Biology ares of emphasis

1. BIOLOGY

2. Themes of biology
1. Levels of organization
2. The cellular basis of life
3. Genetics
4. The correlation between structure and
function
5. The interaction of organisms with their
environment
6. Homeostasis
7. Evolution, unity, and diversity

3. 1. Levels of organization

4. 1. Levels of organization

5. 1. Levels of organization
 Emergent properties
 Characteristics not
present at simpler
levels of organization
 Holism
 An organism is more
than the sum of their
parts
 Reductionism
 By studying an
organisms parts, you
can understand it

6. 2. Cellular basis of life
 Cell theory
 All cells come from other
cells
 All living things made of cells
 Classification of organisms
 Size – single or multicellular
 Complexity – eukaryotic or
prokaryotic
 Energy use – autotroph and
heterotroph

7. 3. Genetics
 Organisms pass on
genetic information
to their offspring via
DNA
 Four different
letters in DNA make
organisms what
they are
 Billions of these
letters code for an
organism

8. 4. Structure and function
 The structure of things are
related to their function –
form fits function
 Anatomy and physiology

9. 5. Ecology
 Organisms always interact with their
environment
 Nutrient cycling
 Energy flow
 Human impact on the environment

10. 6. Homeostasis
 The ability of an
organism to
maintain its
internal
conditions
 Feedback
mechanisms
 Positive
feedback
 Negative
feedback

11. 7. Evolution, unity, and diversity
 Evolution
 Change in frequency
of alleles in a
population over time
 Organisms share
common ancestors
 Natural
selection, “survival
of the fittest,” drives
evolution

12. 7. Evolution, unity, and diversity
 Diversity is
enormous
 Taxonomy –
scientific
classification
 Kingdom-phylum-
class-order-family-
genus-species
 All organisms exhibit
similarities in genetic
code, cell structure,
and metabolic

13. 8. Science as a process
 Inductive reasoning
 Use specifics to
make general
conclusion
 Deductive
reasoning
 Use general idea to
learn specifics

14. 8. Science as a process
 Testing hypotheses
is the basis of
science
 Propose an idea to
a problem or
question
 Scientific method
 A flexible outline to
answer questions
or solve problems
 Requires evidence
The effect of gestational age on birth
weight

15. 8. Science as a process
 Science
continually
incorporates
new data to
gain a better
understanding
of the world

16. Science as a process and
technology
 Technology
improves
the ability to
learn about
many
aspects of
biology

17. EXPERIMENTAL
DESIGN

18. Independent and dependent
variables
 Independent
variable
 What the scientist
intentionally
changes
 Dependent
variable
 What is
measured, or
what changes in
response to the
independent

19. Control and experimental
groups
 Both relate to the
independent
variable
 Control group
 What all other
groups are
compared to
 Usually the lowest,
highest, or “normal”
value
 Experimental groups
 All of the other
values of the
independent
variable compared

20. Scientific title
 Should be
descriptive
enough to
indicate what is
going on in the
experiment
 “The Effect of
(IV) on (DV)”

21. Hypothesis
 Must be
falsifiable
 More than an
educated
guess
 Can’t be
“proven,” only
rejected
 “If…then…”

22. Constants
 Factors that
remain consistent
throughout the
experiment
 There should
only be one
independent
variable in an
experiment

23. GRAPHING

24. Graphs
 The purpose of a
graph is to help
visually depict
data and trends in
data
 There are many
requirements to
graph data
properly

25. Requirements for graphing
 Scientific title
 Axis labels
 Regular intervals
 Variables on
correct axes
 Choosing the right
type of graph
The effect of work
experience on
income

26. Requirements for graphing
 Variables on
correct axes
 Independent
variable on x
axis
 Dependent
variable on y
axis

27. Choosing the right type of graph
 Pie chart
 Typically shows
part, or
percentage, of
a whole

28. Choosing the right type of graph
 Scatter plot and line
graphs
 Used to look at the
relationship of one
variable on another
 Usually requires an
independent
variable that is a
number
 Can use a line of
best fit

29. Choosing the right type of graph
 Bar graph
 Typically
used when
the
independen
t variable is
not a
number

30. Choosing the right type of graph
 Box and
whisker graph
 Similar to a
scatter plot or
bar graph, but
shows much
more detail

31. Choosing the right type of graph

32. WRITING A LAB
REPORT
Using experimental design

33. Pre-lab

34. Overview

35. Introduction

36. Materials

37. Procedure

38. Data

39. Conclusion

40. Trials
 The more
data you can
collect, the
better
 At a
minimum, 30
trials per
experimental
group

41. CHI-SQUARED
ANALYSIS

42. Forming a null hypothesis
 Used because
you don’t “prove”
a hypothesis, but
can reject one
 If you accept
your null
hypothesis, you
would reject your
original
hypothesis

43. An overview of Chi-squared
 You try to evaluate how
likely your results could
be due to chance
 Requires two variables:
 O – observed data
 E – expected data

44. Levels of significance
 How sure
you want to
be that your
results are
not due to
random
chance

45. Degrees of freedom
 The number of
possible outcomes
or selections, minus
1

46. Example problem
 If you rolled 120 six-
sided dice and you
ended up with:
 27 1’s
 23 2’s
 11 3’s
 19 4’s
 18 5’s
 20 6’s
 And you want 95%
confidence… would
you reject or accept
your null hypothesis?

47. Example problem
 If you rolled 120 six-
sided dice and you
ended up with:
 27 1’s
 25 2’s
 11 3’s
 19 4’s
 18 5’s
 20 6’s
 And you want 95%
confidence… would
you reject or accept
your null hypothesis?
 Observed values –
27, 25, 11, 19, 18, 20

48. Example problem
 If you rolled 120 six-
sided dice and you
ended up with:
 27 1’s
 25 2’s
 11 3’s
 19 4’s
 18 5’s
 20 6’s
 And you want 95%
confidence… would
you reject or accept
your null hypothesis?
 Expected values –
120/6 = 20

49. Example problem
 Observed values –
27, 25, 11, 19, 18, 20
 Expected values –
120/6 = 20
(27-20)2+
20
(25-20)2+
20
(11-20)2+
20
(19-20)2+
20
(18-20)2+
20
(20-20)2
20

50. Example problem
 Observed values –
27, 25, 11, 19, 18, 20
 Expected values –
120/6 = 20
49+
20
25+
20
81+
20
1 +
20
4 +
20
0
20
= 160
20
= 8

51. Example problem
 If you rolled 118 six-
sided dice and you
ended up with:
 27 1’s
 23 2’s
 11 3’s
 19 4’s
 18 5’s
 20 6’s
 And you want 95%
confidence… would
you reject or accept
your null hypothesis?
= 8