Portfolio and Stats
Lab Portfolio Formatting
Topics – Expt. Design
The IB Portfolio
The IB portfolio includes evidence for all laboratory work sessions: 40 hours SL or 60 hours HL .
All lab work b) problem solving c) dry labs d) formal labs e) partial labs
FORMAT
Word process (1.5 space) Times new roman 11 point font
Microsoft Excel for: Graphs, tables, statistics
Word can do tables if you have trouble
Include in your portfolio: lab handouts, instructions, notes, log of lab activities, write-ups.
Quick Tips
Treat each lab as practice for the internal assessment
Maximize use of time in class
Turn in only COMPLETE labs
Always think about what your results actually mean
The process is just as important as the end product.
REMEMBER TO KEEP YOUR PORTFOLIO UP TO DATE – QUARTERLY NOTEBOOK CHECKS !!
IB Internal Assessment
Internal Assessment consists of 2 complete labs (Bio = 1 full and 2 partials, Enviro = 4 partials)
You will complete 2 required labs with an option of a 3rd (science fair)
Internal Assessment is 23% of your final IB Biology or IB Environmental score
Remember: You have full control over this portion of your IB test score
Use the following as a format guide for your IA
Remember: Samples will differ slightly from this format
Everything underlined here should appear as an underlined heading in your lab – Refer to the hand out for reference
Name School
Class / Period Dates planning
Lab Partners execution
Use a meaningful, descriptive title of your own creation
Background
*Information that lead to your question
*Background info and Observations
*Include at least two parenthetical references e.g. (Campbell, p. 245) or (Platt, 2001)
*Must have enough info to support problem and hypothesis
*FUNNEL THE READER INTO YOUR EXPERIMENT
(1/2 page maximum)
Design
Problem: Frequently a question
What is the effect of ______on ______?
e.g. What is the effect of seasonal changes in rainfall on the reproduction of tree frogs?
Hypothesis:
Based on preliminary info
Be as quantitative as possible
State as If…Then… & Because
e.g. If there is less than 20 cm of rain in a particular season then tree frogs will not reproduce.
This will happen because 20cm of rainfall is the minimum to leave standing water in pools for
the eggs to float.
Variables
(list them as follows)
Independent variable = Parts of the experiment that the scientist changes
= e.g. amount of rainfall frogs receive
Dependent variable = Variable that is being measured (its changes are measured) and how it is measured
= e.g. size of eggs produced (measured in cm with calipers)
Controlled variable = What is kept the same throughout the experiment – include as many as possible & be sure you explain how and why here
= e.g. temp, food supply, age, time of year, etc …
Materials
must be a COMPLETE list
with an explanation of how each item is used in the experiment
Be specifics on sizes, concentrations, etc.
(include safety equipment)
Experimental Set up
Photographs with labels showing ongoing experiment with all apparatus including safety equipment
A drawing is acceptable if it is detailed and complete
Procedures:
numbered steps – complete enough to be replicated exactly by another person
Include replications
Must include method of data analysis, technology used and tests completed
Safety: steps taken for safety in the lab
e.g.
Data Collection and Processing
(All results should stand alone)
Raw Data Table
organize in excel or word chart with lines sig. figs., labels, replicates, units, titles, uncertainties
Raw Data Graph
typically a bar graph showing individual measurements – remember title, axis labels, units, scale,
Observations
qualitative observations made during experiment
Data Processing
Overview – explains how you will analyze the data (T-test – 1 or 2 tailed - or Linear regression)
Explains why you chose that test
Calculations
Sample calculations for each manipulation you do of the raw data
Minimum will include – mean, standard deviation, T-test or Linear regression
Include formula with your #’s plugged in – if repetitive may include “…”
Need even if using excel or calculator for it
Presentation
Another 2 tables –
descriptive stats (mean, med. mode), Standard Deviation, other stats, etc.
Statistical test results
T-test = df, T value, p value
Linear Regression = df, critical r value, r value
must be your own presentation not an excel output table
Graph correct type (bar graph for T-test, scatterplot with trendline for Linear Regression)
label axes, units, title, central tendency and range
Example of graphs
Graphs/Figures
Type meaningful title
Label axes with units
Do 1 representation of raw data
Do 2nd for the transformed data (means with error bars).
e.g. Frogs:
One graph showing pairs of individual frog data (rainfall, eggs per frog)
One showing Average rainfall (as bar graph) and Average eggs produced (bar graphs)
One showing scatter plot of X (rainfall) and Y (eggs) plots with trend line, r value, linear equation
Conclusion
(must have 3 things) (about 1/2 page)
1. Compare results to initial hypothesis – Were you right or wrong?
2. Restate numerical information important to your conclusion – graphs and stats info
What do your results show or mean?
WHY did the expt. turn out the way it did?
3. You must include a biological explanation for the results you found
Citations must be used here as well – what was supposed to happen? Why was yours the same or different (at least 2 references)
Evaluation
(about 1/2 page)
Critically evaluate the quality of your data, procedures, etc.
Variability? Reliability? Error Sources?
You must discuss standard deviation as a numerical estimate of error or variability
Systematic Error – based on your manipulation
Random error – nature is variable
Improvements:
Suggest improvements for procedures & data collection
Must have at least 3 improvements relating to evaluation issues
E.g. increased sample size, increased number of replicates, longer sampling times, better controls (same age, gender) etc., better accuracy in measurement.
DO NOT design a different experiment (toads, different time of day, food available). Work with what you have started with.
Works Cited
Minimum of two references – probably 4
Use proper MLA format, refer to handout or reference the internet
END OF LABORATORY REPORT
Skills Assessment
The following will be assessed by the teacher during the lab activity and from the write-up. It reflects 12/48 points on your final IA grade
Manipulative skills: Graded Summatively across all labs
6 points total
Were all instructions followed?
Were procedures carried out efficiently with Proper recording of lab activities?
Was everything done in a safe Manner?
Personal skills: Assessed on Jan 9th at Group 4 and included everything this activity encompasses
6 points total for this one activity
Worked effectively within a team
Recognized and encouraged contributions of others
Self motivation and perseverance
Ethics – honesty, integrity of data, citing of sources
Attention to environmental impact
Skills Assessment Automatic Deductions
Manipulative skills:
Safety concerns
does not demonstrate proper techniques
not recording data during or by the end of the lab period
Failure to approach lab activities with due diligence
failing to clean up after lab
Not analyzing data properly
Perpetually late labs
Improper citations
Personal skills / Group 4
Safety concerns
Problems with completing activities on time line
lack of effort or behavioural issues
Any cheating or plagarism will result in a grade of 0 on the entire lab
Any cheating or plagarism will result in a grade of 0 on the entire lab
Did I mention that …
Thoughts on Experimental Design
Designing a Good Experiment
1. Replication – do it enough to show that the result is not a chance occurrence
2. Control & Constants – ensure that you know what is the cause of the effect you see
I.V. is the manipulated variable (treatments)
3. Data collection – plan for the type of data you want to collect
Be precise and meticulous in your collection of data
4. Data analysis – is your result significant?
Statistical tests, graphical analysis, what does it actually show (beyond the #’s)
5. What does it all mean
Why did it happen
THINK ABOUT THIS, Its your chance to use your knowledge to explain a new phenomenon
Don’t be afraid to research similar experiments and reference them
Statistical Analysis
Topic – 1.1.1-1.1.6
Math skills requirements
Syllabus Statements
1.1.1: State that error bars are graphical representations of the variability of data
1.1.2: calculate the mean and standard deviation of a set of values
1.1.3: State that the term standard deviation is used to summarize the spread of values around the mean and that 68% of the values fall within one standard deviation of the mean
1.1.4: Explain how the standard deviation is useful for comparing the means and the spread of the data between two or more samples
1.1.5: deduce the significance of the difference between two sets of data using calculated values for t and appropriate tables
1.1.6: Explain that the existence of a correlation does not establish a causal relationship between two variables.
I know this is a science class but…
The math is still very important
Step 1: Construct a Data Table
Title
Units
Significant Figures
Uncertainties
MAKE IT CLEAR AND USEFUL TO THE READER
So What’s wrong with this table?
