Skip to content Skip to navigation Skip to collection information

OpenStax_CNX

You are here: Home » Content » Elementary Statistics » Confidence Interval for a Population Proportion

Navigation

Table of Contents

Lenses

What is a lens?

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

This content is ...

Endorsed by Endorsed (What does "Endorsed by" mean?)

This content has been endorsed by the organizations listed. Click each link for a list of all content endorsed by the organization.
  • College Open Textbooks display tagshide tags

    This module is included inLens: Community College Open Textbook Collaborative
    By: CC Open Textbook CollaborativeAs a part of collection: "Collaborative Statistics"

    Comments:

    "Reviewer's Comments: 'I recommend this book. Overall, the chapters are very readable and the material presented is consistent and appropriate for the course. A wide range of exercises introduces […]"

    Click the "College Open Textbooks" link to see all content they endorse.

    Click the tag icon tag icon to display tags associated with this content.

  • JVLA Endorsed

    This module is included inLens: Jesuit Virtual Learning Academy Endorsed Material
    By: Jesuit Virtual Learning AcademyAs a part of collection: "Collaborative Statistics"

    Comments:

    "This is a robust collection (textbook) approved by the College Board as a resource for the teaching of AP Statistics. "

    Click the "JVLA Endorsed" link to see all content they endorse.

  • WebAssign display tagshide tags

    This module is included inLens: WebAssign The Independent Online Homework and Assessment Solution
    By: WebAssignAs a part of collection: "Collaborative Statistics"

    Comments:

    "Online homework and assessment available from WebAssign."

    Click the "WebAssign" link to see all content they endorse.

    Click the tag icon tag icon to display tags associated with this content.

Affiliated with (What does "Affiliated with" mean?)

This content is either by members of the organizations listed or about topics related to the organizations listed. Click each link to see a list of all content affiliated with the organization.
  • OrangeGrove display tagshide tags

    This module is included inLens: Florida Orange Grove Textbooks
    By: Florida Orange GroveAs a part of collection: "Collaborative Statistics"

    Click the "OrangeGrove" link to see all content affiliated with them.

    Click the tag icon tag icon to display tags associated with this content.

  • Bookshare

    This module is included inLens: Bookshare's Lens
    By: Bookshare - A Benetech InitiativeAs a part of collection: "Collaborative Statistics"

    Comments:

    "DAISY and BRF versions of this collection are available."

    Click the "Bookshare" link to see all content affiliated with them.

  • Featured Content display tagshide tags

    This module is included inLens: Connexions Featured Content
    By: ConnexionsAs a part of collection: "Collaborative Statistics"

    Comments:

    "Collaborative Statistics was written by two faculty members at De Anza College in Cupertino, California. This book is intended for introductory statistics courses being taken by students at two- […]"

    Click the "Featured Content" link to see all content affiliated with them.

    Click the tag icon tag icon to display tags associated with this content.

Also in these lenses

  • statistics display tagshide tags

    This module is included inLens: Statistics
    By: Brylie OxleyAs a part of collection: "Collaborative Statistics"

    Click the "statistics" link to see all content selected in this lens.

    Click the tag icon tag icon to display tags associated with this content.

  • Lucy Van Pelt display tagshide tags

    This module is included inLens: Lucy's Lens
    By: Tahiya MaromeAs a part of collection: "Collaborative Statistics"

    Comments:

    "Part of the Books featured on Community College Open Textbook Project"

    Click the "Lucy Van Pelt" link to see all content selected in this lens.

    Click the tag icon tag icon to display tags associated with this content.

  • Educational Technology Lens display tagshide tags

    This module is included inLens: Educational Technology
    By: Steve WilhiteAs a part of collection: "Collaborative Statistics"

    Click the "Educational Technology Lens" link to see all content selected in this lens.

    Click the tag icon tag icon to display tags associated with this content.

  • Statistics

    This module is included inLens: Mathieu Plourde's Lens
    By: Mathieu PlourdeAs a part of collection: "Collaborative Statistics"

    Click the "Statistics" link to see all content selected in this lens.

