worksheet

Today we did a worksheet on transformations.

Ch 10!

Ch. 10 #9 and 10

Review answers

a) Yes! The residual plot shows no pattern
b) 233.5: For each year that goes by we predict about 233.5 more aircraft flying.
c) 89.9% of the variation in aircraft flying is explained by regression on year.
d) Plug in 2 (not 1992!): predicted aircraft = 2939.9+233.5*2 = 3406.9 aircraft.
e) residual at 2 = 40, so the actual was 3406.9+40=3446.9 or 3447
f) sqrt(.899) = .948 = strong, positive, linear relationship between year and aircraft.
g) On average, my predicted number of aircraft misses by about 33.43
h) aircraft-hat = 2939.93 + 233.5(year)
i) we predict in 1990 that the number of aircraft flying is about 2939.9

Study hard! I hope this helps!!!

This week

WASC week!!

Monday:  P. 204 #1,2
Tuesday:  Ch. 9 #2, 4, 13, 14
Wednesday:  Practice for the test.  Regression skills, concepts and normal problems.  + a crossword!

Review

Quiz tomorrow!

Ch. 8 #35, 36

Regression practice

Ch 8 #7bcd
#28 all + (e) interpret slope
#33 all + (f) interpret r + (g) interpret r^2

residuals

Ch. 8 #7a, c, e, f & #9

slope and y-intercept

Ch. 8 #25a & c, #29a, c, e, f

Scatterplots

Ch. 7 #4, 6, 8

some review ideas, Unit 1

Outlier fences:
Q1 - 1.5IQR
Q3 + 1.5IQR

sd is always positive
(or zero if all the data is identical)

Categorical graphs:
bar and pie

Quantitative graphs:
stem and leaf (shows data)
boxplot (can hide shape)
ogive/cumulative freq
dotplot
histogram

Independent data makes bar graphs with similar levels

The mean is lower than the median for skewed left data

Measures of spread:  IQR, sd and range
Measures of center: mean and median
Which of the above are resistant?  med and IQR

Rule of thumb:  68-95-99.7

z-score formula:  (x - mu)/sigma

review for wednesday's test

Ch. 3 #22

Unit 1 review #11, 25, 29fg, 30

normal cdf

Ch. 6 #26abc and 17
Answers:
a)  Only 0.07% of tires last longer than 40,000 miles.  Not very likely!
b)  21.19% (z score is -0.8)
c)  67.31% (z scores are -0.8 and 1.2)

Tuesday night's HW

Ch. 6 #7, 11, 12
Page 113 #36
If you ever come looking for homework and I forgot post it, feel free to email me!  I check email on my phone too much, so you'll get a fast reply!

review

Both review assignments are due tomorrow!

Review and test

This week:
Monday:  Unit 1 review, page 105 #7, 16, 21, 29 a-e, 31 and 32
Tuesday:  practice, practice.  Tutoring
Wednesday:  Jeopardy?!?
Thursday:  Test (no tutoring)
Friday:  StatCrunch in the library computer lab
3-day weekend!!!

data

You can find data here:

 

http://wps.aw.com/aw_bock_statsmodworld_3/108/27677/7085352.cw/index.html

standard deviation!

Ch. 5 #5, 6, 36

Chapter 5!

#12, 14, 24, 25, 35

StatCrunch this week

Assignment 1:

• 
  
• Go to My Groups
• Click on RCHS group
• Click on the First Day of school data
• Make a graph of one or more variables on the survey
• Describe
• Print graph and description

Assignment 2:

• Find some data. Lots of it.
• You have to find data that contains both categorical and quantitative variables on the individuals.
• Go to My Data
• On the left, you'll see some options, choose the one that works.
• Make sure to Share with our group:
• If you are viewing the data in the StatCrunch, click Edit and then you can share.

• There is a cool new option that will grab data from a website
• Go to http://www.statcrunch.com/bookmarklet
• Go to that page and read about adding a bookmark called "StatcrunchThis".
• Then go to the website you want to grab.
• Click the bookmark
• Save and data and share it.

Make sure you have described your data so that everyone knows what all the variables mean.

You may do Assignment #2 with a partner IF both of you have joined the AP Stats group.

After you have done assignment #2, email me with your names, your names in StatCrunch and the name of your data set.

Assignment #1 will be checked in class on Friday.

Assignment #2 must be done by 8pm on Thursday night. Anyone who does not receive a reply email from me by 9pm on Thursday night will be considered late.

Find an interesting data set about something you care about!!!

a little more chapter 4

Ch. 4 #13, 28

data, data

Ch. 3 #20
Ch. 4 #9, 12, 17, 24
Don't forget:  if technology fails you, just make a dotplot!
Or you could try making a graph on Statcrunch!
#24 is a problem with statistics done WRONG.  You task is to figure out what is wrong.

