Loading presentation...

Present Remotely

Send the link below via email or IM

Copy

Present to your audience

Start remote presentation

  • Invited audience members will follow you as you navigate and present
  • People invited to a presentation do not need a Prezi account
  • This link expires 10 minutes after you close the presentation
  • A maximum of 30 users can follow your presentation
  • Learn more about this feature in our knowledge base article

Do you really want to delete this prezi?

Neither you, nor the coeditors you shared it with will be able to recover it again.

DeleteCancel

Make your likes visible on Facebook?

Connect your Facebook account to Prezi and let your likes appear on your timeline.
You can change this under Settings & Account at any time.

No, thanks

8.3 The Sampling Distribution of a Sample Proportion

No description
by

Jaime Pitman

on 9 April 2014

Comments (0)

Please log in to add your comment.

Report abuse

Transcript of 8.3 The Sampling Distribution of a Sample Proportion

8.3 The Sampling Distribution of a Sample Proportion
The objective of many statistical investigations is to draw a conclusion about the proportion of individuals or objects in a population that possess a specified property.
For example, coffee drinkers who regularly drink decaffeinated coffee
NEW NOTATION!
Let's EXPERIMENT!!
We're each going to flip a coin 20 times. Then calculate the proportion and plot on the dotplot.
What if...

What if we flipped the coins 50 times and found the proportion of heads?
Sampling Distributions of p
Sampling Distributions of p depends on both:
n, sample size
, proportion of successes in the population
Properties of Sampling Distribution of p
The mean value of the sampling distribution p is equal to the proportion of successes in the population.
Holds true when no more than 10% of the population is included in the sample
When n is large and is not too near 0 or 1, the sampling distribution of p is approximately normal.
RULE #1
RULE #2
RULE #3
Center
Spread
Shape
Conditions on Shape (Rule #3)
The sampling distribution of p can be considered a normal distribution if:
EXAMPLE
What is the probability that the proportion of defective products in the sample is greater than 0.10? P (z > .10)

Practice on Your Own!
Suppose 3%, or 𝜋=0.03, of the people contacted by phone are receptive to a certain sales pitch and buy your product. A sample size of 2,000 is considered.

1) Show that this sample size is large enough to justify using the normal approximation to the sampling distribution of 𝑝.

2) What is the mean of the sampling distribution of 𝑝?

3) What is the standard deviation of the sampling distribution of 𝑝?

4) What is the probability that the proportion of people who are receptive to the sales pitch is less than 0.025? P( z < .025)
Full transcript