  • statf12

    This module is included inLens: Statistics Fall 2012
    By: Alex KolesnikAs a part of collection: "Collaborative Statistics"

    Click the "statf12" link to see all content selected in this lens.

  • UTEP display tagshide tags

    This module is included inLens: Amy Wagler's Lens
    By: Amy WaglerAs a part of collection: "Collaborative Statistics"

    Click the "UTEP" link to see all content selected in this lens.

    Click the tag icon tag icon to display tags associated with this content.

  • Make Textbooks Affordable

    This module is included inLens: Make Textbooks Affordable
    By: Nicole AllenAs a part of collection: "Collaborative Statistics"

    Click the "Make Textbooks Affordable" link to see all content selected in this lens.

  • BUS204 Homework display tagshide tags

    This module is included inLens: Saylor BUS 204 Homework
    By: David BourgeoisAs a part of collection: "Collaborative Statistics"

    Comments:

    "Homework for Discrete Variables/Probability. "

    Click the "BUS204 Homework" link to see all content selected in this lens.

    Click the tag icon tag icon to display tags associated with this content.

  • crowe

    This module is included in aLens by: Chris RoweAs a part of collection: "Collaborative Statistics"

    Click the "crowe" link to see all content selected in this lens.

  • Bio 502 at CSUDH display tagshide tags

    This module is included inLens: Bio 502
    By: Terrence McGlynnAs a part of collection: "Collaborative Statistics"

    Comments:

    "This is the course textbook for Biology 502 at CSU Dominguez Hills"

    Click the "Bio 502 at CSUDH" link to see all content selected in this lens.

    Click the tag icon tag icon to display tags associated with this content.

Recently Viewed

This feature requires Javascript to be enabled.

Tags

(What is a tag?)

These tags come from the endorsement, affiliation, and other lenses that include this content.
 

Confidence Interval for a Population Proportion

Module by: Susan Dean, Barbara Illowsky, Ph.D.. E-mail the authors

Summary: Confidence Interval for a Population Proportion is part of the collection col10555 written by Barbara Illowsky and Susan Dean with contributions from Roberta Bloom.

During an election year, we see articles in the newspaper that state confidence intervals in terms of proportions or percentages. For example, a poll for a particular candidate running for president might show that the candidate has 40% of the vote within 3 percentage points. Often, election polls are calculated with 95% confidence. So, the pollsters would be 95% confident that the true proportion of voters who favored the candidate would be between 0.37 and 0.43 : ( 0.40 - 0.03 , 0.40 + 0.03 ) (0.40-0.03,0.40+0.03).

Investors in the stock market are interested in the true proportion of stocks that go up and down each week. Businesses that sell personal computers are interested in the proportion of households in the United States that own personal computers. Confidence intervals can be calculated for the true proportion of stocks that go up or down each week and for the true proportion of households in the United States that own personal computers.

The procedure to find the confidence interval, the sample size, the error bound, and the confidence level for a proportion is similar to that for the population mean. The formulas are different.

How do you know you are dealing with a proportion problem? First, the underlying distribution is binomial. (There is no mention of a mean or average.) If XX is a binomial random variable, then X~B(n,p) X~B(n,p) where nn = the number of trials and pp = the probability of a success. To form a proportion, take XX, the random variable for the number of successes and divide it by nn, the number of trials (or the sample size). The random variable P'P' (read "P prime") is that proportion,

P'=XnP'=Xn

(Sometimes the random variable is denoted as P̂P̂, read "P hat".)

When nn is large and p is not close to 0 or 1, we can use the normal distribution to approximate the binomial.

XX ~ N ( n p , n p q ) N(np, n p q )

If we divide the random variable by nn, the mean by nn, and the standard deviation by nn, we get a normal distribution of proportions with P'P', called the estimated proportion, as the random variable. (Recall that a proportion = the number of successes divided by nn.)

