BTM8106-8-2 Jackson Even-Numbered Chapter Exercises
Even-numbered exercises analyzing business research techniques.
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BTM8106-8-2 1
Part I
BTM8106-8-2 JACKSON EVEN-NUMBERED CHAPTER EXERCISES (PP. 220-221).
2a. This is a one-tail test because the manufacturers of the toothpaste want to prove that their
new toothpaste prevents more cavities than other brands of toothpaste (their sample vs. the
general population.
2b. Ho: μcavities with toothpaste1 ≤ μ cavities in general population
Ha: μcavities with toothpaste1 > μ cavities in general population
2c. σx̅ = 1.12 / √60 = 1.12 / 7.745: = .144
z = 1.73 - 1.5 / .144 = .23 / .144: = 1.597
2d. ±1.645 (Jackson, p.205).
2e. No, it should not be rejected. If the p-value is large, (> .05) than the evidence against the null
hypothesis is small. The conclusion is that using the manufacturer’s toothpaste prevents more
cavities than their competitor’s toothpaste.
2f. σx̅ = 1.12 / √60 = 1.12 / 7.745: = .144
CI = 1.50 ± 1.96 x 1.12 / √60: = 1.50 ± 1.96 x .144: = 1.50 ± .2834
1.5 - .2834 = 1.2166, 1.5 + .2834 = 1.7834
4. He is more likely to make a Type I error.
6a. This is a two-tailed test.
6b. Ho: μclassical music listeners ≤ μ spatial ability in general population
Ha: μclassical music listeners > μ spatial ability in general population
6c. x̅ = 52 +59 + 63 + 65 + 58 + 55 + 62 + 63 + 53 + 59 + 57 + 61 + 60 + 59 / 14: = 59
(52 - 59)² / 14 - 1, + (59-59)² / 14 – 1: = 3.802
59 - 58 / 3.802 / √14 = 1 / 1.0161: .9841
Part I
BTM8106-8-2 JACKSON EVEN-NUMBERED CHAPTER EXERCISES (PP. 220-221).
2a. This is a one-tail test because the manufacturers of the toothpaste want to prove that their
new toothpaste prevents more cavities than other brands of toothpaste (their sample vs. the
general population.
2b. Ho: μcavities with toothpaste1 ≤ μ cavities in general population
Ha: μcavities with toothpaste1 > μ cavities in general population
2c. σx̅ = 1.12 / √60 = 1.12 / 7.745: = .144
z = 1.73 - 1.5 / .144 = .23 / .144: = 1.597
2d. ±1.645 (Jackson, p.205).
2e. No, it should not be rejected. If the p-value is large, (> .05) than the evidence against the null
hypothesis is small. The conclusion is that using the manufacturer’s toothpaste prevents more
cavities than their competitor’s toothpaste.
2f. σx̅ = 1.12 / √60 = 1.12 / 7.745: = .144
CI = 1.50 ± 1.96 x 1.12 / √60: = 1.50 ± 1.96 x .144: = 1.50 ± .2834
1.5 - .2834 = 1.2166, 1.5 + .2834 = 1.7834
4. He is more likely to make a Type I error.
6a. This is a two-tailed test.
6b. Ho: μclassical music listeners ≤ μ spatial ability in general population
Ha: μclassical music listeners > μ spatial ability in general population
6c. x̅ = 52 +59 + 63 + 65 + 58 + 55 + 62 + 63 + 53 + 59 + 57 + 61 + 60 + 59 / 14: = 59
(52 - 59)² / 14 - 1, + (59-59)² / 14 – 1: = 3.802
59 - 58 / 3.802 / √14 = 1 / 1.0161: .9841
BTM8106-8-2 2
6d. 2.1603
6e. No, it should not be rejected. The conclusion is that listeners of classical will score
differently a tests of spatial ability.
6f. 59 ± 2.1603 x 3.8028 / √14 = 59 ± 2.1956: 56.8044 ≤ μ ≤ 61.956
8a. 1.0423
8b. 1
8c. 3.8415
8d. Fail reject the null hypothesis. People in California is greater than the national exercise rate.
What are degrees of freedom? How are the calculated?
They are the number of scores in a sample that are free to vary. Degrees of freedom in an
equation is vital since the number of degrees lets us know how many values in the final
calculation are allowed to vary. Since statistics attempts to be as precise as possible, the degrees
of freedom calculation is done often and contributes to the validity of the outcome (Lawrence,
2015). There is no general rule for determining the degrees of freedom that applies to every
inference problem. However, these are the general considerations used in determining the
degrees of freedom: type of statistical test needed to run; number of independent variables in the
population or sample; and the critical values for the equation using a critical value table.
What do inferential statistics allow you to infer?
They allow researchers to draw conclusions about a population based on data collected from
a sample. According to Cozby and Bates (2012) they are used to determine whether the results of
an experiment would match the results of repeated experiments using multiple samples;
“inferring that the difference in sample means reflects a true difference in the population means”
(p. 263).
6d. 2.1603
6e. No, it should not be rejected. The conclusion is that listeners of classical will score
differently a tests of spatial ability.
6f. 59 ± 2.1603 x 3.8028 / √14 = 59 ± 2.1956: 56.8044 ≤ μ ≤ 61.956
8a. 1.0423
8b. 1
8c. 3.8415
8d. Fail reject the null hypothesis. People in California is greater than the national exercise rate.
What are degrees of freedom? How are the calculated?
They are the number of scores in a sample that are free to vary. Degrees of freedom in an
equation is vital since the number of degrees lets us know how many values in the final
calculation are allowed to vary. Since statistics attempts to be as precise as possible, the degrees
of freedom calculation is done often and contributes to the validity of the outcome (Lawrence,
2015). There is no general rule for determining the degrees of freedom that applies to every
inference problem. However, these are the general considerations used in determining the
degrees of freedom: type of statistical test needed to run; number of independent variables in the
population or sample; and the critical values for the equation using a critical value table.
What do inferential statistics allow you to infer?
They allow researchers to draw conclusions about a population based on data collected from
a sample. According to Cozby and Bates (2012) they are used to determine whether the results of
an experiment would match the results of repeated experiments using multiple samples;
“inferring that the difference in sample means reflects a true difference in the population means”
(p. 263).
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Document Details
University
Northcentral University
Subject
Business Management