BIOL260_SHFYR_2019_ALL_U: Science Literacy Assessment 4 - Handling Data
27/8/19, 5*46 pmBIOL260_SHFYR_2019_ALL_U: Science Literacy Assessment 4 - Handling Data
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Science Literacy Assessment 4 - Handling Data
BIOL260 Science of Sex
Science Literacy Assessment 4 - Handling Data
Data, data, data…. That is what science is really about in the end. Regardless if the experiment requires recording behavioural
videos, timing responses, blood samples taken, counting number of sperm, or measuring fertilised eggs. All the hours
collecting samples, can then require hours more processing the samples collected to turn them into numbers that can be
statistically analysed and turned often into figures. For example, behavioural videos have to be watched and scored and
translated into numbers, and blood samples can be used for genetic work, hormone analysis, or to count parasites.
Goal of Assessment: In this assessment you will learn how to select and organise the right part of a basic data and how to
handle it to help you make statements about the research findings and to make figure. You will also learn about the
interpretation of statistics.
The Assessment: You will be provided with a small data set that you will have to answer questions about.
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Handling data tutorial: Using excel and interpreting the data
When you collect data from an experiment you often collect information about multiple variables that are categorized, some
time in multiple ways. This means that you will have multiple columns of data that contain a category or numbers. The
categories can help you group the numbers for analysis.
Watch the video on ECHO for a demonstration of how to use excel
.
You will learn:
1) How to take averages of multiple cells of data and calculate the standard deviation.
2) How to make a basic figure, and add in e
or bars.
3) How to save the figure and put it in a document.
Statistics
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We are not asking you to run any statistical tests in the course. You just need to be able to interpret the outputs that we give
you.
What statistical tests you run depend on what kind of data you have and the distribution. For example, if you have measures o
value data (e.g. weight of egg) vs. count data (e.g. number of eggs) In statistical terms this means you have continuous (i.e.
can take on any value) vs. a discrete (i.e. whole number or category) data set.
The statistics that will be presented to you for the posters will be simple ANOVAs or t-tests. Both tests essentially are looking
to test fro differences between groups. The outputs will give you information that needs to be reported in your Results section.
What you need to report:
T-Tests – you need to report the t-stat number, the degrees of freedom, and the p-value. e.g. t = -1.593, df = 12, p = 0.297
ANOVA – you will get an F statistic, degrees of freedom in group sand individuals, and a p-value. e.g. F = 0.47, p = 0.73
BUT, what does it mean!!
The test you run on the data puts different constraints on the data, but with a-priori (before you run the test based on
assumptions you make before running the experiment). The classic way to judge if groups significantly differ is the p-value. If
the p-value is p < 0.05 then the groups are considered to be significantly different. Typically a p = 0.001 represents a stronge
difference between groups then p =0.04. By stronger, I mean it is a result more likely to stand up to further testing.
Science is generally moving away from the p-value though, so donʼt be surprised if you see significance presented in papers in
different ways – especially more recent papers. However, for this course you donʼt need to wo
y about this!.
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The Assessment
Use the following data set (as xlsx or as doc) answer the following questions, put them into a document fo
submission into turnitin.
To be completed in a document and submitted to TurnItIn - you only get one upload.
Please include you Name, Student ID number, and number your answers as they are asked below to avoid
confusion with marking.
You do not need to include a title page with your name and ID. Please use a legible font and text size. Normal
spacing is fine. Please save file with at least sir name, your student number, and assessment #.
1. (1 point) What is the average and standard deviation of the right testis collected from site A?
2. (1 point) Which season has the largest follicle volume? Name it and give the average and standard
3,31.2
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2. (1 point) Which season has the largest follicle volume? Name it and give the average and standard
deviation.
3. (3 points) Make a graph of averages with e
or bars of the oviduct weights across season.
Last modified: Monday, 19 August 2019, 2k12 PM
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