X n = P' X n =P' ~ N ( n p n , n p q n ) N( n p n , n p q n )

Using algebra to simplify : n p q n = p q n n p q n = p q n

P'P' follows a normal distribution for proportions: P' P' ~ N ( p , p q n ) N(p, p q n )

The confidence interval has the form (p'-EBP,p'+EBP)(p'-EBP,p'+EBP).

p' = x n p'= x n

p' p' = the estimated proportion of successes (p'p' is a point estimate for pp, the true proportion)

xx = the number of successes.

nn = the size of the sample

The error bound for a proportion is

EBP = z α 2 p' q' n EBP= z α 2 p' q' n where q' = 1 - p' whereq'=1-p'

This formula is similar to the error bound formula for a mean, except that the "appropriate standard deviation" is different. For a mean, when the population standard deviation is known, the appropriate standard deviation that we use is σ n σ n . For a proportion, the appropriate standard deviation is p q n p q n .

However, in the error bound formula, we use p ' q ' n p ' q ' n as the standard deviation, instead of p q n p q n

However, in the error bound formula, the standard deviation is p ' q ' n p ' q ' n .

In the error bound formula, the sample proportions p'p' and q'q' are estimates of the unknown population proportions pp and qq. The estimated proportions p'p' and q'q' are used because pp and qq are not known. p'p' and q'q' are calculated from the data. p'p' is the estimated proportion of successes. q'q' is the estimated proportion of failures.

The confidence interval can only be used if the number of successes np'np' and the number of failures nq'nq' are both larger than 5.

Note:

For the normal distribution of proportions, the z-score formula is as follows.

If P 'P' ~ N ( p , p q n ) N(p, p q n ) then the z-score formula is z = p ' - p p q n z= p ' - p p q n

Example 1

Problem 1

Suppose that a market research firm is hired to estimate the percent of adults living in a large city who have cell phones. 500 randomly selected adult residents in this city are surveyed to determine whether they have cell phones. Of the 500 people surveyed, 421 responded yes - they own cell phones. Using a 95% confidence level, compute a confidence interval estimate for the true proportion of adults residents of this city who have cell phones.

Solution

  • You can use technology to directly calculate the confidence interval.
  • The first solution is step-by-step (Solution A).
  • The second solution uses a function of the TI-83, 83+ or 84 calculators (Solution B).

Solution A

Let XX = the number of people in the sample who have cell phones. XX is binomial. XX ~ B(500, 421500)B(500,421500).

To calculate the confidence interval, you must find p'p', q'q', and EBPEBP.

n = 500 x n=500x = the number of successes = 421 =421

p ' = x n = 421 500 = 0.842 p'= x n = 421 500 =0.842

p ' = 0.842 p'=0.842 is the sample proportion; this is the point estimate of the population proportion.

q ' = 1 - p ' = 1 - 0.842 = 0.158 q'=1-p'=1-0.842=0.158

Since CL = 0.95 CL=0.95, then α = 1 - CL = 1 - 0.95 = 0.05 α 2 = 0.025 α=1-CL=1-0.95=0.05 α 2 =0.025.

Then z α 2 = z .025 = 1.96 z α 2 = z .025 =1.96

Use the TI-83, 83+ or 84+ calculator command invNorm(0.975,0,1) to find z.025 z.025. Remember that the area to the right of z.025 z.025 is 0.025 and the area to the left of z0.025 z0.025 is 0.975. This can also be found using appropriate commands on other calculators, using a computer, or using a Standard Normal probability table.

EBP = z α 2 p ' q ' n = 1.96 ( 0.842 ) ( 0.158 ) 500 = 0.032 EBP= z α 2 p ' q ' n =1.96 ( 0.842 ) ( 0.158 ) 500 =0.032

p ' - EBP = 0.842 - 0.032 = 0.81 p'-EBP=0.842-0.032=0.81

p ' + EBP = 0.842 + 0.032 = 0.874 p'+EBP=0.842+0.032=0.874

The confidence interval for the true binomial population proportion is (p'-EBP,p'+EBP) =(p'-EBP,p'+EBP)=(0.810,0.874)(0.810,0.874).

