AP Bio Unit 1 Complete Student Notes Flashcards

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AP Biology Unit 1 Student Notes

Table of Contents Link

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Table of Contents

A. Scientific Method/Experimental Design—Pages 3-5

B. Graphing—Pages 5-6

C. Free Response Writing Tips—Pages 7-9

D. Data Analysis/Statistics—Pages 10-25

E. Graphs With Error Bars—Pages 12-16

F. Hypothesis Testing—Pages 16-25

G. Chi Square Analysis—Pages 16-19

H. t-tests—Pages 20-24

I. Chemistry Basics—Pages 25-26

J. Biochemistry of Water—Pages 27-29

K. Biochemistry of Carbon—Pages 30-31

L. Carbohydrates—Page 32

M. Lipids—Pages 32-35

N. Proteins—Pages 35-39

O. Nitrogen Cycle—Pages 39-40

P. Nucleic Acids—Pages 41-43

Q. Phosphorus Cycle—Pages 43-44

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## Unit 1 Student Notes Content Outline: The Scientific Method

The Scientific Method

Series of steps followed to solve problems

Steps are not always the same for each question

Step 1: State your Problem/Question

Develop a question or problem that can be solved through experimentation

Make sure it is something that interests you

Step 2: Make Observations/Do Research

Make observations

Qualitative observations

Quantitative observations

Inferences

Predictions

Do research

Literature research, not lab-based research

Step 3: Formulate a Hypothesis

A hypothesis is a prediction or possible answer to the problem or question

Relationship between the Independent variable and Dependent variables

Step 4: Experiment

Develop and follow a procedure that anyone can follow

Use precise directions

Include a detailed materials list

The experiment must have a control group

Experimental group(s) and constants

Step 5: Collect Data

Write down results as you perform the experiment

Qualitative Data

Quantitative Data

Step 6: Analyze Data

Confirm the results by retesting

Trials

Convert results to a graph

Use descriptive and inferential statistics

Step 7: Conclusion

The written results of the experiment

Statement if the hypothesis was supported or refuted

Recommendations for further study and improvements

Step 8: Communicate Results

Be prepared to present the project to an audience

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Graphing

Graphs and charts communicate information visually

Independent variable on the x-axis

Dependent variable on the y-axis

Label both axes and include units

Provide a descriptive title

Use the pattern "The Effect of the independent variable on the dependent variable"

Plotting data points without drawing a line

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Graphing (continued)

DRY MIX mnemonic for remembering the pattern of labeling axes

Enclose the unit in parentheses

Descriptive title for the graph

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Use the ten minute reading time advantageously

Read all of the free response questions and map out/outline your answers

Jot down the big ideas and main terms

Outline your answer to organize your thoughts

Underline important terms and power verbs in the question

Use the 80 minutes to write thorough responses to all eight questions

Stay focused on what the prompt is requiring you to do

Use the outline, mindmap, or bullet points developed during the reading time

Write legibly using black ink

Answer in the format of the question

Use scientific language, depth, elaboration, and examples

Use graphs or diagrams when it enhances the essay response

Clearly mark the answer sheet with the free response question being answered

Answer all subunits of a question thoroughly

Label all graphs correctly

Use the time at the end to re-read responses and check for clarity, accuracy, and thoroughness

# Page 10:

Don't obsess over correct grammar

Don't write introductory or closing paragraphs

Don't ramble, get to the point

Don't write only in outline format, use complete sentences

Don't over-answer the sub-questions of a free response question

Don't leave any free response questions blank

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Data analysis is important to determine the validity of observed patterns

Descriptive and inferential statistics are used in AP Biology lab data analysis

Descriptive statistics estimate important parameters of the sample data set

Inferential statistics rely on probability theory to determine precise estimates of true population parameters

Most AP Biology experiments collect parametric data, which follows a normal distribution

Mean, sample size, standard deviation, and standard error are important descriptive statistics for a normal distribution

Standard deviation measures the spread or variance in the sample population

Interpretation of standard deviation is important, but calculation may not be required on the exam

Data points within ±1 standard deviation from the mean account for about two-thirds of the data

More than 95% of the data falls within ±2 standard deviations from the mean

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Sample standard error (SEx) allows students to make inferences about how well the sample mean matches up to the true population mean.

Standard error of the mean uses the standard deviation of the sample and the sample size to estimate how closely the sample data approximates the data that would be collected if the entire population were measured.

Taking a large number of samples (at least 30) from a population would form an approximately normal distribution of sample means.

The distribution of sample means helps define the boundaries of confidence in the sample.

