Unit 1 AP BIO - Review Notes

Hypotheses: Educated guesses that are based on prior knowledge and prior research.

  • Null Hypothesis: What you would expect if your hypothesis was false.

  • Alternative Hypothesis: What you would expect if your hypothesis was true

  • Null Hypothesis - Opposite - Alternative Hypothesis


Variables:

  • Independent Variable: This is the manipulated variable which you can change

  • Independent Variable: The responding variable which can be measured.

  • Controlled Variable: Conditions that stays the same for all experimental groups.


Groups:

Control Group: The group that remains unchanged or untreated to refer back to.

Experimental Group: The group that is changed or treated.


  • One experiment may not yield accurate results.

  • Generalization is only made when a small sample size is made and based on the result of from that experiment the same patterns can be assumed of the larger whole.

  • In order to avoid making false generalization, try to have a large sample size.


Sampling Error: The difference between the result of the subset and the result of the whole.


  • Bias: When scientists only pay attention to the results they expect to happen.


Scientific Theory: A long-standing hypothesis that has been disapproved after many years of rigorous testing.


Types of Data Collection:

  • Tables - are used to organize exact amounts of data and to display numerical information. Tables do not show visual comparisons.

  • Line graphs - are used to display data or information that changes continuously over time. Line graphs allow us to see overall trends such as an increase or decrease in data over time.

  • Bar graphs - are used to compare facts. The bars provide a visual display for comparing quantities in different categories or groups.


  • Statistically Significant - refers to a result that is statistically unlikely to have occurred by chance.

  • Standard Deviation: a measure of how spread out the data is from the mean.

  • Lower Standard Deviation: Data is closer to the mean and

  • High Standard Deviation: Data is more spread out from the mean