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#### 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: H0:  population standard deviation1 = population standard deviation2 H1: population standard deviation1  is 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 ENTERF 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 PercentYou 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.

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