introduction to biology
DESCRIPTION
This slideshow will provide an introduction to themes of biology and experimental design.TRANSCRIPT
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BIOLOGY
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Themes of biology
1. Levels of organization2. The cellular basis of life3. Genetics4. The correlation between structure and
function5. The interaction of organisms with their
environment6. Homeostasis7. Evolution, unity, and diversity8. Science as a process
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1. Levels of organization
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1. Levels of organization
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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 better as a whole
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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
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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
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4. Structure and function
The structure of things are related to their function – form fits function Anatomy and
physiology
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5. Ecology
Organisms always interact with their environment Nutrient cycling Energy flow Human impact on the environment
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6. Homeostasis
The ability of an organism to maintain its internal conditions
Feedback mechanisms Positive
feedback Negative
feedback
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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
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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 pathways
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8. Science as a process
Inductive reasoning Use specifics to
make general conclusion
Deductive reasoning Use general idea to
learn specifics
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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
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8. Science as a process
Science continually incorporates new data to gain a better understanding of the world
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Science as a process and technology
Technology improves the ability to learn about many aspects of biology
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EXPERIMENTAL DESIGN
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Independent and dependent variables
Independent variable What the scientist
intentionally changes
Dependent variable What is measured,
or what changes in response to the independent variable
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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 to the control group
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Scientific title
Should be descriptive enough to indicate what is going on in the experiment
“The Effect of (IV) on (DV)”
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Hypothesis
Must be falsifiable
More than an educated guess
Can’t be “proven,” only rejected
“If…then…”
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Constants
Factors that remain consistent throughout the experiment
There should only be one independent variable in an experiment
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GRAPHING
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Graphs
The purpose of a graph is to help visually depict data and trends in data
There are many requirements to graph data properly
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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
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Requirements for graphing
Variables on correct axes Independent
variable on x axis
Dependent variable on y axis
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Choosing the right type of graph
Pie chart Typically
shows part, or percentage, of a whole
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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
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Choosing the right type of graph
Bar graph Typically
used when the independent variable is not a number
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Choosing the right type of graph
Box and whisker graph Similar to a
scatter plot or bar graph, but shows much more detail
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Choosing the right type of graph
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WRITING A LAB REPORT
Using experimental design
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Pre-lab
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Overview
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Introduction
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Materials
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Procedure
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Data
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Conclusion
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Trials
The more data you can collect, the better
At a minimum, 30 trials per experimental group
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CHI-SQUARED ANALYSIS
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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
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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
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Levels of significance
How sure you want to be that your results are not due to random chance
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Degrees of freedom
The number of possible outcomes or selections, minus 1
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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?
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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
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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
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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
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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
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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