AP Bio: Statistics and Experimental design

Standard deviation

A computed measure of how much scores vary around the mean score

Hypothesis

A testable prediction, often implied by a theory

Controlled variable

A variable that is kept constant during a controlled experiment.

Positive control

Control group expected to give a known, strong result. Needed to compare to the experimental group to show that the experiment is properly designed to measure the dependent variable.

Negative control

Control group where there is no expected change. Needed to compare to the experimental group to show to assess the effect of the independent variable.

Control group

In an experiment, a group that is NOT exposed to the experimental treatment, but is needed to compare with the experimental group to evaluate the effect of the treatment.

Statistical testing

Provides a way of determining whether the null hypothesis should be accepted or rejected; determines if relationships between variables are statistically significant or have occurred by chance.

Error bar

Representation of an uncertainty on a graph.

Chi-square test

Statistical test used to determine if observed results are significantly different than expected results.

Statistically significant difference

The difference between two groups is large enough that it is unlikely to be due to chance or sampling error. +/-2SEM error bars do NOT overlap p<0.05 Reject the null hypothesis

Critical value

The dividing point between the region where the null hypothesis is rejected and the region where it is not rejected. If chi-square > critical value: reject the null hypothesis If If chi-square < critical value: fail to reject the null hypothesis

Independent variable

The experimental factor that is manipulated; the variable whose effect is being studied. Graphed on the x-axis.

Sample size (n)

The number of subjects used in an experiment or study. Generally, the larger the better.

Dependent variable

The outcome factor; the variable that may change in response to manipulations of the independent variable. Graphed on the y-axis.

p-value

The probability of observing a test statistic as extreme as, or more extreme than, the statistic obtained from a sample, under the assumption that the null hypothesis is true.

Significance level (alpha, α)

The probability of rejecting the null hypothesis when the null hypothesis is true. Usually set at 0.05.

Alternative hypothesis

The statistical hypothesis that states there is a difference between two or more sets of data.

Null hypothesis

The statistical hypothesis that there is no significant difference between specified populations, and that any observed difference is due to sampling or experimental error.

Chi-square value is less than the critical value

There is NOT a statistically significant difference between observed and expected results. Any difference between the groups is due to random chance. p>0.05 Fail to reject the null hypothesis

Fail to reject the null hypothesis

There is NOT a statistically significant difference between two groups. Any difference between the groups is due to random chance. +/-2SEM error bars overlap p>0.05

Error bars overlap

There is NOT a statistically significant difference between two groups. Any difference between the groups is due to random chance. p>0.05 Fail to reject the null hypothesis

Chi-square value is greater than the critical value

There is a statistically significant difference between observed and exepcted results. p<0.05 Reject the null hypothesis

Error bars do NOT overlap

There is a statistically significant difference between two gThere is a statistically significant difference between two groups. p<0.05 Reject the null hypothesisroups. p<0.05 Reject the null hypothesis

Reject the null hypothesis

There is a statistically significant difference between two groups. +/-2SEM error bars do NOT overlap p<0.05

Standard error of the mean

the standard deviation of the sampling distribution of sample means