Standard error is the equivalent of the standard deviation of the sampling distribution of the means and is calculated using a specific formula.

An interval within ±1 SEx of the sample mean describes the range of values with approximately 67% confidence that the range includes the true population mean.

An interval within ±2 SEx of the sample mean defines a range of values with approximately 95% certainty that the true population mean falls within the interval.

The 95% confidence interval technique is an inference that allows investigators to gauge the reliability of their estimate of the true population mean.

The larger the sample size, the smaller the standard error and the more confident the researcher can be about the reliability of the data.

Error bars are used to construct graphs showing the mean values of data sets.

The error bars usually show the range 2 standard errors above and 2 below the mean value.

To create a graph with error bars, graph the means of each data set using a bar chart and draw horizontal lines representing the confidence interval.

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The vertical space between the two horizontal lines represents a 95% confidence interval.

Error bars can be used to determine if the difference between two groups/samples is statistically significant.

When error bars overlap, the difference between the two groups is likely not statistically significant.

If there is no overlap between the error bars, the differences between the two groups are likely to be statistically significant.

The data from Peter and Rosemary Grant's research on finches in the Galápagos Islands is used as an example.

The mean beak depth after the drought was different in a statistically significant amount from the beak depth before the drought.

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The data table shows the change in beak depth of a population of finches following a drought year.

The table includes the band numbers (names for individual birds), beak depth before and after the drought, and descriptive statistics.

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The data from the table is graphed as a bar chart of the means with error bars representing a 95% confidence interval.

The mean beak depth after the drought was different in a statistically significant amount from the beak depth before the drought.

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Instructions on how to add error bars to an Excel graph are provided.

A bar chart is shown with the mean beak depth for the two conditions.

# Page 17: Hypothesis Testing

A hypothesis is a statement explaining a causal relationship between a factor and a phenomenon

Statistical hypothesis testing focuses on rejecting a null hypothesis

Null hypothesis (H0) states that there is no causal relationship or difference between variables

Alternative hypothesis (HA) is the hypothesis that opposes the null hypothesis

Hypothesis testing does not prove or accept the alternative hypothesis, it only determines if there is enough evidence to reject the null hypothesis

Types of statistical tests: chi square analysis and t-test

# Page 18: Chi Square Analysis

Chi square analysis compares observed and expected data

Used to compare two or more categories of data, not averages

Used to test genetic crosses, gene frequencies, and other theoretical expectations

Goal is to determine if the variation in results from expected values is due to chance

Can be used to confirm or reject the null hypothesis

# Page 19: Calculating Chi Square

Example problem: testing if pillbugs have a preference for wet or dry environments

Null hypothesis: no preference for either wet or dry

Phenotypes or groups: "wet" and "dry"

Expected values: 10 on each side

Observed values: 14 on wet side, 6 on dry side

Calculate chi square statistic by summing the last column in the table

In this case, chi square is equal to 3.2

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Two ways to interpret the meaning of the chi square statistic

Compare it to a critical value

Use the chi square table to find the critical value

Degrees of freedom = number of phenotypes/categories minus one

Use 0.05 significance level in Biology

Significance level (alpha) is the probability of rejecting the null hypothesis when it is true

Significance level of 0.05 indicates a 5% risk of concluding a difference exists when there is none

Use 0.05 significance level and 1 degree of freedom to find a critical value of 3.84

If chi square statistic is greater than critical value, reject null hypothesis

If chi square statistic is less than critical value, fail to reject null hypothesis

Use the p-value approach

Move along row 1 in the chi square distribution table to find chi square value of 3.2

Chi square value is between 0.10 and 0.05 columns

P-value for this data is between 0.10 and 0.05

P-value is the probability of whether the results differ from null results by chance alone

P-value of 0.05 means a 5% chance that the difference is real and repeatable

If p-value is greater than 0.05, fail to reject null hypothesis

If p-value is less than 0.05, reject null hypothesis

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t-Test

Used to determine if mean of one population significantly differs from mean of another population

Useful for comparing means of control and experimental groups

Assume data is parametric and samples are independent

Example: comparing mean number of trichomes in different fast plant generations

Null hypothesis: mean number of trichomes in generation 2 sample is same as mean of generation 1 sample

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Calculation steps for t-test

Calculate mean of each sample population and subtract one from the other

Calculate standard error (SE) by calculating variance (S^2) of each sample and dividing by sample size (n)

Divide difference between means by standard error to get t-statistic

Compare calculated value to critical t-value in table

Critical values for different degrees of freedom at significance value of 0.05

If calculated t-value is greater than critical t-value, reject null hypothesis

If calculated t-value is smaller than critical t-value, fail to reject null hypothesis

