Warning: foreach() argument must be of type array|object, bool given in /var/www/html/web/app/themes/studypress-core-theme/template-parts/header/mobile-offcanvas.php on line 20

Ages of MoviegoersThe table below shows the distribution of the ages of moviegoers(based on data from the Motion Picture Association of America). Use the data to estimate themean, standard deviation, and variance of ages of moviegoers.Hint:For the open-ended categoryof “60 and older,” assume that the category is actually 60–80.

Age

2-11

12-17

18-24

25-39

40-49

50-59

60 and older

Percent

7

15

19

19

15

11

14

Short Answer

Expert verified

The value of the mean is equal to 35.17 years.

The value of the standard deviation is equal to 19.64 years.

The value of the variance is equal to 385.69 years.

Step by step solution

01

Given information

The distribution of the ages of moviegoers is provided.

02

Compute the midpoints

Consider the last class interval “60 and older” as 60-80.

The midpoint of a class interval has the following expression:

\({\rm{Midpoint}} = \frac{{{\rm{Lower}}\;{\rm{limit}} + {\rm{Upper}}\;{\rm{limit}}}}{2}\)

Thus, the midpoints of the class intervals are computed as shown:

Class Interval

Midpoint

2-11

\(\begin{array}{r}{\rm{Midpoint}} = \frac{{2 + 11}}{2}\\ = 6.5\end{array}\)

12-17

\(\begin{array}{c}{\rm{Midpoint}} = \frac{{12 + 17}}{2}\\ = 14.5\end{array}\)

18-24

\(\begin{array}{c}{\rm{Midpoint}} = \frac{{18 + 24}}{2}\\ = 21\end{array}\)

25-39

\(\begin{array}{c}{\rm{Midpoint}} = \frac{{25 + 39}}{2}\\ = 32\end{array}\)

40-49

\(\begin{array}{c}{\rm{Midpoint}} = \frac{{40 + 49}}{2}\\ = 44.5\end{array}\)

50-59

\(\begin{array}{c}{\rm{Midpoint}} = \frac{{50 + 59}}{2}\\ = 54.5\end{array}\)

60-80

\(\begin{array}{c}{\rm{Midpoint}} = \frac{{60 + 80}}{2}\\ = 70\end{array}\)

03

Calculate the mean

The following table shows the calculations required to compute the mean value:

Class Interval

f

Midpoint(x)

fx

2-11

7

6.5

45.5

12-17

15

14.5

217.5

18-24

19

21

399

25-39

19

32

608

40-49

15

44.5

667.5

50-59

11

54.5

599.5

60-80

14

70

980

\(\sum f = N = 100\)

\(\sum {x = 243} \)

\(\sum {fx = 3517} \)

Themean value is computed below:

\(\begin{array}{c}\bar x = \frac{{\sum\limits_{i = 1}^n {f{x_i}} }}{N}\\ = \frac{{3517}}{{100}}\\ = 35.17\end{array}\)

The mean value is equal to 35.17 years.

04

Calculate the standard deviation

The following table shows the computations necessary for calculating the standard deviation:

Class Interval

f

Midpoint(x)

fx

\({x^2}\)

\(f{x^2}\)

2-11

7

6.5

45.5

42.25

295.75

12-17

15

14.5

217.5

210.25

3153.75

18-24

19

21

399

441

8379

25-39

19

32

608

1024

19456

40-49

15

44.5

667.5

1980.25

29703.75

50-59

11

54.5

599.5

2970.25

32672.75

60-80

14

70

980

4900

68600

\(\sum f = N = 100\)

\(\sum {x = 243} \)

\(\sum {fx = 3517} \)

\(\sum {{x^2}} = 11568\)

\(\sum {f{x^2}} = 162261\)

The value of the standard deviation is computed below:

\(\begin{array}{c}\sigma = \sqrt {\frac{{\sum {f{x^2}} }}{N} - {{\left( {\frac{{\sum {fx} }}{N}} \right)}^2}} \\ = \sqrt {\frac{{162261}}{{100}} - {{\left( {\frac{{3517}}{{100}}} \right)}^2}} \\ = 19.64\end{array}\)

Therefore, the standard deviation is equal to 19.64 years.

05

Calculate the variance

The variance is computed as follows:

\(\begin{array}{c}{\sigma ^2} = \frac{{\sum {f{x^2}} }}{N} - {\left( {\frac{{\sum {fx} }}{N}} \right)^2}\\ = \frac{{162261}}{{100}} - {\left( {\frac{{3517}}{{100}}} \right)^2}\\ = 385.69\end{array}\)

The value of the variance is equal to 385.69 years squared.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Testing for a Linear Correlation. In Exercises 13–28, construct a scatterplot, and find the value of the linear correlation coefficient r. Also find the P-value or the critical values of r from Table A-6. Use a significance level of A = 0.05. Determine whether there is sufficient evidence to support a claim of a linear correlation between the two variables. (Save your work because the same data sets will be used in Section 10-2 exercises.)

Sports Diameters (cm), circumferences (cm), and volumes (cm3) from balls used in different sports are listed in the table below. Is there sufficient evidence to conclude that there is a linear correlation between diameters and circumferences? Does the scatterplot confirm a linear association?


Diameter

Circumference

Volume

Baseball

7.4

23.2

212.2

Basketball

23.9

75.1

7148.1

Golf

4.3

13.5

41.6

Soccer

21.8

68.5

5424.6

Tennis

7

22

179.6

Ping-Pong

4

12.6

33.5

Volleyball

20.9

65.7

4780.1

Softball

9.7

30.5

477.9

Scatterplots Match these values of r with the five scatterplots shown below: 0.268, 0.992, -1, 0.746, and 1.

Stocks and Sunspots. Listed below are annual high values of the Dow Jones Industrial Average (DJIA) and annual mean sunspot numbers for eight recent years. Use the data for Exercises 1–5. A sunspot number is a measure of sunspots or groups of sunspots on the surface of the sun. The DJIA is a commonly used index that is a weighted mean calculated from different stock values.

DJIA

14,198

13,338

10,606

11,625

12,929

13,589

16,577

18,054

Sunspot

Number

7.5

2.9

3.1

16.5

55.7

57.6

64.7

79.3

Hypothesis Test The mean sunspot number for the past three centuries is 49.7. Use a 0.05 significance level to test the claim that the eight listed sunspot numbers are from a population with a mean equal to 49.7.

Interpreting a Computer Display. In Exercises 9–12, refer to the display obtained by using the paired data consisting of Florida registered boats (tens of thousands) and numbers of manatee deaths from encounters with boats in Florida for different recent years (from Data Set 10 in Appendix B). Along with the paired boat, manatee sample data, Stat Crunch was also given the value of 85 (tens of thousands) boats to be used for predicting manatee fatalities.


Testing for Correlation Use the information provided in the display to determine the value of the linear correlation coefficient. Is there sufficient evidence to support a claim of a linear correlation between numbers of registered boats and numbers of manatee deaths from encounters with boats?

What is the relationship between the linear correlation coefficient rand the slope\({b_1}\)of a regression line?

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free