Stats 2 tips


F test notes

posted Dec 3, 2010, 7:07 PM by Prof Kiernan   [ updated Dec 3, 2010, 7:39 PM ]

You can use the F test to verify a claim about a standard deviation (or variance) for 2 data sets.

Assumptions: The sample is from a "normal distribution"

NOTE: some professors prefer to use the following notation: N~(mean, Standard Deviation)

English Translation: Use an F test  if you are Given: 2 sample sizes (n) and 2 standard deviations (or variances=s2 ) AND you are testing a claim about a standard deviation or variance.

Writing the hypothesis:

H0population standard deviation1 = population standard deviation2

H1: population standard deviationis less than, greater than, or not equal to population standard deviation2

Critical Value = shaded area from F table using the degrees of freedom.

Degrees of freedom: for numerator (use the info from the bigger Standard Deviation) n-1, for denominator (use the info from the smaller Standard Deviation) n-1. Remember that if the null hypothesis requires two tails, split the alpha before using the tables.

Test statistic formula:

F = variance1 / variance2

**The bigger variance (standard deviation squared) must be divided by the smaller variance (standard deviation squared).**


Calculator:

Press STAT

Highlight TESTS

Select 2-SampFTest 

Put your information in.

    **NOTE: S1 must be the biggest standard deviation**

Make sure the not equal to, less than, or greater than symbol matches the one in your alternative hypothesis (H1).

Highlight Calculate Press ENTER

F is the test statistic, and P is the P-value.

Rejection of the null hypothesis (Ho):

You can reject the null hypothesis if:

  • the F from the formula falls in the shaded critical area from the table.
  • the P-value is smaller than your alpha Reject Ho.

Remember: if you are not given an alpha assume you are using 0.05.

A little fun with the Ftest

posted Dec 3, 2010, 7:02 PM by Prof Kiernan   [ updated Dec 3, 2010, 7:07 PM ]

I stumbled across this comic and thought you might find it amusing especially if you're struggling with Hypothesis testing and the ANOVA (analysis of variance).

http://www.phdcomics.com/comics/archive/phd082707s.gif

Hypothesis testing workshop

posted Oct 7, 2010, 1:38 PM by Prof Kiernan

Hi everyone,
 
There will be a workshop on hypothesis testing on Thursday OCT 21,2010 from 2:30 to 3:30 in the IRC Room 116.
 
Click here to RSVP for a seat and free candy.
 
-Patty
If the link doesn't work try this one: http://www.zoomerang.com/Survey/WEB22BAPG6V8E7

Confidence intervals

posted Sep 15, 2010, 1:46 PM by Prof Kiernan

Welcome back, the first sections of Stats 2 will cover a review of stats one and an introduction to the confidence interval. Not only is it important that you understand how to create a confidence interval but you must be able to translate their meaning from stats into everyday english. In short, a confidence interval is found via a formula and states that within a certain amount of error (E) you can be certain that your data should fall between two numbers.


I've attached an example of how to create a confidence interval.

 

 

Happy summer everyone!

posted Aug 10, 2010, 7:56 AM by Prof Kiernan   [ updated Aug 12, 2010, 11:18 AM ]

Happy summer everyone!
 
Heads up, this is the material you need to remember if you're planning on starting Stats 2 this semester.

Review descriptive statistics, basic graphs (histogram, box plot, stem & leaf, cumulative frequency polygon), normal curve, central limit theorem. Might want to also do assessing normality (section 6-2).

Which formula to use:

posted Feb 19, 2010, 7:59 AM by Prof Kiernan


parameter Conditions/given Confidence Interval
test statistic Key words
Proportion nP > 5 & nQ < 5

given:
population proportion (P)

sample proportion
(p = x/n)

q=1-p & Q=1-P
 

Proportion

Percent

You are not given a standard deviation
Mean population data known
OR
n > 30


GIVEN:
σ (population standard deviation)
population mean (μ)         _
sample mean: X
sample size = n
 
 
You know what the population standard deviation is.
Mean population data NOT known
and n < 30

GIVEN:
s (sample standard deviation)
population mean (μ)         _
sample mean: X
sample size = n
 
 
Given sample info
Standard deviation
OR variance(σ²)
Population normally distributed
GIVEN:
σ (population standard deviation)
sample size = n
s (sample standard deviation) 
 

You're working with a hypothesis
about the standard
deviation of a sample

Population or Sample

posted Oct 23, 2009, 12:21 AM by Unknown user   [ updated Feb 4, 2010, 5:39 AM by Prof Kiernan ]

"Samples are small, & they're written in English

Populations are general, & they're written in Greek."

    All sample (portions of the whole group) data is written using english letters. Whereas, the majority of population data use Greek notation. 

1-7 of 7