics, because it would not be feasible to get the credit card debt from every
graduate student in the country. These results would be based on a sample of the population used to make
an inference about the entire population.
1.28 Descriptive statistics, because we summarize reviewer scores without going into inference.
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1.29 Inferential statistics, because it would not be feasible to survey every American in the country.
These results are based on a sample of the population used to make an inference on the entire population.
1.30 Descriptive statistics, because this percentage represents the proportion of a specific group of
customers arriving before 6 PM and is not making an inference about the entire population of customers.
CHAPTER 2
Displaying Descriptive Statistics
2.1
a) 27 128 100 therefore use 7 classes.
b) 29 512 300 therefore use 9 classes.
c) 210 1, 024 1, 000 therefore use 10 classes.
a) 16-25, 26-35, 36-45, 46-55, 56-65, 66-75
b) 16 to under 26, 26 to under 36, 36 to under 46,
46 to under 56, 56 to under 66, 66 to under 76
2.3
Cumulative
Frequency Relative Relative
Frequency Frequency
Number
1 6 0.250 0.250
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