Tests


 * T tests** (Making inferences about means)

x bar ±t*(s/√n); with n-1 degrees of freedom t= (x bar -µ0)/ s/ √n 2nd-> DISTR->4:invT(.05, 7) H0 :µ=___ Ha:µ >, <, or not equal to__ _
 * One Sample T-test**
 * Assumptions and Conditions**
 * Randomness
 * The sample size must be less than 10% of the population
 * Can be normal or __nearly normal__ (found by using a Normal Probability Plot or with a unimodal and symmetric histogram).
 * 1 sample Confidence Interval**
 * 1 sample t-test**
 * Finding t* on the calculator for 90% confidence with 7 degrees of freedom**
 * Hypothesis Testing**

SE= √(S1^2/N1)+(S2^2/N2) (x bar 1- x bar 2) ± t*SE As n increases, p-values become more accurate t= __(x bar 1- x bar 2)- (µ____1-µ2)__ SE For a two-sample t-test, use whichever degrees of freedom is smaller.
 * Two Sample T-statistics**
 * Assumptions and Conditions**
 * 2 Random Samples and 2 Different populations
 * Independent of each other
 * Both are nearly normal
 * 10% Condition
 * Standard Error for Two-Sample T-tests**
 * 2- sample Confidence Interval**
 * 2-sample t-test**
 * Degrees of Freedom**

Great idea for a post!