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A study of the relationship between age and variousvisual functions (such as acuity and depth perception)reported the following observations on the area of sclerallamina (\({\bf{m}}{{\bf{m}}^2}\)) from human optic nerve heads(鈥淢orphometry of Nerve Fiber Bundle Pores in theOptic Nerve Head of the Human,鈥 Experimental EyeResearch, 1988: 559鈥568):

2.75 2.62 2.74 3.85 2.34 2.74 3.93 4.21 3.88

4.33 3.46 4.52 2.43 3.65 2.78 3.56 3.01

a. Calculate \(\sum {{x_i}} \)and \(\sum {x_i^2} \).

b. Use the values calculated in part (a) to compute the sample variance s2 and then the sample standard deviation s.

Short Answer

Expert verified

a.\(\sum {{x_i}} = 56.8\;m{m^2}\)and\(\sum {x_i^2} = 197.804\;m{m^2}\;square\).

b. The sample variance is 0.5016 \({\rm{m}}{{\rm{m}}^{\rm{2}}}\) square. The sample standard deviation is 0.708 \({\rm{m}}{{\rm{m}}^{\rm{2}}}\).

Step by step solution

01

 Step 1: Given information

The data is provided as,

2.75

2.62

2.74

3.85

2.34

2.74

3.93

4.21

3.88

4.33

3.46

4.52

2.43

3.65

2.78

3.56

3.01


The size of the sample is 17.

02

Compute \(\sum {{x_i}} \) and \(\sum {x_i^2} \)

a.

Let x represents the sample values.

The symbol \(\sum {} \)shows the summation of a range of values.

The table representing the calculations are as follows,

S.No

\({x_i}\)

\(x_i^2\)

1

2.75

7.5625

2

2.62

6.8644

3

2.74

7.5076

4

3.85

14.8225

5

2.34

5.4756

6

2.74

7.5076

7

3.93

15.4449

8

4.21

17.7241

9

3.88

15.0544

10

4.33

18.7489

11

3.46

11.9716

12

4.52

20.4304

13

2.43

5.9049

14

3.65

13.3225

15

2.78

7.7284

16

3.56

12.6736

17

3.01

9.0601

Therefore, the values are,

\(\begin{array}{c}\sum {{x_i}} &=& 2.75 + 2.62 + ... + 3.01\\ &=& 56.8\\\sum {x_i^2} &=& {2.75^2} + {2.62^2} + ... + {3.01^2}\\ &=& 197.804\end{array}\)

Therefore, \(\sum {{x_i}} = 56.8\;m{m^2}\) and \(\sum {x_i^2} = 197.804\;m{m^2}\;square\)

03

Compute the sample variance and sample standard deviation

b.

Referring to part a, the values are,

\(\sum {{x_i}} = 56.8\)and\(\sum {x_i^2} = 197.804\)

The sample variance is given as,

\({s^2} = \frac{{{S_{xx}}}}{{n - 1}}\)

Where,

\({S_{xx}} = \sum {x_i^2} - \frac{{{{\left( {\sum {{x_i}} } \right)}^2}}}{n}\)

The sample variance is computed as,

\(\begin{array}{c}{s^2} &=& \frac{{{S_{xx}}}}{{n - 1}}\\ &=& \frac{{197.804 - \frac{{{{\left( {56.8} \right)}^2}}}{{17}}}}{{17 - 1}}\\ &=& 0.5016\end{array}\)

Therefore, the sample variance is 0.5016\(m{m^2}\;square\).

The sample standard deviation is computed as,

\(\begin{array}{c}s &=& \sqrt {{s^2}} \\ &=& \sqrt {0.5016} \\ &=& 0.708\end{array}\)

Therefore, the sample standard deviation is 0.708\(m{m^2}\).

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Most popular questions from this chapter

Many universities and colleges have instituted supplemental

instruction (SI) programs, in which a student facilitator meets regularly with a small group of students enrolled in the course to promote discussion of course material and enhance subject mastery. Suppose that students in a large statistics course (what else?) are randomly divided into a control group that will not participate in SI and a treatment group that will participate. At the end of the term, each student鈥檚 total score in the course is determined.

a. Are the scores from the SI group a sample from an existing population? If so, what is it? If not, what is the relevant conceptual population?

b. What do you think is the advantage of randomly dividing the students into the two groups rather than letting each student choose which group to join?

c. Why didn鈥檛 the investigators put all students in the treatment group? [Note:The article 鈥淪upplemental Instruction: An Effective Component of Student Affairs Programming鈥 (J. of College Student Devel., 1997: 577鈥586) discusses the analysis of data from several SI programs.]

For each of the following hypothetical populations, give

a plausible sample of size 4:

a. All distances that might result when you throw a football

b. Page lengths of books published 5 years from now

c. All possible earthquake-strength measurements (Richter scale) that might be recorded in California during the next year

d. All possible yields (in grams) from a certain chemical reaction carried out in a laboratory.

The article 鈥淎 Thin-Film Oxygen Uptake Test for the Evaluation of Automotive Crankcase Lubricants鈥 (Lubric. Engr., 1984: 75鈥83) reportedthe following data on oxidation-induction time (min) for various commercial oils:

87 103 130 160 180 195 132 145 211 105 145

153 152 138 87 99 93 119 129

a. Calculate the sample variance and standard deviation.

b. If the observations were re expressed in hours, what would be the resulting values of the sample variance and sample standard deviation? Answer without actually performing the re expression

A sample of 26 offshore oil workers took part in a simulated escape exercise, resulting in the accompanying data on time (sec) to complete the escape (鈥淥xygen Consumption and Ventilation During Escape from an Offshore Platform,鈥 Ergonomics, 1997: 281鈥292):

389 356 359 363 375 424 325 394 402

373 373 370 364 366 364 325 339 393

392 369 374 359 356 403 334 397

a. Construct a stem-and-leaf display of the data. How does it suggest that the sample mean and median will compare?

b. Calculate the values of the sample mean and median.(Hint:\(\sum {{x_i} = } \)9638.)

c. By how much could the largest time, currently 424, be increased without affecting the value of the sample median? By how much could this value be decreased without affecting the value of the sample median?

d. What are the values of \(\bar x\)and \(\tilde x\), when the observations are re expressed in minutes?

Grip is applied to produce normal surface forces that compress the object being gripped. Examples include two people shaking hands, or a nurse squeezing a patient鈥檚 forearm to stop bleeding. The article 鈥淚nvestigation of Grip Force, Normal Force, Contact Area, Hand Size, and Handle Size for Cylindrical Handles鈥 (Human Factors, 2008: 734鈥744) included the following data on grip strength (N) for a sample of 42

individuals:

16 18 18 26 33 41 54 56 66 68 87 91 95

98 106 109 111 118 127 127 135 145 147 149 151 168

172 183 189 190 200 210 220 229 230 233 238 244 259

294 329 403

a. Construct a stem-and-leaf display based on repeating each stem value twice, and comment on interesting features.

b. Determine the values of the fourths and the fourth spread.

c. Construct a boxplot based on the five-number summary, and comment on its features.

d. How large or small does an observation have to be to qualify as an outlier? An extreme outlier? Are there any outliers?

e. By how much could the observation 403, currently the largest, be decreased without affecting\({f_s}\)?

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