Science And Experimental Design

Question 1

Negative control

Answer 1

Negative control is a sample or experiment to determine what happens without the experimental intervention

Question 2

Positive control

Answer 2

A sample or experiment to show that the experimental system will show an effect (if it does really have an effect)

Question 3

Example of biases

Answer 3

-using inappropriate controls
-failing to take a truly random sample from a population
-human bias in observation
—selecting which data to include after seeing results from an experiment

Question 4

Systematic errors

Answer 4

Are errors that bias the data in a particular direction.

Eg a miscalibrated pipette always add too low a volume of same

Question 5

Random errors

Answer 5

May increase/decrease the variation

Question 6

Sampling error

Answer 6

Natural variation between individuals-has the same mathematical effect as ‘random error’ in measurements.

Question 7

Sem

Answer 7

Standard error of the mean
Our data is subject to random error and variation
This leaves uncertainty about how close our experimental answer is to real answer
Where the real answer is the answer with no random error
Or the mean of a whole population

Sem is where mathematicians can combine the overall variability with the number of times the experiment has been repeated to get an indication of uncertainty. This is called sem which is sd/ sq root of n, where n is the number of repeats

Sem does not measure the spread of data, it measures our confidence in the estimate of the mean

Confidence interval, measure of the uncertainty in estimate of the mean
Only an indication of confidence
Real answer could be +-1 sem or maybe 2 sem but his is less likely

Question 8

Standard deviation

Answer 8

Sd is a measure of the spread of your data. As you get more data the spread will stay the same, only change slightly