Interpretation

We estimate with 95% confidence that between 81% and 87.4% of all adult residents of this city have cell phones.

Explanation of 95% Confidence Level

95% of the confidence intervals constructed in this way would contain the true value for the population proportion of all adult residents of this city who have cell phones.

Solution B

Using a function of the TI-83, 83+ or 84 calculators:


Press STAT and arrow over to TESTS.
Arrow down to A:1-PropZint. Press ENTER.
Arrow down to xx and enter 421.
Arrow down to nn and enter 500.
Arrow down to C-Level and enter .95.
Arrow down to Calculate and press ENTER.
The confidence interval is (0.81003, 0.87397).

Example 2

Problem 1

For a class project, a political science student at a large university wants to estimate the percent of students that are registered voters. He surveys 500 students and finds that 300 are registered voters. Compute a 90% confidence interval for the true percent of students that are registered voters and interpret the confidence interval.

Solution

  • You can use technology to directly calculate the confidence interval.
  • The first solution is step-by-step (Solution A).
  • The second solution uses a function of the TI-83, 83+ or 84 calculators (Solution B).
Solution A

x=300x=300 and n=500n=500.

p ' = x n = 300 500 = 0.600 p'= x n = 300 500 =0.600

q ' = 1 - p ' = 1 - 0.600 = 0.400 q'=1-p'=1-0.600=0.400

Since CL = 0.90 CL=0.90, then α = 1 - CL = 1 - 0.90 = 0.10 α 2 = 0.05 α=1-CL=1-0.90=0.10 α 2 =0.05.

z α 2 = z .05 = 1.645 z α 2 = z .05 =1.645

Use the TI-83, 83+ or 84+ calculator command invNorm(0.95,0,1) to find z.05 z.05. Remember that the area to the right of z.05 z.05 is 0.05 and the area to the left of z.05 z.05 is 0.95. This can also be found using appropriate commands on other calculators, using a computer, or using a Standard Normal probability table.

EBP = z α 2 p ' q ' n = 1.645 ( 0.60 ) ( 0.40 ) 500 = 0.036 EBP= z α 2 p ' q ' n =1.645 ( 0.60 ) ( 0.40 ) 500 =0.036

p ' - EBP = 0.60 - 0.036 = 0.564 p'-EBP=0.60-0.036=0.564

p ' + EBP = 0.60 + 0.036 = 0.636 p'+EBP=0.60+0.036=0.636

The confidence interval for the true binomial population proportion is (p'-EBP,p'+EBP) =(p'-EBP,p'+EBP)=(0.564,0.636)(0.564,0.636).

Interpretation:
  • We estimate with 90% confidence that the true percent of all students that are registered voters is between 56.4% and 63.6%.
  • Alternate Wording: We estimate with 90% confidence that between 56.4% and 63.6% of ALL students are registered voters.
Explanation of 90% Confidence Level

90% of all confidence intervals constructed in this way contain the true value for the population percent of students that are registered voters.

Solution B

Using a function of the TI-83, 83+ or 84 calculators:

Press STAT and arrow over to TESTS.
Arrow down to A:1-PropZint. Press ENTER.
Arrow down to xx and enter 300.
Arrow down to nn and enter 500.
Arrow down to C-Level and enter .90.
Arrow down to Calculate and press ENTER.
The confidence interval is (0.564, 0.636).

Calculating the Sample Size n

If researchers desire a specific margin of error, then they can use the error bound formula to calculate the required sample size.

The error bound formula for a population proportion is

  • EBP = z α 2 p'q' n EBP= z α 2 p'q' n
  • Solving for nn gives you an equation for the sample size.
  • n= z α 2 2 p'q' EBP 2 n= z α 2 2 p'q' EBP 2

Example 3

Suppose a mobile phone company wants to determine the current percentage of customers aged 50+ that use text messaging on their cell phone. How many customers aged 50+ should the company survey in order to be 90% confident that the estimated (sample) proportion is within 3 percentage points of the true population proportion of customers aged 50+ that use text messaging on their cell phone.

