MIS Test 2 – presentation 1

MIS Test 2 – presentation 1 - MIS Test 2...

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MIS Test 2 – presentation 1 27/02/2007 14:03:00 Sats continued Standard Error of the sample mean*     o The SD of the sampling distribution of the sampling means. TI is a  measure of the variability of the sampling distribution of the sample  mean.  o The SD. Of a sample!  o Ex: row – 6 ppl on row  Hours sleep last night   SD of this row – add get mean and sub each from mean How far is each person vary form each other person Standard Error  Each row in the class is now a sample  Find the mean for each sample (row)  Until you find the mean for every row.  Then take the mean of the entire 26 groups (class)  Then see how far each sample’s mean is from the  whole average o Sample compared to the population** Same relationship as SD.  Simply a SD looking at one sample to the whole***  Same relationship as SD They are still going to fall in the normal curve Its going to balance 
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The variance of the way the samples are taken if  you take a large enough sample then it will still fall  out into the normal curve.  Experimental Process     o Subjects Something were looking at  ( ex: ppl) we have to look at the size of our sample small if using 50 or smaller  why we use n-1 (gives us freedom) what if…  confounded variable  o therefore size and circumstance can effect  you data o Treatment  Were going to do something to them or observe what has  already been done to it  (ppl come to Ms. C’s house) o Observation  (does the side that went to her house do better) Variables     o Explanatory variable  Independent  students o Response variable 
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Dependent   Their grades  o Lurking or Confounding variable All 4.0 students on one side – or other side all parties night  before test. Variables that just happen o Test question given a situation and ask to name dependent,  independent, and confounded variable  Completely Randomized Design     o Simplest design strategy o Each subject is randomly assigned to one group  o Typically, group sizes are identical  o (can’t compare unequal groups – 1 to 12 ) they need to be keep EQUAL o EX:  Group A, B & C Randomly assigned  Was it an equal chance that each got in that row  Not completely random – just pick 1 st  3 rows get A’s  This would be sewed data – curve Needs to be completely random  Block Design      o Used when known extraneous variables may influence the  experiments
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o Subjects are pre-sorted by the influencing variables, then partitioned  into similar blocks
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