/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 7 The Thomas Supply Company Inc. i... [FREE SOLUTION] | 91Ó°ÊÓ

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The Thomas Supply Company Inc. is a distributor of gas-powered generators. As with any business, the length of time customers take to pay their invoices is important. Listed below, arranged from smallest to largest, is the time, in days, for a sample of the Thomas Supply Company Inc. invoices. $$ \begin{array}{|lllllllllllllll|} \hline 13 & 13 & 13 & 20 & 26 & 27 & 31 & 34 & 34 & 34 & 35 & 35 & 36 & 37 & 38 \\ 41 & 41 & 41 & 45 & 47 & 47 & 47 & 50 & 51 & 53 & 54 & 56 & 62 & 67 & 82 \\ \hline \end{array} $$ a. Determine the first and third quartiles. b. Determine the second decile and the eighth decile. c. Determine the 6 7th percentile.

Short Answer

Expert verified
Q1: 33.25, Q3: 50.25; D2: 27.8, D8: 52.6; 67th percentile: 47.

Step by step solution

01

Calculate the First (Q1) and Third Quartiles (Q3)

Since the data set is already sorted in ascending order, we need to find the positions of the first and third quartiles using the positions given by \( Q_1 = \frac{n+1}{4} \) and \( Q_3 = \frac{3(n+1)}{4} \), where \( n \) is the number of observations.The number of observations \( n \) is 30.To find the first quartile (\( Q_1 \)), calculate:\[ Q_1 = \frac{30+1}{4} = 7.75 \]The position is 7.75, indicating \( Q_1 \) is between the 7th and 8th values in the list (31 and 34 respectively). The value of \( Q_1 \) is calculated as:\[ Q_1 = 31 + 0.75(34 - 31) = 33.25 \]To find the third quartile (\( Q_3 \)), calculate:\[ Q_3 = \frac{3(30+1)}{4} = 23.25 \]The position is 23.25, indicating \( Q_3 \) is between the 23rd and 24th values in the list (50 and 51 respectively). The value of \( Q_3 \) is calculated as:\[ Q_3 = 50 + 0.25(51 - 50) = 50.25 \]
02

Calculate the Second and Eighth Deciles

Deciles divide the data set into ten equal parts. The positions for the second and eighth decile are given by:For the second decile (\(D_2\)), \[ D_2 = \frac{2(n+1)}{10} = \frac{2(30+1)}{10} = 6.2 \]The position is 6.2. The 6th and 7th values in the list are 27 and 31 respectively. So:\[ D_2 = 27 + 0.2(31 - 27) = 27.8 \]For the eighth decile (\(D_8\)), \[ D_8 = \frac{8(n+1)}{10} = \frac{8(30+1)}{10} = 24.8 \]The position is 24.8. The 24th and 25th values in the list are 51 and 53 respectively. So:\[ D_8 = 51 + 0.8(53 - 51) = 52.6 \]
03

Calculate the 67th Percentile

Percentiles divide the data into 100 equal parts. For the 67th percentile, the position is given by:\[ P_{67} = \frac{67(n+1)}{100} = \frac{67(30+1)}{100} = 20.77 \]This position suggests the 20th and 21st items, which are both 47. Thus, the 67th percentile value is simply 47.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

First Quartile (Q1)
The concept of the First Quartile, often abbreviated as Q1, is fundamental in statistics. It is the point that marks the first 25% of a dataset when arranged in ascending order. This means it separates the lowest quarter of data from the rest. To determine the position of Q1, apply the formula: \[ Q_1 = \frac{n+1}{4}, \]where \( n \) is the total number of observations.
For example, if you have a dataset with 30 entries, calculating \( Q_1 \) helps identify the value that falls between the 7th and 8th position. To find the precise value of Q1 between these two data points, interpolate using their values. In our dataset, this leads to finding that Q1 equals approximately 33.25.
This indicates that 25% of the data points in the list are less than or equal to 33.25 days.
Third Quartile (Q3)
The Third Quartile, denoted as Q3, plays an important role in illustrating the spread of data in the upper end. It divides the lowest 75% from the top 25% of data values. Use the formula: \[ Q_3 = \frac{3(n+1)}{4}, \]to find its position.
In a dataset of 30 elements, as in our case, the position of Q3 falls around the 23.25th point, necessitating interpolation between the data points at the 23rd and 24th positions. For our example, Q3 is calculated to be around 50.25.
This means that 75% of the invoices take 50.25 days or less to be paid, providing insight into how laggard payments are distributed.
Deciles
Deciles are another method to divide your dataset into equal parts, specifically into ten parts, and help understand the distribution in finer detail. Each decile indicates 10% of the data span. Unlike quartiles which split data into quarters, deciles offer a more granular view.
  • The second decile, \( D_2 \), represents the 20th percentile. For our data, \( D_2 \) falls at position 6.2, meaning it's between the 6th and 7th values, which are 27 and 31. Interpolating gives \( D_2 \approx 27.8 \).
  • Meanwhile, the eighth decile, \( D_8 \), is equivalent to the 80th percentile. This falls at the 24.8 position, placing it between the 24th (51) and 25th (53) items. Hence, \( D_8 \approx 52.6 \).
These deciles shed light on distribution, highlighting where 20% and 80% of the data sets lie, enhancing our understanding of payment patterns.

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Most popular questions from this chapter

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