Loose Leaf for Statistical Techniques in Business and Economics
Loose Leaf for Statistical Techniques in Business and Economics
17th Edition
ISBN: 9781260152647
Author: Douglas A. Lind
Publisher: McGraw-Hill Education
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Chapter 4, Problem 36CE

a.

To determine

Find the mean of the number of members per component.

Find the median of the number of members per component.

Find the standard deviation of the number of members per component.

a.

Expert Solution
Check Mark

Answer to Problem 36CE

The mean of the number of members per component is 348.5.

The median of the number of members per component is 276.

The standard deviation of the number of members per component is 277.4.

Explanation of Solution

Calculation:

Step by step procedure to obtain mean, median and standard deviation using MINITAB software is given as,

  • Choose Stat > Basic Statistics > Display Descriptive Statistics.
  • In Variables enter the columns Membership.
  • Choose option statistics, and select Mean, Median, Standard deviation.
  • Click OK.

Output using MINITAB software is given below:

Loose Leaf for Statistical Techniques in Business and Economics, Chapter 4, Problem 36CE , additional homework tip  1

Hence, mean of the number of members per component is 348.5, the median is 276 and the standard deviation is 277.4.

b.

To determine

Find the coefficient of skewness.

Identify the shape of the distribution of component size.

b.

Expert Solution
Check Mark

Answer to Problem 36CE

The coefficient of skewness is 1.17.

The shape of the distribution of component size is positive skewness.

Explanation of Solution

Calculation:

Step by step procedure to obtain skewness using MINITAB software is given as,

  • Choose Stat > Basic Statistics > Graphical Summary.
  • In Variables enter the columns Membership.
  • Click OK.

Output using MINITAB software is given below:

Loose Leaf for Statistical Techniques in Business and Economics, Chapter 4, Problem 36CE , additional homework tip  2

Hence, the value of coefficient of skewness is 1.17.

From the plot, it can be observed that most of the values are extended towards right indicating that distribution of component size is skewed to the right or positively skewed.

c.

To determine

Find the first quartile.

Find the third quartile.

c.

Expert Solution
Check Mark

Answer to Problem 36CE

The first quartile is 108.25.

The third quartile is 527.50.

Explanation of Solution

Calculation:

Location of percentile:

The formula for percentile is,

LP=(n+1)P100

In the formula, P denotes the location of the percentile and n denotes the total number of observations.

First quartile:

The first quartile represents the 25% of observation lies below first quartile. That is P=25. There are 40 observations in the dataset. Arrange the values in ascending order.

Substitute, P=25,n=40 in the percentile formula.

L25=(40+1)25100=41×25100=1,025100=10.25

The position of first quartile is 10.25th value in the dataset.

First quartile=10thvalue+(11thvalue10thvalue)0.25=106+(115106)0.25=106+2.25=108.25

Hence, the first quartile is 108.25.

Third quartile:

The third quartile represents the 75% of observation lies above third quartile. That is P=75.

Substitute, P=75,n=40 in the percentile formula.

L75=(40+1)75100=41×75100=3,075100=30.75

The position of third quartile is 30.75th value in the dataset.

Third quartile=30rdvalue+(31thvalue30rdvalue)0.75=517+(531517)0.75=517+10.5=527.50

Hence, the third quartile is 527.50.

d.

To determine

Construct a boxplot.

Identify whether there are outliers or not.

Find the components that are outliers.

Find the limits for outliers.

d.

Expert Solution
Check Mark

Answer to Problem 36CE

The boxplot is,

Loose Leaf for Statistical Techniques in Business and Economics, Chapter 4, Problem 36CE , additional homework tip  3

Yes, there are outliers.

The limits for outliers are (0; 1,156.375).

The component that is outlier is California.

Explanation of Solution

Calculation:

Step by step procedure to obtain boxplot using MINITAB software is given as,

  • Choose Graph > Boxplot.
  • In Graph variables enter the columns Membership.
  • Click OK.

In the boxplot, the outlier is represented using asterisk. In the boxplot of data set there is one asterisk representing outliers. Hence, there is one outlier in the dataset.

Limits for detecting outliers:

Any data value beyond the below points are considered as outliers.

Lowerpoint=Q11.5(Q3Q1)Upperpoint=Q3+1.5(Q3Q1)

Substitute, Q3=527.50,Q1=108.25 in the formula.

Lowerpoint=108.251.5(527.5108.25)=108.251.5(419.25)=108.25628.875=520.625

Since the membership cannot be negative, the lower point is considered as 0.

Upperpoint=527.5+1.5(527.5108.25)=527.5+1.5(419.25)=527.5+628.875=1,156.375

The points below 0 and above 1,156.375 are considered as outliers. Hence the limits for outliers are (0; 1,156.375).

The membership corresponding to state ‘California’ is 1,165, which is above the upper limit 1,156.375. This shows that, California is a component of outlier.

Hence, the component that is outlier is California.

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Chapter 4 Solutions

Loose Leaf for Statistical Techniques in Business and Economics

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