College Athletes’ Weights In exercise 9.64 , you could reject the null hypothesis that the mean weights of soccer and baseball players were equal using a two-tailed test with a significance level of 0.05 . If you found a 95 % confidence interval for the difference between means, would it capture 0? Explain. If you found a 90 % interval, would it capture 0? Explain. Now go back to exercise 9.64 . Find a 95 % confidence interval for the difference between means, and explain what it shows.
College Athletes’ Weights In exercise 9.64 , you could reject the null hypothesis that the mean weights of soccer and baseball players were equal using a two-tailed test with a significance level of 0.05 . If you found a 95 % confidence interval for the difference between means, would it capture 0? Explain. If you found a 90 % interval, would it capture 0? Explain. Now go back to exercise 9.64 . Find a 95 % confidence interval for the difference between means, and explain what it shows.
Solution Summary: The author explains how to obtain the 95% confidence interval for the difference of means using the MINITAB software.
College Athletes’ Weights In exercise
9.64
, you could reject the null hypothesis that the mean weights of soccer and baseball players were equal using a two-tailed test with a significance level of
0.05
.
If you found a
95
%
confidence interval for the difference between means, would it capture 0? Explain.
If you found a
90
%
interval, would it capture 0? Explain.
Now go back to exercise
9.64
. Find a
95
%
confidence interval for the difference between means, and explain what it shows.
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
08:34
◄ Classroom
07:59
Probs. 5-32/33
D
ا.
89
5-34. Determine the horizontal and vertical components
of reaction at the pin A and the normal force at the smooth
peg B on the member.
A
0,4 m
0.4 m
Prob. 5-34
F=600 N
fr
th
ar
0.
163586
5-37. The wooden plank resting between the buildings
deflects slightly when it supports the 50-kg boy. This
deflection causes a triangular distribution of load at its ends.
having maximum intensities of w, and wg. Determine w
and wg. each measured in N/m. when the boy is standing
3 m from one end as shown. Neglect the mass of the plank.
0.45 m
3 m
Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp
Mean
Median
First Quartile (Q1)
Second Quartile (Q2)
Third Quartile (Q3)
Fourth Quartile (Q4)
10th Percentile
70th Percentile
Skewness
Kurtosis
Document Your Results:
In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command”
In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…
Examine the Variables: Carefully review and note the names of all variables in the dataset. Examples of these variables include:
Mileage (mpg)
Number of Cylinders (cyl)
Displacement (disp)
Horsepower (hp)
Research: Google to understand these variables.
Statistical Analysis: Select mpg variable, and perform the following statistical tests. Once you are done with these tests using mpg variable, repeat the same with hp
Mean
Median
First Quartile (Q1)
Second Quartile (Q2)
Third Quartile (Q3)
Fourth Quartile (Q4)
10th Percentile
70th Percentile
Skewness
Kurtosis
Document Your Results:
In RStudio: Before running each statistical test, provide a heading in the format shown at the bottom. “# Mean of mileage – Your name’s command”
In Microsoft Word: Once you've completed all tests, take a screenshot of your results in RStudio and paste it into a Microsoft Word document. Make sure that snapshots are very clear. You will need multiple snapshots. Also transfer these results to the…
Chapter 9 Solutions
The King's minion: Richelieu, Louis XIII, and the affair of Cinq-Mars
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.