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Another way to interpret t-test data using p-values

Move along row 12 in t distribution table to find t value of 2.9417

T value is between 0.02 and 0.01 columns

P-value for this data is between 0.02 and 0.01

If p-value is greater than 0.05, fail to reject null hypothesis

If p-value is less than 0.05, reject null hypothesis

T-test calculations can be done with Excel, TI calculator, or Google Sheets

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Excel calculates a T-test in a different way

Excel gives the probability that the means are different due to chance (P value)

Steps to calculate a P value using a t-test with Excel:

Create two columns for the data of interest

Click on a blank cell for the P value to appear

Click "fx" on the Excel Formulas toolbar

Search for the "T test" function and choose "T.TEST"

Set the t-test parameters: highlight data for each sample, enter "2" for "Tails", select the appropriate "Type"

Click "OK" and the P value will appear

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P value meaning in Excel

P value represents the likelihood that the difference in means is due to random chance

P value of 0.22 means a 22% likelihood of difference due to random chance

Significance of P value

P value of .05 or less indicates significant differences between the two groups

P value greater than 0.05 means no significant difference between the two groups

Steps to perform a T-test with the TI-83/84 calculator

Press the STAT button

Select option 4 to clear past data lists

Select option 1 to edit lists

Enter data for each group as List 1 and List 2

Press the STAT button and go to the TESTS option

Scroll to option 4, the 2-sample T test, and press ENTER

Press ENTER over the CALCULATE option to get results

Compare the calculated t-statistic to the critical value from the table

Reject the null hypothesis if the t statistic is greater than the critical value

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Steps to perform a t-test with Google Sheets

Enter data from two samples in separate columns

Use the formula =TTEST(A1:A4, B1:B4, 2, 2) with appropriate data ranges

P-value is given, reject null hypothesis if p-value is less than 0.05

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Covalent Bonds

Intramolecular bond resulting from sharing valence electrons between atoms

Atoms held together by covalent bonds are called molecules

Polar Molecules

Carry a slight electrical charge at opposite poles

Non-polar molecules do not have an electrical charge

Electronegativity

Atom's desire to acquire electrons

Hydrogen is the least electronegative atom

Oxygen and Nitrogen are biologically important with high electronegativity

Ionic Bonds

Form between metal and non-metal atoms

Metal atoms lose electrons, non-metal atoms gain electrons to have 8 valence electrons

Compounds held together by ionic bonds are called salts

Hydrogen Bonds

Weak intermolecular attractions between polar molecules

Important in water due to its polar nature

Van der Waals Interactions or London Dispersion Forces

Temporary intermolecular attractions due to clumping of electrons on one side of an atom

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Water supports life on Earth

Water makes up over 70% of most organisms' bodies

Biogeochemical Cycles

Cycling of matter

Water cycle

Water vapor generated by the sun causes evaporation from various sources

Condenses to form precipitation and returns to land or ocean

Plants take in water for photosynthesis and lose it through transpiration

Water is a polar molecule

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Water molecule has a slight negative charge on the oxygen end and a slight positive charge on the hydrogen end

Water molecule's shape is "bent" with a positive hydrogen side and a negative oxygen side

Water molecules form hydrogen bonds with each other

Water has high specific heat due to hydrogen bonds, which helps maintain constant body temperature

Water is an excellent solvent, especially for salts and polar molecules

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Water has high heat of vaporization due to hydrogen bonds

Evaporative cooling allows processes like sweating and transpiration to cool off organisms

Water is cohesive and adhesive, allowing it to stick to other water molecules and polar molecules

Water expands as it freezes, making ice less dense than liquid water and allowing it to float

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Carbon is the element that makes up most compounds found in living things

Carbon is abundant on Earth and is the building block of life

Organic macromolecules include carbohydrates, lipids, proteins, and nucleic acids

Carbon dioxide is the original source of carbon in all life forms

Miller/Urey experiment showed that organic molecules could be created by non-living things

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Carbon has 4 valence electrons, allowing it to form four covalent bonds and create a variety of shapes and functions

Carbon is an excellent building material for life due to its strong covalent bonds

Macromolecules are formed by combining individual units called monomers through dehydration synthesis

Macromolecules are broken apart into monomers by hydrolysis reactions

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Carbohydrates are sugars and serve as sources of quick energy and structural materials

Monosaccharides are the building blocks of carbohydrates, with glucose, fructose, and ribose being common examples

Polysaccharides are formed by bonding several monosaccharides together, including starch, glycogen, and cellulose

