Title: Review Lecture
1Review Lecture
- Preparing for the midterm
2Statistics on midterm
- Let Ymidterm average of first three
assignments - For spring 2004, interpret the following
-
3To increase Y
- Know all the material
- Dont be surprised
- Be fast
- Recognize different types of problem
- Find formulas quickly, calculate quickly
- Write up briefly
- Finish the Practice Midterm
- in 90 minutes
- Note. Topics not on Practice Midterm are fair
game - e.g., sampling and sampling variation
4Other ways to study
- Go over old homework
- making sure you can correct your mistakes
- Go over lecture notes
- Do examples before you see my solution
- Do odd numbered chapter problems
- Check your answers in the back of the book
- Remember the book doesnt use t in confidence
intervals for meansbut you do!
5Allowed materials
- Formula sheet you can annotate with
- interpretations
- examples
- mistakes youve made in the past
- Tables you can annotate
- Calculator
- Pencil (recommended) or pen
6First half of course
7Data sets and frequency tables
- Distinguish a frequency table from a data set
- Turn a data set into a frequency table
- and vice versa
- Calculate and interpret
- (cumulative) frequencies
- (cumulative) proportions/percentages
8Graphics
- Turn a frequency table into a
- histogram
- bar chart
- pie chart
- Use vocabulary to describe and explain shape
- left/right skew, symmetry, (uni/bi/multi)modal
- Distort graphics
- Recognize and correct others distortions
9Measures of center
- Calculate each measure of center
- from a data set
- from a frequency table
- Interpret each measure of center
- Use the measure in a sentence that shows a naïve
reader what it means - Know which statistics are sensitive and robust
- Anticipate the effects of adding/removing extreme
values
10Measures of variation
- Calculate each measure of variation
- from a data set
- from a frequency table
- Interpret each measure of variation
- Use the measure in a sentence that shows a naïve
reader what it means - Know which statistics are sensitive and robust
- Anticipate the effects of adding/removing extreme
values
11Sampling
- Identify the population being sampled
- Is it the right population?
- If not, how might the right population differ?
- Know how to take a simple random sample
- and whats wrong with alternatives
- Recognize sampling variation when you see it
- Calculate and interpret the standard error (
margin of error) - What decreases/increases the standard error?
- How sure can you be that the sample mean will be
within X standard errors of the population mean?
12Confidence intervals for the mean
- Calculate a confidence interval for the mean
- Interpret it
- Whats being estimated?
- Why are we uncertain?
- Whats certain / whats uncertain?
- What does it mean to be 95 confident?
- Is it small enough to be informative?
- How can we make it smaller?
- Is it smaller than it needs to be?
- How can we make it bigger?
13Sampling for proportions
- Identify the population being sampled
- Is it the right population?
- If not, how might the right population differ?
- Recognize sampling variation when you see it
- http//www.ohiotreasurer.org/images/f-stat3w.jpg
- Calculate and interpret the standard error (
margin of error) - What decreases/increases the standard error?
- How sure can you be that the sample proportion
will be within X standard errors of the
population proportion?
14Confidence interval for a proportion
- Calculate a confidence interval for a proportion
- Interpret it (use percentage language)
- Whats being estimated?
- Why are we uncertain?
- Whats certain / whats uncertain?
- What does it mean to be 95 confident?
- Is it small enough to be informative?
- How can we make it smaller?
- Is it smaller than it needs to be?
- How can we make it bigger?
15Means vs. proportions
- Calculate confidence intervals
- for means, using t
- for proportions using Z
- different standard errors formulas
- How to tell a proportions problem from a means
problem - Bottom line A proportions problem involves a
dummy variable - keywords
- means problem may say mean or average and give a
standard deviation - proportions problem may say percentage or
probability or chance - keywords not 100 reliable
- see slide 2
16Bonus slides
17Turn this into a frequency table
What of players are at most 80 inches
tall? What are at least 80 inches tall?
18Calculate and interpret measures of center from
the raw data set
19Calculate and interpret measures of center from
the frequency table
20Calculate and interpret measures of variation
from the raw data set
21Calculate and interpret measures of variation
from the frequency table
22Calculate a confidence interval for a mean
- Suppose those players were a sample of the NBA
- Whats a point estimate for the mean height in
the NBA? - Whats a 95 confidence interval?
- Use t
23Calculate a confidence interval for a proportion
- Whats a point estimate for the of NBA players
who are at least 80 inches tall? - Whats a 99 confidence interval?
- Use Z