Solution

From the problem, we know that EBP=0.03 (3%=0.03) and

z α 2 = z .05 = 1.645 z α 2 = z .05 =1.645 because the confidence level is 90%

However, in order to find n , we need to know the estimated (sample) proportion p'. Remember that q'=1-p'. But, we do not know p' yet. Since we multiply p' and q' together, we make them both equal to 0.5 because p'q'= (.5)(.5)=.25 results in the largest possible product. (Try other products: (.6)(.4)=.24; (.3)(.7)=.21; (.2)(.8)=.16 and so on). The largest possible product gives us the largest n. This gives us a large enough sample so that we can be 90% confident that we are within 3 percentage points of the true population proportion. To calculate the sample size n, use the formula and make the substitutions.

n=z2p'q'EBP2 n z 2 p' q' EBP 2 gives n=1.6452(.5)(.5).032 n 1.645 2 (.5) (.5) .03 2 =751.7

Round the answer to the next higher value. The sample size should be 752 cell phone customers aged 50+ in order to be 90% confident that the estimated (sample) proportion is within 3 percentage points of the true population proportion of all customers aged 50+ that use text messaging on their cell phone.

**With contributions from Roberta Bloom.

Glossary

Binomial Distribution:
A discrete random variable (RV) which arises from Bernoulli trials. There are a fixed number, nn, of independent trials. “Independent” means that the result of any trial (for example, trial 1) does not affect the results of the following trials, and all trials are conducted under the same conditions. Under these circumstances the binomial RV XX size 12{X} {} is defined as the number of successes in nn trials. The notation is: XX~ B ( n , p )B(n,p). The mean is μ=np μ np and the standard deviation is σ = npq σ=npq. The probability of exactly xx successes in nn trials is P ( X = x ) = n x p x q n x P(X=x)= n x p x q n x .
Confidence Interval (CI):
An interval estimate for an unknown population parameter. This depends on:
  • The desired confidence level.
  • Information that is known about the distribution (for example, known standard deviation).
  • The sample and its size.
Confidence Level (CL):
The percent expression for the probability that the confidence interval contains the true population parameter. For example, if the CL=90%CL=90%, then in 9090 out of 100100 samples the interval estimate will enclose the true population parameter.
Error Bound for a Population Proportion(EBP):
The margin of error. Depends on the confidence level, sample size, and the estimated (from the sample) proportion of successes.
Normal Distribution:
A continuous random variable (RV) with pdf f(x)=1σe(xμ)2/2f(x)=1σe(xμ)2/2 size 12{ ital "pdf"= { {1} over {σ sqrt {2π} } } e rSup { size 8{ - \( x - μ \) rSup { size 6{2} } /2σ rSup { size 6{2} } } } } {}, where μμ is the mean of the distribution and σσ is the standard deviation. Notation: XX ~ N μ σ N μ σ . If μ=0μ=0 and σ=1σ=1, the RV is called the standard normal distribution.

Collection Navigation

Content actions

Download:

Collection as:

PDF | EPUB (?)

What is an EPUB file?

EPUB is an electronic book format that can be read on a variety of mobile devices.

Downloading to a reading device

For detailed instructions on how to download this content's EPUB to your specific device, click the "(?)" link.

| More downloads ...

Module as:

PDF | EPUB (?)

What is an EPUB file?

EPUB is an electronic book format that can be read on a variety of mobile devices.

Downloading to a reading device

For detailed instructions on how to download this content's EPUB to your specific device, click the "(?)" link.

| More downloads ...

Add:

Collection to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks

Module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need an account to use 'My Favorites'.

| A lens I own (?)

Definition of a lens

Lenses

A lens is a custom view of the content in the repository. You can think of it as a fancy kind of list that will let you see content through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks