Statistical difference is relative to variation range precision accuracy( variation, range, precision, accuracy ) in the dataset, and tells you nothing everything you need to know( nothing, everything you need to know ) about the actual biology. The biological importance of the dataset is the effect of the statistical difference observational difference precision( statistical difference, observational difference, precision ), and is the primary subject of the "discussion conclusion methods introduction( discussion, conclusion, methods, introduction )" portion of a paper.

Number of people is an example of discrete continuous( discrete, continuous ) data.
Length of an elephant's trunk is an example of continuous discrete( continuous, discrete ) data.

Accuracy Precision( Accuracy, Precision ) is how close the data is to "the truth" (specifically the mean range median( mean, range, median )).
Precision Accuracy( Precision, Accuracy ) is how close multiple measurements are to each other.

Standard Deviation Standard Error of the Mean Sum of Squares( Standard Deviation, Standard Error of the Mean, Sum of Squares ): deviation in the sample that was measured
Standard Error of the Mean Standard Deviation Mean of Squares( Standard Error of the Mean, Standard Deviation, Mean of Squares ): estimate in variation of mean values if you take multiple sets f samples

TYPES OF RANDOMIZATION

Random Selection with Replacement Random Selection without Replacement Haphazard Selection( Random Selection with Replacement, Random Selection without Replacement, Haphazard Selection )
1. Tag entire population
2. Random Draw
3. Replace individual in population
4. Probability of selection is constant Probability of selection changes No probability of selection( Probability of selection is constant, Probability of selection changes, No probability of selection )
Theoretically the best way. The worst kind of selection( Theoretically the best way., The worst kind of selection )

Random Selection without Replacement Random Selection with Replacement Haphazard Selection( Random Selection without Replacement, Random Selection with Replacement, Haphazard Selection )
1. Tag entire population
2. Random Draw
3. Measure Inividual
4. Do not place back into population
5. Probability of selection changes Probability of selection is constant No probability of selection( Probability of selection changes, Probability of selection is constant, No probability of selection )
Can get around by using same measurement if drawn again

Haphazard Selection Random Selection with Replacement Random Selection without Replacement( Haphazard Selection, Random Selection with Replacement, Random Selection without Replacement ):
1. Don't tag anything
2. No random draw
3. Measure Individual
4. Replacement is irrelevant
5. No probability of selection Probability of selection is constant Probability of selection changes( No probability of selection, Probability of selection is constant, Probability of selection changes )
The worst kind of selection Theoretically the best way( The worst kind of selection, Theoretically the best way ), though it is still often used

As sample size (n) increases, the t-value decreases increases( decreases, increases ), the standard error (SE) decreases increases( decreases, increases ), and the confidence interval (CI) narrows widens( narrows, widens ).

Measurement Unit Experimental Unit( Measurement Unit, Experimental Unit ): the object that is measured
Experimental Unit Measurement Unit( Experimental Unit, Measurement Unit ): the object that is manipulated