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ElenaW
19 days ago
6

1. The following are the number of hours that 10 police officers have spent being trained in how to handle encounters with peopl

e who are mentally ill:
4 17 12 9 6 10 1 5 9 3

Calculate the (a) range, (b) inter-quartile range, (c) variance, and (d) standard deviation.
(Use N)
Mathematics
1 answer:
zzz [12.3K]19 days ago
4 0

Answer:

Range = 16

Inter\ Quartile\ Range = 6.75

Variance = 20.44

Standard\ Deviation = 4.52

Step-by-step explanation:

Provided

4, 17, 12, 9, 6, 10, 1, 5, 9, 3

Calculating the range;

Range = Highest - Lowest

From the data provided;

The highest value is 17 and the lowest is 1

Thus;

Range = 17 - 1

Range = 16

Calculating the inter-quartile range

The inter-quartile range (IQR) is computed as follows

IQR = Q_3 - Q_1

Where

Q3 = Upper Quartile and Q1 = Lower Quartile

Start by sorting the data in ascending order

1, 3, 4, 5, 6, 9, 9, 10, 12, 17

N = Total data points; N = 10

---------------------------------------------------------------------------------

Calculating Q3

Q_3 = \frac{3}{4}(N+1) th\ item

Substituting 10 for N

Q_3 = \frac{3}{4}(10+1) th\ item

Q_3 = \frac{3}{4}(11) th\ item

Expressing 8.25 as 8 + 0.25Q_3 = \frac{33}{4} th\ item

Q_3 = 8.25 th\ item

Converting 0.25 into fractions

Q_3 = (8 + 0.25) th\ item

Q_3 = 8th\ item + 0.25 th\ item

From the ordered dataset;

Q_3 = 8th\ item +\frac{1}{4} th\ item and

Q_3 = 8th\ item +\frac{1}{4} (9th\ item - 8th\ item)

8th\ item = 109th\ item = 12

Q_3 = 8th\ item +\frac{1}{4} (9th\ item - 8th\ item)

Q_3 = 10 +\frac{1}{4} (12 - 10)

Q_3 = 10 +\frac{1}{4} (2)

Q_3 = 10 +0.5

Q_3 = 10.5

Calculating Q1

Substituting 10 for N

Q_1 = \frac{1}{4}(N+1) th\ item

Expressing 2.75 as 2 + 0.75

Q_1 = \frac{1}{4}(10+1) th\ item

Q_1 = \frac{1}{4}(11) th\ item

Q_1 = \frac{11}{4} th\ item

Q_1 = 2.75 th\ item

Converting 0.75 into fractions

Q_1 = (2 + 0.75) th\ item

Q_1 = 2nd\ item + 0.75 th\ item

From the arranged dataset;

and Q_1 = 2nd\ item +\frac{3}{4} th\ item

Q_1 = 2nd\ item +\frac{3}{4} (3rd\ item - 2nd\ item)

2nd\ item = 33rd\ item = 4

Q_1 = 3 +\frac{3}{4} (4 - 3)

Q_1 = 3 +\frac{3}{4} (1)

Q_1 = 3 +0.75

Q_1 = 3.75

---------------------------------------------------------------------------------

Remember that

IQR = Q_3 - Q_1

IQR = 10.5 - 3.75

IQR = 6.75

Calculating Variance

Begin by determining the mean

Mean = \frac{1+3+4+5+6+9+9+10+12+17}{10}

Mean = \frac{76}{10}

Mean = 7.6

Then subtract the mean from each value and square the differences

(1 - 7.6)^2 = (-6.6)^2 = 43.56

(3 - 7.6)^2 = (-4.6)^2 = 21.16

(4 - 7.6)^2 = (-3.6)^2 = 12.96

(5 - 7.6)^2 = (-2.6)^2 = 6.76

(6 - 7.6)^2 = (-1.6)^2 = 2.56

(9 - 7.6)^2 = (1.4)^2 = 1.96

(9 - 7.6)^2 = (1.4)^2 = 1.96

(10 - 7.6)^2 = (2.4)^2 = 5.76

(12 - 7.6)^2 = (4.4)^2 = 19.36

(17 - 7.6)^2 = (9.4)^2 = 88.36

Sum up the squared results

43.56 + 21.16 + 12.96 + 6.76 + 2.56 + 1.96 + 1.96 + 5.76 + 19.36 + 88.36 = 204.4

Then divide that sum by the total number of observations;

Variance = \frac{204.4}{10}

Variance = 20.44

Calculating Standard Deviation (SD)

SD = \sqrt{Variance}

SD = \sqrt{20.44}

SD = 4.52 (Approximated)

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The correlation coefficient is a measure that quantifies the strength of the relationship between two variable movements, denoted as r and ranging between -1 and 1.

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n=110, \sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9, sum y^2_i=\sum(y-\bar y)^2 =94228.8

\sum Y_i =17375, \sum X_i = 7665.5

Part a

The slope can be calculated using this formula:

\hat \beta_1 =\frac{\sum (x-\bar x) (y-\bar y)}{\sum (x-\bar x )^2}

Following the substitutions, we have:

\hat \beta_1 =\frac{7625.9}{1248.9}=6.106

The intercept can be determined with this formula:

\hat \beta_o = \bar y -\hat \beta_1 \bar x

Average values for x and y can be calculated this way:

\bar X=7665.5/110 =69.686, \bar y= 17375/110=157.955

Replacing yields:

\hat \beta_o = 157.955 -6.106 (69.686)=-267.548

Part b

The correlation coefficient can be calculated using the following formula:

r=\frac{\sum (x-\bar x)(y-\bar y) }{\sqrt{[\sum (x-\bar x)^2][\sum(y-\bar y)^2]}}

In our situation:

n=110, \sum x_i y_i = \sum (X-\bar X)(Y-\bar Y) =7625.9,\sum x^2_i=\sum (x-\bar x)^2 =1248.9, sum y^2_i=\sum(y-\bar y)^2 =94228.8

We can compute the correlation coefficient by substituting values:

r=\frac{7625.9}{\sqrt{[1248.9][94228.8]}}=0.657

The coefficient of determination is r^2 = 0.657^2 =0.432

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