Cellulose is the most abundant organic compound on Earth and is difficult to digest

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Lipids are fats, oils, waxes, and steroids, and are mostly hydrophobic

Lipids consist of fatty acids and a glycerol molecule held together by ester linkages

Major types of lipids include triglycerides, saturated fats, unsaturated fats, and polyunsaturated fats

Hydrogenated or trans fats are solid fats created by adding hydrogen and breaking double or triple bonds, and are associated with health issues

# Page 35

Phospholipids replace a fatty acid chain with a phosphate ion

Phosphate portion is hydrophilic

Fatty acid chains are hydrophobic

Phospholipids are amphipathic with polar and nonpolar sides

Phospholipid bilayers are important for cell and organelle membranes

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Steroids are lipids composed of 4 carbon rings

Common steroids include testosterone, estrogen, progesterone, and cholesterol

Functional groups attached to steroids determine their function

Steroids function as cell signals/hormones and can penetrate cell membranes

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Proteins make up over 50% of an organism's dry weight

Proteins are composed of amino acids

There are 20 different amino acids used to make proteins

Amino acids have four parts: carboxyl end, amine end, alpha carbon, and R group

Amino acids are bonded together by peptide bonds

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Two amino acids bonded together are a dipeptide

More than two bonded amino acids form a polypeptide chain

Proteins are made from several polypeptide chains

Protein function is determined by its shape/structure

Four levels of protein structure: primary, secondary, tertiary, and quaternary

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Tertiary structure refers to the overall shape of an individual polypeptide chain

Disulfide bridges and ionic interactions stabilize the folded structure

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Quaternary structure is formed when two or more polypeptides are woven together

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Denaturation is the unfolding of a protein or enzyme, causing loss of function

Denaturation can be caused by pH changes, salt concentration changes, and temperature increases

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Nitrogen cycle is the process of nitrogen moving from the atmosphere to living things and back

Nitrogen is essential for proteins, amino acids, DNA, RNA, and ATP

Nitrogen fixation converts nitrogen gas into ammonium ions

Nitrification converts ammonium ions into nitrite and then nitrate

Denitrification converts nitrates back into oxygen and nitrogen gas

Ammonification converts ammonia into ammonium

Nitrogen is released through decomposition and animal urine

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Nucleic Acids function to store genetic information and/or to store and transfer energy.

Common nucleic acids found in living organisms include: DNA, RNA, ATP, cAMP, NADH, and NADPH.

The monomers of nucleic acids are called nucleotides.

A nucleotide consists of a 5 carbon (pentose) sugar bonded to a phosphate group and a nitrogenous base.

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DNA and mRNA are both polymers.

DNA and RNA are the primary sources of genes and hereditary information.

DNA has Deoxyribose as its 5 Carbon sugar.

DNA is double stranded.

In eukaryotic cells, DNA is always stored inside a nuclear membrane or envelope.

DNA's function is to code for proteins.

The sequence of the nitrogenous bases in the DNA determines the order of the amino acids in each of the body's proteins.

RNA has Ribose as its 5 Carbon sugar.

RNA is single stranded.

There are several types of RNA.

Messenger RNA (mRNA) is made from the DNA template during the process of transcription.

mRNA's job is to transmit the protein building directions from the DNA in the nucleus to the ribosomes in the cytoplasm.

Transfer RNA's (tRNA) job is to deliver and place the appropriate amino acids into the proteins that are built by the ribosomes.

Ribosomal RNA (rRNA) is one of the main building components of the cell's ribosomes.

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Scientists can now sequence the nucleotide/nitrogenous bases found in genes of an organism and compare this sequence to the sequence of the same gene found in another organism.

The more similar the two sequences are, the more related the two organisms are.

ATP (Adenosine Triphosphate) is another important nucleic acid.

An ATP molecule is composed of a single nucleotide which consists of the sugar (ribose) bonded to a nitrogenous base (always adenine), and three phosphate groups.

ATP's role in the body is to store and transfer energy.

ATP is made during the process of cellular respiration.

It functions to power almost every activity that occurs in the cell.

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The phosphorus cycle is another important biogeochemical cycle.

Phosphorus is an important component of DNA, RNA, ATP, and bone.

Most of the Earth's phosphorus is found in rock.

As the rock weathers, some of the phosphorus is released into the soil.

Some dissolves into the water as the rains pass through the soil.

This phosphorus makes its way into bodies of water and is available for producers (phytoplankton) to use to make organic compounds such as phospholipids, DNA, RNA, ATP, etc...

Plants can also retrieve the phosphorus directly from the soil and use it

# AP Bio Unit 1 Complete Student Notes Flashcards

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AP Biology Unit 1 Student Notes

Table of Contents Link

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Table of Contents

A. Scientific Method/Experimental Design—Pages 3-5

B. Graphing—Pages 5-6

C. Free Response Writing Tips—Pages 7-9

D. Data Analysis/Statistics—Pages 10-25

E. Graphs With Error Bars—Pages 12-16

F. Hypothesis Testing—Pages 16-25

G. Chi Square Analysis—Pages 16-19

H. t-tests—Pages 20-24

I. Chemistry Basics—Pages 25-26

J. Biochemistry of Water—Pages 27-29

K. Biochemistry of Carbon—Pages 30-31

L. Carbohydrates—Page 32

M. Lipids—Pages 32-35

N. Proteins—Pages 35-39

O. Nitrogen Cycle—Pages 39-40

P. Nucleic Acids—Pages 41-43

Q. Phosphorus Cycle—Pages 43-44

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## Unit 1 Student Notes Content Outline: The Scientific Method

The Scientific Method

Series of steps followed to solve problems

Steps are not always the same for each question

Step 1: State your Problem/Question

Develop a question or problem that can be solved through experimentation

Make sure it is something that interests you

Step 2: Make Observations/Do Research

Make observations

Qualitative observations

Quantitative observations

Inferences

Predictions

Do research

Literature research, not lab-based research

Step 3: Formulate a Hypothesis

A hypothesis is a prediction or possible answer to the problem or question

Relationship between the Independent variable and Dependent variables

Step 4: Experiment

Develop and follow a procedure that anyone can follow

Use precise directions

Include a detailed materials list

The experiment must have a control group

Experimental group(s) and constants

Step 5: Collect Data

Write down results as you perform the experiment

Qualitative Data

Quantitative Data

Step 6: Analyze Data

Confirm the results by retesting

Trials

Convert results to a graph

Use descriptive and inferential statistics

Step 7: Conclusion

The written results of the experiment

Statement if the hypothesis was supported or refuted

Recommendations for further study and improvements

Step 8: Communicate Results

Be prepared to present the project to an audience

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Graphing

Graphs and charts communicate information visually

Independent variable on the x-axis

Dependent variable on the y-axis

Label both axes and include units

Provide a descriptive title

Use the pattern "The Effect of the independent variable on the dependent variable"

Plotting data points without drawing a line

# Page 5:

Graphing (continued)

DRY MIX mnemonic for remembering the pattern of labeling axes

Enclose the unit in parentheses

Descriptive title for the graph

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Use the ten minute reading time advantageously

Read all of the free response questions and map out/outline your answers

Jot down the big ideas and main terms

Outline your answer to organize your thoughts

Underline important terms and power verbs in the question

Use the 80 minutes to write thorough responses to all eight questions

Stay focused on what the prompt is requiring you to do

Use the outline, mindmap, or bullet points developed during the reading time

Write legibly using black ink

Answer in the format of the question

Use scientific language, depth, elaboration, and examples

Use graphs or diagrams when it enhances the essay response

Clearly mark the answer sheet with the free response question being answered

Answer all subunits of a question thoroughly

Label all graphs correctly

Use the time at the end to re-read responses and check for clarity, accuracy, and thoroughness

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Don't obsess over correct grammar

Don't write introductory or closing paragraphs

Don't ramble, get to the point

Don't write only in outline format, use complete sentences

Don't over-answer the sub-questions of a free response question

Don't leave any free response questions blank

# Page 11:

Data analysis is important to determine the validity of observed patterns

Descriptive and inferential statistics are used in AP Biology lab data analysis

Descriptive statistics estimate important parameters of the sample data set

Inferential statistics rely on probability theory to determine precise estimates of true population parameters

Most AP Biology experiments collect parametric data, which follows a normal distribution

Mean, sample size, standard deviation, and standard error are important descriptive statistics for a normal distribution

Standard deviation measures the spread or variance in the sample population

Interpretation of standard deviation is important, but calculation may not be required on the exam

Data points within ±1 standard deviation from the mean account for about two-thirds of the data

More than 95% of the data falls within ±2 standard deviations from the mean

# Page 12:

Sample standard error (SEx) allows students to make inferences about how well the sample mean matches up to the true population mean.

Standard error of the mean uses the standard deviation of the sample and the sample size to estimate how closely the sample data approximates the data that would be collected if the entire population were measured.

Taking a large number of samples (at least 30) from a population would form an approximately normal distribution of sample means.

The distribution of sample means helps define the boundaries of confidence in the sample.

Standard error is the equivalent of the standard deviation of the sampling distribution of the means and is calculated using a specific formula.

An interval within ±1 SEx of the sample mean describes the range of values with approximately 67% confidence that the range includes the true population mean.

An interval within ±2 SEx of the sample mean defines a range of values with approximately 95% certainty that the true population mean falls within the interval.

The 95% confidence interval technique is an inference that allows investigators to gauge the reliability of their estimate of the true population mean.

The larger the sample size, the smaller the standard error and the more confident the researcher can be about the reliability of the data.

Error bars are used to construct graphs showing the mean values of data sets.

The error bars usually show the range 2 standard errors above and 2 below the mean value.

To create a graph with error bars, graph the means of each data set using a bar chart and draw horizontal lines representing the confidence interval.

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The vertical space between the two horizontal lines represents a 95% confidence interval.

Error bars can be used to determine if the difference between two groups/samples is statistically significant.

When error bars overlap, the difference between the two groups is likely not statistically significant.

If there is no overlap between the error bars, the differences between the two groups are likely to be statistically significant.

The data from Peter and Rosemary Grant's research on finches in the Galápagos Islands is used as an example.

The mean beak depth after the drought was different in a statistically significant amount from the beak depth before the drought.

# Page 14:

The data table shows the change in beak depth of a population of finches following a drought year.

The table includes the band numbers (names for individual birds), beak depth before and after the drought, and descriptive statistics.

# Page 15:

The data from the table is graphed as a bar chart of the means with error bars representing a 95% confidence interval.

# Page 16:

Instructions on how to add error bars to an Excel graph are provided.

A bar chart is shown with the mean beak depth for the two conditions.

# Page 17: Hypothesis Testing

A hypothesis is a statement explaining a causal relationship between a factor and a phenomenon

Statistical hypothesis testing focuses on rejecting a null hypothesis

Null hypothesis (H0) states that there is no causal relationship or difference between variables

Alternative hypothesis (HA) is the hypothesis that opposes the null hypothesis

Hypothesis testing does not prove or accept the alternative hypothesis, it only determines if there is enough evidence to reject the null hypothesis

Types of statistical tests: chi square analysis and t-test

# Page 18: Chi Square Analysis

Chi square analysis compares observed and expected data

Used to compare two or more categories of data, not averages

Used to test genetic crosses, gene frequencies, and other theoretical expectations

Goal is to determine if the variation in results from expected values is due to chance

Can be used to confirm or reject the null hypothesis

# Page 19: Calculating Chi Square

Example problem: testing if pillbugs have a preference for wet or dry environments

Null hypothesis: no preference for either wet or dry

Phenotypes or groups: "wet" and "dry"

Expected values: 10 on each side

Observed values: 14 on wet side, 6 on dry side

Calculate chi square statistic by summing the last column in the table

In this case, chi square is equal to 3.2

# Page 20:

Two ways to interpret the meaning of the chi square statistic

Compare it to a critical value

Use the chi square table to find the critical value

Degrees of freedom = number of phenotypes/categories minus one

Use 0.05 significance level in Biology

Significance level (alpha) is the probability of rejecting the null hypothesis when it is true

Significance level of 0.05 indicates a 5% risk of concluding a difference exists when there is none

Use 0.05 significance level and 1 degree of freedom to find a critical value of 3.84

If chi square statistic is greater than critical value, reject null hypothesis

If chi square statistic is less than critical value, fail to reject null hypothesis

Use the p-value approach

Move along row 1 in the chi square distribution table to find chi square value of 3.2

Chi square value is between 0.10 and 0.05 columns

P-value for this data is between 0.10 and 0.05

P-value is the probability of whether the results differ from null results by chance alone

P-value of 0.05 means a 5% chance that the difference is real and repeatable

If p-value is greater than 0.05, fail to reject null hypothesis

If p-value is less than 0.05, reject null hypothesis

# Page 21:

t-Test

Used to determine if mean of one population significantly differs from mean of another population

Useful for comparing means of control and experimental groups

Assume data is parametric and samples are independent

Example: comparing mean number of trichomes in different fast plant generations

Null hypothesis: mean number of trichomes in generation 2 sample is same as mean of generation 1 sample

# Page 22:

Calculation steps for t-test

Calculate mean of each sample population and subtract one from the other

Calculate standard error (SE) by calculating variance (S^2) of each sample and dividing by sample size (n)

Divide difference between means by standard error to get t-statistic

Compare calculated value to critical t-value in table

Critical values for different degrees of freedom at significance value of 0.05

If calculated t-value is greater than critical t-value, reject null hypothesis

If calculated t-value is smaller than critical t-value, fail to reject null hypothesis

# Page 23:

Another way to interpret t-test data using p-values

Move along row 12 in t distribution table to find t value of 2.9417

T value is between 0.02 and 0.01 columns

P-value for this data is between 0.02 and 0.01

If p-value is greater than 0.05, fail to reject null hypothesis

If p-value is less than 0.05, reject null hypothesis

T-test calculations can be done with Excel, TI calculator, or Google Sheets

# Page 24:

Excel calculates a T-test in a different way

Excel gives the probability that the means are different due to chance (P value)

Steps to calculate a P value using a t-test with Excel:

Create two columns for the data of interest

Click on a blank cell for the P value to appear

Click "fx" on the Excel Formulas toolbar

Search for the "T test" function and choose "T.TEST"

Set the t-test parameters: highlight data for each sample, enter "2" for "Tails", select the appropriate "Type"

Click "OK" and the P value will appear

# Page 25:

P value meaning in Excel

P value represents the likelihood that the difference in means is due to random chance

P value of 0.22 means a 22% likelihood of difference due to random chance

Significance of P value

P value of .05 or less indicates significant differences between the two groups

P value greater than 0.05 means no significant difference between the two groups

Steps to perform a T-test with the TI-83/84 calculator

Press the STAT button

Select option 4 to clear past data lists

Select option 1 to edit lists

Enter data for each group as List 1 and List 2

Press the STAT button and go to the TESTS option

Scroll to option 4, the 2-sample T test, and press ENTER

Press ENTER over the CALCULATE option to get results

Compare the calculated t-statistic to the critical value from the table

Reject the null hypothesis if the t statistic is greater than the critical value

# Page 26:

Steps to perform a t-test with Google Sheets

Enter data from two samples in separate columns

Use the formula =TTEST(A1:A4, B1:B4, 2, 2) with appropriate data ranges

P-value is given, reject null hypothesis if p-value is less than 0.05

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Covalent Bonds

Intramolecular bond resulting from sharing valence electrons between atoms

Atoms held together by covalent bonds are called molecules

Polar Molecules

Carry a slight electrical charge at opposite poles

Non-polar molecules do not have an electrical charge

Electronegativity

Atom's desire to acquire electrons

Hydrogen is the least electronegative atom

Oxygen and Nitrogen are biologically important with high electronegativity

Ionic Bonds

Form between metal and non-metal atoms

Metal atoms lose electrons, non-metal atoms gain electrons to have 8 valence electrons

Compounds held together by ionic bonds are called salts

Hydrogen Bonds

Weak intermolecular attractions between polar molecules

Important in water due to its polar nature

Van der Waals Interactions or London Dispersion Forces

Temporary intermolecular attractions due to clumping of electrons on one side of an atom

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Water supports life on Earth

Water makes up over 70% of most organisms' bodies

Biogeochemical Cycles

Cycling of matter

Water cycle

Water vapor generated by the sun causes evaporation from various sources

Condenses to form precipitation and returns to land or ocean

Plants take in water for photosynthesis and lose it through transpiration

Water is a polar molecule

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Water molecule has a slight negative charge on the oxygen end and a slight positive charge on the hydrogen end

Water molecule's shape is "bent" with a positive hydrogen side and a negative oxygen side

Water molecules form hydrogen bonds with each other

Water has high specific heat due to hydrogen bonds, which helps maintain constant body temperature

Water is an excellent solvent, especially for salts and polar molecules

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Water has high heat of vaporization due to hydrogen bonds

Evaporative cooling allows processes like sweating and transpiration to cool off organisms

Water is cohesive and adhesive, allowing it to stick to other water molecules and polar molecules

Water expands as it freezes, making ice less dense than liquid water and allowing it to float

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Carbon is the element that makes up most compounds found in living things

Carbon is abundant on Earth and is the building block of life

Organic macromolecules include carbohydrates, lipids, proteins, and nucleic acids

Carbon dioxide is the original source of carbon in all life forms

Miller/Urey experiment showed that organic molecules could be created by non-living things

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Carbon has 4 valence electrons, allowing it to form four covalent bonds and create a variety of shapes and functions

Carbon is an excellent building material for life due to its strong covalent bonds

Macromolecules are formed by combining individual units called monomers through dehydration synthesis

Macromolecules are broken apart into monomers by hydrolysis reactions

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Carbohydrates are sugars and serve as sources of quick energy and structural materials

Monosaccharides are the building blocks of carbohydrates, with glucose, fructose, and ribose being common examples

Polysaccharides are formed by bonding several monosaccharides together, including starch, glycogen, and cellulose

