1 / 21

Statistics Quick Overview - PowerPoint PPT Presentation

Statistics Quick Overview. Class #2. A New Game. 1. 2. 3. Conditional Probability Examples. Given that a consumer has looked at a green shirt 5 times What is the probability that they will buy? What is the probability that they will buy if you give them 5% off?

I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.

PowerPoint Slideshow about 'Statistics Quick Overview' - lot

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

Statistics Quick Overview

Class #2

1

2

3

• Given that a consumer has looked at a green shirt 5 times

• What is the probability that they will buy?

• What is the probability that they will buy if you give them 5% off?

• What is the probability that they will buy if you give them 10% off?

• What is the probability given that they are a new customer/existing customer?

• Given that a consumer has bought a flashlight

• What is the probability that they will buy batteries?

• What is the probability that they will buy a 2nd flashlight?

Solution space = 1

A and B

Solution space = 1

A and B

(75%)

= 90% + 80% - 75%=95%

1-95% = 5% chance neither will start

Neither Will Start?A Table Can Be Helpful

Acura

Starts Doesn’t

Starts

Doesn’t

80%

75%

5%

BMW

20%

15%

5%

10%

90%

Solution space = 1

A and B

(75%)

= 75% / 80% = 93.75%

Conditional Probability:A Table Can Be Helpful

Acura

Starts Doesn’t

Normalize this row:

75% / 80%

Starts

Doesn’t

80%

75%

5%

BMW

20%

15%

5%

10%

90%

Counting: What Do These Five Guys in Front……

Right

Center

Left

Let’s Say A Coach (Maybe Mr. Brown?) Had to Pick 3 Players for Hockey and Then Quiditch

• Here, order matters

• The person on the left must stay on the left

• The person on the right must stay on the right

• So, how many different potential line-ups does Mr. Brown have to consider?

• Choices are: Mr Blonde, Mr White, Mr Orange, Mr Pink, and Mr Blue

5 x 4 x 3 = 60

Where n is the number of choices, and k is the number picked. In Excel, this is PERMUT(n,k)

Let’s Carefully Write Out the Permutations for Hockey and Then

Note: Each column is a unique combination of players

Note: The entries within each row are different permutations of the players. This is our same problem again where n= 3 and k = 3

==6

Mr. Brown’s Choices for a for Hockey and Then Quiditch Front Line

• Here, order does not matter

• He just needs a front line

• All that matters is the number of unique combinations

• What observation from the permutation table helps us determine the unique combinations

Figuring out the Combinations for Hockey and Then

When calculating the permutations, we naturally determined the unique combinations (the columns) and then ran the permutations for each combination. If we divide out that last step, we will have just the combinations:

= 60 / 6=10

Binomial Distribution for Hockey and Then

• Sample Size of 10

• Case #1: Assume that the lot is good with 5% defectives

• When will you reject because you find 3 or more defectives

• Case #2: Assume that the lot has 40% defectives

• When will you accept because you find 2 or less defectives

• Let’s assume:

• s is the probability of success

• f is the probability of failure

Case #1 (only 5% of the lot is defective) for Hockey and Then

• Example of getting 3 Failures

• fssfsssssf

• Probability of this is (5%)3(95%)7

• Example of getting 4 Failures

• fssfsfsssf

• Probability of this is (5%)4(95%)6

• What are we missing?

The number of combinations

Bayes’ Rule for Hockey and Then

• A1 uses drugs P(A1) = 5%

• A2 does not use drugs P(A2) = 95%

• B tests shows drug use

• P(B | A1) = 98%

• P(B | A2) = 2%

What we want….

Bayes Rule- Calculate for Hockey and Then

Bayes Rule- Calculation for Hockey and Then

=

= 5%*(98%) / ((5%*98%)+(95%*2%)) =72%