Step 2: Make a Picture
Choose the correct graph for your data
Bar graph, histogram, line graph, pie chart, scatterplot, box plot
Label axes, units, titles, legend, choose appropriate scale
If graphing means you must include error bars
Excel Demo
Suggestions for Choice of graphs
Histogram – continuous data
Bar graph – comparing discrete data, comparing means (use error bars)
Line graph – change over time
Scatterplot – showing the relationship between two measured variables
Pie chart – working with percents
Box plot – displays measure of central tendency and spread
Descriptive statistics
Do just that
They summarize your data in a few numbers
Step 5: Descriptive statistics: Central Tendencies
Arithmetic Mean = sum of all observations divided by the number of observations
Always report this in your lab
E.g. To calculate the mean of 100, 75, 75, 50
(100+75+75+50) / 4
In general
Xbar = (x1 + x2 + x3 + … + xn) / n
Step 5: Descriptive statistics: Central Tendencies continued
Only report these two if you use them – like when you have a very skewed distribution of data
Median: The point on the scale of observations on each side of which, there are equal areas under the histogram
The middle number of a data set when written sequentially
Odd # of observations (5,5,6,7,8) = ?
Even # of observations (5,5,6,7,8,9) = ?
Mode: The most common number (5,5,6,7,8) = ?
Step 6: Descriptive Statistics Measures of Dispersion
Central tendencies don’t tell the whole story.
Take a look at these data sets
We need a way to look at more than the middle
Range = Highest # - Lowest #
Standard Deviation (s) = Spread of data around the mean (How different are the values from the mean?)
Standard Deviation Graphic
Practice: Given a set of data can you calculate mean and stdev?
In calculator
Stat key
Edit and enter your list(s)
Stat key again
Calc and 1-var stats then specify your list
Which one is the mean?
Which one is the standard deviation?
Use the following data as an example
170, 160, 150, 175, 180, 175, 190, 165
The mean is 170.63
The standard deviation is 12.37 (use the s value)
Express means in this class as as:
Xbar +/- stdev ( 8 +/- 1.6 cm))
Try this for the data you just worked with
Step 7: Now use the Descriptive statistics to make your point
In a normal distribution (bell curve) remember the 68, 95, 99.7 RULE
68% of observations are within 1 stdev of the mean, 95% within 2 stdev, 99.7% within 3 stdev
Now can compare mean and spread of 2 distributions
small stdev = values tightly cluster around the mean (little variability)
large stdev = values spread out around the mean (large variability)
Using Standard Deviation - Variability
All have the same mean but different spread
Standard Deviation is just
A numerical measure of the spread of the data around the mean
The absolute number doesn’t mean a lot
Look at the number in relation to the mean
If you mean is 100 and your standard deviation is 1 then its tiny
If your mean is 1.5 and your standard deviation is 1 then that is pretty significant
Rule of thumb is if Sx/mean > .20 then its getting up there
For your error bars
On your bar graphs of the mean
Use standard error
Allows you to eyeball significant differences – if there is overlap then there is no significant difference
*Excel Tip*
Mean =average (highlight data) hit enter
Standard Deviation =stdev(highlight data) hit enter
Standard Error (Used for error bars on graphs) =[stdev (highlight data)] / square root (n)
So your Bar graphs now need Error Bars
Bars on a graph only show means and can be misleading
Error bars show variability around the mean
Can be used to show range, standard deviation or standard error
Means can look different
But really not be
Step 8: SO Does your data really show an effect?
Statistics give power to your results
Is your result just chance or is it caused by your Independent Variable (IV)?
Statistics uses probability to determine how likely it is that your results are just random
You should be proficient with T-test, linear regression analysis, chi square
Statistics: T-test
Compares the means of two populations which are normally distributed.
A way to tell if two means are actually different from each other.
The calculation accounts for the mean and variability of the data
Types of T-tests
Tails – Based on your initial hypothesis
1 tailed test – one mean is greater or one mean is less
2 tailed tests – the means are different
Paired – measuring the same individuals before and after – removes independence from the data
Statistics: T-test e.g.