Cellulose is the most abundant organic compound on Earth and is difficult to digest

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Lipids are fats, oils, waxes, and steroids, and are mostly hydrophobic

Lipids consist of fatty acids and a glycerol molecule held together by ester linkages

Major types of lipids include triglycerides, saturated fats, unsaturated fats, and polyunsaturated fats

Hydrogenated or trans fats are solid fats created by adding hydrogen and breaking double or triple bonds, and are associated with health issues

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Phospholipids replace a fatty acid chain with a phosphate ion

Phosphate portion is hydrophilic

Fatty acid chains are hydrophobic

Phospholipids are amphipathic with polar and nonpolar sides

Phospholipid bilayers are important for cell and organelle membranes

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Steroids are lipids composed of 4 carbon rings

Common steroids include testosterone, estrogen, progesterone, and cholesterol

Functional groups attached to steroids determine their function

Steroids function as cell signals/hormones and can penetrate cell membranes

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Proteins make up over 50% of an organism's dry weight

Proteins are composed of amino acids

There are 20 different amino acids used to make proteins

Amino acids have four parts: carboxyl end, amine end, alpha carbon, and R group

Amino acids are bonded together by peptide bonds

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Two amino acids bonded together are a dipeptide

More than two bonded amino acids form a polypeptide chain

Proteins are made from several polypeptide chains

Protein function is determined by its shape/structure

Four levels of protein structure: primary, secondary, tertiary, and quaternary

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Tertiary structure refers to the overall shape of an individual polypeptide chain

Disulfide bridges and ionic interactions stabilize the folded structure

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Quaternary structure is formed when two or more polypeptides are woven together

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Denaturation is the unfolding of a protein or enzyme, causing loss of function

Denaturation can be caused by pH changes, salt concentration changes, and temperature increases

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Nitrogen cycle is the process of nitrogen moving from the atmosphere to living things and back

Nitrogen is essential for proteins, amino acids, DNA, RNA, and ATP

Nitrogen fixation converts nitrogen gas into ammonium ions

Nitrification converts ammonium ions into nitrite and then nitrate

Denitrification converts nitrates back into oxygen and nitrogen gas

Ammonification converts ammonia into ammonium

Nitrogen is released through decomposition and animal urine

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Nucleic Acids function to store genetic information and/or to store and transfer energy.

Common nucleic acids found in living organisms include: DNA, RNA, ATP, cAMP, NADH, and NADPH.

The monomers of nucleic acids are called nucleotides.

A nucleotide consists of a 5 carbon (pentose) sugar bonded to a phosphate group and a nitrogenous base.

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DNA and mRNA are both polymers.

DNA and RNA are the primary sources of genes and hereditary information.

DNA has Deoxyribose as its 5 Carbon sugar.

DNA is double stranded.

In eukaryotic cells, DNA is always stored inside a nuclear membrane or envelope.

DNA's function is to code for proteins.

The sequence of the nitrogenous bases in the DNA determines the order of the amino acids in each of the body's proteins.

RNA has Ribose as its 5 Carbon sugar.

RNA is single stranded.

There are several types of RNA.

Messenger RNA (mRNA) is made from the DNA template during the process of transcription.

mRNA's job is to transmit the protein building directions from the DNA in the nucleus to the ribosomes in the cytoplasm.

Transfer RNA's (tRNA) job is to deliver and place the appropriate amino acids into the proteins that are built by the ribosomes.

Ribosomal RNA (rRNA) is one of the main building components of the cell's ribosomes.

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Scientists can now sequence the nucleotide/nitrogenous bases found in genes of an organism and compare this sequence to the sequence of the same gene found in another organism.

The more similar the two sequences are, the more related the two organisms are.

ATP (Adenosine Triphosphate) is another important nucleic acid.

An ATP molecule is composed of a single nucleotide which consists of the sugar (ribose) bonded to a nitrogenous base (always adenine), and three phosphate groups.

ATP's role in the body is to store and transfer energy.

ATP is made during the process of cellular respiration.

It functions to power almost every activity that occurs in the cell.

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The phosphorus cycle is another important biogeochemical cycle.

Phosphorus is an important component of DNA, RNA, ATP, and bone.

Most of the Earth's phosphorus is found in rock.

As the rock weathers, some of the phosphorus is released into the soil.

Some dissolves into the water as the rains pass through the soil.

This phosphorus makes its way into bodies of water and is available for producers (phytoplankton) to use to make organic compounds such as phospholipids, DNA, RNA, ATP, etc...

Plants can also retrieve the phosphorus directly from the soil and use it