Nada

No homework today.
If you missed class, read the TI-Tip on page 11 and learn how to put data in your calculator.  Then read (in chapter 4) how to make a histogram.

Review

Ch. 2 #8
Ch. 3 #14
In class we learned how CUSS!

independent?

Today we started looking at the very important idea of independence.
In class we did Ch. 3 #17 and 18
For homework:  Ch. 3 #15

Pie!

Ch. 2 #7

Ch. 3 #6, 8

Who?

Ch. 2 #2-6
Read Chapter 1

Day 1

Get set up at StatCrunch.com (instructions below)
Read your syllabus
Get a graphing calculator

Stat Crunch instructions

Go to:  Statcrunch.com

Click:  Subscribe

Click:  Redeem access code (under the student section!)

Accept terms and then click No

Choose a login name THAT I CAN RECOGNIZE AS YOU!

Enter password and code

Enter personal info

Now find our group and join it!

RCHS AP stats (2nd page of groups)

Then take the survey!

Competition Information

Information about the Southern California stats event at City of Hope can be found at:

http://postercomp.sc-asa.org/

The national ASA information is at:

http://www.amstat.org/education/posterprojects/index.cfm

resources

I had this nifty packet at the Friday review, but I didn't let you take it home.  If you want a copy, you can find here:

http://tinyurl.com/gwcmq

If you want the answers to the '02 or '07 MC, email me.

Last weekend!

If you're feeling stuck or frustrated, feel free to email me:

mrmathman@gmail.com

You guys are going to do great!

Mr. D

Friday review session

I'm available Friday from 1:30 to 7pm

Bring $5 if you want to order pizza at around 4:15.

I'll bring soda and water.

See you then!

O answers

If you want to check your answers to practice test O, click on the Blog Archive on right.  #1-5 are under April 2008 and #6 is May 1, 2008

Keep practicing!

Finish test O
Keep working on MC '07!

Name that test!

Name: D-4, F-6, H-2 O-6

Name and do:  L-4, L-6, O-2

Web site for Name that Test!

This web site loads slowly, but is pretty nifty:

 

http://www.ltcconline.net/greenl/java/Statistics/StatsMatch/StatsMatch.htm

 

Note: the wording on this website is more vague than the AP test. The AP test always asks for "a 95% confidence interval" if it wants an interval (or some other %). Also, the AP problems are longer, and thus have more information that will guide you to deciding what to do. 

However, I think that after you 10 or so of these, you'll get used to the wording of this site and it will be good practice. 

Note: this website includes prediction intervals, which you do not need to know.

Last Week!!

In Class:  E-3 and we discussed the pearl

HW:  H-3, M-6, start the '07 MC

Prom week

Today in class we did:  E-4b, J-2, L-5

Homework this week:

Test P

Test Q

' 02 Multiple Choice

This week:

Practice test on Tuesday, Wednesday, Thursday

Friday:

Homework day

#6

Double points and double length:

E-6, F-6 and J-6

Inference

We did M4 today and discussed the meaning of a p-value and the meaning of confidence level.

Homework:  MC-A, B-5, G-4

Wednesday

In class:  MC quiz and name that test for I-3b, I-5c, J-5a, K-4a, L-4

 

Homework:  A-5, C-2 and L-4

Tuesday

We practiced with L-1. 

 

Name that test!!

A4, A5, B5, C2, D2, E5, F5, G4, H5

Monday

Sorry, got a day behind.

In class we practice probability.  We did the practice problems on your prob review sheet from Chapters 14, 15 and 18.

Homework:  finish '97 MC and J-3

'97 MC test on Wednesday!

probability

We reviewed calculator probability problems:

Ch. 6 #25 (normal)

Ch. 17 #13d (binomial)

Ch. 16 #15 (expected value)

HW:  97 MC #1-20

Design review

Practice:  C-3 and E-4

Homework:  F2, G3 and H4

Review so far

Last week we reviewed regression:  C-1, D-1

Today we reviewed Unit 1.

Ogives:  A-1

Practice:  J-1

Homework:  E-1, F-1 and H-1

regression practice

C-1 and D-1

regression

C-1 and D-1

a little of this, a little of that...

Hopefully you're done with MC-Y by Friday.

Also

Ch. 22 #17 + interval

Ch. 27 #8, test and interval

2-prop

Ch. 22 #5, 9, 14

B-4

Work on multiple choice test Y

Review for test

From last night's homework, pick one of each:
G of Fit
2-way table
1-t
mp t
2-t

CLT video

http://gallery.me.com/mrmathman/100124

This should help you think about the Central Limit Theorem

t and X^2 review

Name the procedure:
Page 574 #4a, 6, 7, 10, 12, 23, 27, 30acd

practice, practice

Ch. 26 #5, 6, 10, 14
The X^2 for the evens are:  3.677, 290.131, 479.508 (listed in no particular order!).  But that lets you check your work, at least a little bit!

2-way table

Ch. 26 #12 & 13

More G of Fit

Ch. 26 #4, 7, 8

G of fit!

Ch. 26 #2

2-t (and some not!)

Ch. 24 #9, 14 and 16

matched pairs

Ch. 25 #14

tests and intervals together!

Ch. 23 #28, 29

Ch. 13 #35

t-tests

Ch. 23 #17, 21, 25

t-intervals

Ch. 23 #13 & 23

Due on Friday

Read and answer!
statsarticles.blogspot.com

Review!

Page 437 #2, 5, 27, 29, 30
Due Wednesday!
No Late Work!!

Chapter 21 recap

Sample Size!
The bigger the sample size, the more power we have.
We also lower our chances of making either error.

More Sample Size!
We need to be careful with REALLY big sample sizes.
The standard deviation gets really small and you'll always get a small p-value.
This can cloud practical significance: use a confidence interval instead!

Ho is false!
If the Ho is really false, we have lots of power and very little Type
II error (dumb criminal).
If the true value differs only slightly from the Ho, we have little
power and may make a Type II error. (smart criminal)
This is called effect size.

Changing alpha
Making alpha smaller (0.01) makes it harder to reject.
We do this if want less Type I, but are willing to tolerate more Type
II and less power.
i.e., death penalty

Alpha and medicine
If the established treatment is highly effective, you demand a very
small p-value before rejecting (low alpha).
If the standard treatment is not very effective and you have reason to
believe it can be easily improved, you would be more willing to accept
a new treatment even though the p-value is larger (higher alpha).

website

Want to play around with the web site I showed you Thursday?

http://wise.cgu.edu/power/powerapplet1.html

Enjoy!

error?

Ch. 21 #5, 11, 12 (skip e)

quest tomorrow

Ch. 20 #21, 23 + 90% confidence interval for both

sub work

Ch. 20 #2, 7, 8, 18, 19

Tests!

Ch. 20 #9

sample size?

Ch. 19 #3, 8, 13, 25bc

Enjoy!!

End of 18

Ch. 18 #15, 16, 27, 27

Ch. 6 #25e, 27c

p-hats

Ch. 18 #12-14

proportions

Ch. 18 #7, 9, 11

Finals!

An easier simulation is:
Ch. 11 #19
You could look back on old homework, too (Chapter 11)

If you get totally stuck, send me an email, I'll send some answers.

Binomial practice

Ch. 17 #13-21 odd

more review

Page 342 #20, 25, 26

Probability review

Page 340 #1, 2, 5, 15, 16, 19, 20

the end...

Ch. 17 #19ab, #21a

Binomial

Ch. 17 #14abd
Page 341 #3, 6, 7
Merry Christmas!

Binomial

Ch. 16 #33
Ch. 17 #6

Tuesday's work

Ch. 16 #5, 6 and 14

rules, rules

Ch. 16 #25, 27, 30

14 and 15

Ch. 14 #20, 21
Ch. 15 #23, 24, 17

Last night: Ch. 15 #4, 14, 20

End of Unit 3

Page 269 #23, 24, 29

Chapter 13

#23-26

more experiments

Ch. 13 #28, 29, 30

Experiments!

Ch. 13 #6-8

End of 12

Ch. 12 #8, 9, 18, 19, 22

just a bit

Find a price from your parents and figure out the inflation rate
Finish #4: graph and algebra
On the ball lab: are the graphs continuous or discrete? what are the
y-intercepts?

methods

Ch. 12 #11, 12, 14

survey says...

Ch. 12 #5-8
Read P. 241-242

Unit 2 Review

Ch. 10 #27
Unit II Review #1, 2, 4, 8, 9, 37, 40
Due Wednesday!
Article Due Friday!!

more transformations

worksheet

transformers!

Ch. 10 #1, 2, 7

Influential

Ch. 9 #11, 12, 13

end of chapter 8

HW:  Ch. 8 #31, 32, 36

Notes from today in class:

• What the heck is a "line of best fit"?
  
• Its real name is: Least Squares Regression Line!
  
• Or:  LSRL
  
• Least squares? least squares of what?
  
• The sum of all the residuals squared is as small as possible!
  
• Regression?  What does that word mean?
  
• r tells us how much to regress to the mean (example…)
  
• And speaking of mean:
  
• (x-bar, y-bar) is on the line (duh!).
  
• And btw:  the residuals always add up to zero.
• You should also note that if you switch x and y, the correlation does not change, but the LSRL does.
• You should never use a LSRL to predict x using y.  It is not created to minimize the predictions for x, only for y.

R^2

Ch. 8 #3bcd and #21

residuals

Ch 8 # 9c, 10de, 35d
Thanks!

slope, y-int

Ch. 8 #9ab, 10abc, 35abc