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Research Methods and Statistics 1 - PPLS08001
Coursework set: 12noon, Friday 1st March 2019
Coursework due: 12noon, Thursday 28th March 2019
Feedback returned: Thursday 19th April 2019
Online hand-in: read carefully!
An electronic copy of your report should be submitted online via the Turnitin link on the LEARN page for
RMS1. This will be located under the ‘Assessment Details & Submission’ tab. You should also submit your
R-code through the same link. The submission link will become available after you click on the “Own work
declaration” link.
IMPORTANT: Please name your files using your exam number only
Do not include any identifying information in the file name
(no name and no matriculation number)
You must follow this naming convention EXACTLY so that we can match your R-code to your script. Failure
to do so may result in your coursework not being graded.
Example of submission if your exam number was B00001 (you will use your own exam number, obviously!):
1. B000001.doc (or B000001.docx or B000001.pdf etc) file containing your report
Include your exam number inside the report too! In the header or footer of each page.
2. B000001.R file containing your R code
Include your exam number inside your R code too! This student could have used # B000001 as
first line in her script
You will be contacted by email by the course administrator, Alex McAndrew, to confirm all hand in
instructions.
Task
You are provided with a data set, a description of the data set, and a set of research questions. Your task
is to analyse the data in order to provide answers to the research questions. Analyses will draw on the
analytic procedures we have discussed in lectures and labs. You also have one conceptual question to
answer using knowledge you have built during this year.Page 2 of 4
Queries concerning the task
This document contains a basic overview of the task and of how to submit it.
If you have any questions concerning the coursework report, we ask that you post them on the
designated section of the on-line discussion board on Learn. If you have a question, it is likely your
classmates may have the same question. Before posting a question, please check the on-line board in
case it has already been answered.
Grading
Marks will be awarded for providing correct information for each element in the list above, for each of the
questions you are asked. Marks will be evenly distributed across questions.
You are required to submit your R-code which reproduces the answers you in the report. If the submitted
code runs and reproduces exactly the results reported, you will be awarded 10%. If the code fails to run,
or does not exactly reproduce the results reported, you will lose 10%.
Coursework body
Below are four research questions and one conceptual question. The research questions refer to data
from the file RMS1_1718_coursework_data.csv (available on Learn). Names of variables correspond to
column names from that file.
Your answer to each research question should include your analysis strategy and rationale why you are
choosing a particular method/analytical tool. You should aim to show us what you’ve learnt during the
course, making clear references to appropriate statistical tests, assumptions and providing detailed
interpretations.
These are some of the guidelines on what your answer should include.
Research Questions (Max:1750):
Data presentation: all necessary checks and data descriptions need to be reported
Analysis strategy (i.e. the hypotheses; choice of the test; where assumptions are required those
need to be referred to)
Present clearly the results from your analysis in R and provide clear interpretation.
Discuss the results in the context of the original research question using your own words. Is this
consistent with what you expected? Outline briefly the limitations of this research design, both
statistically and practically.
Conceptual Question (Max:250):
Provide a detailed answer to the question using your own words and statistical terminology.
Provide a clear example for illustration. Page 3 of 4
Research Questions
Question 1
A research team conducts a study examining the effects of various manipulations on participants’ ability to
learn novel categories. The experimenters create a set of cartoon aliens. Each alien belongs to one of five
imaginary alien species created by the experimenters.
In one study, participants study labelled examples of these cartoon aliens then take a categorisation test.
Participants either (a) study a set of 50 exemplars presented one at a time in a random order, (b) study 25
pairs of exemplars, each from the same category, (c) study 25 pairs of exemplars, each from a different
category, or (d) study 50 exemplars presented one at a time, but blocked by category (i.e., all the exemplars
from one category are presented, followed by the exemplars from the next category, and so on). The same
50 exemplars are used for each study condition.
The research team is interested in whether study type (study_type) has an effect on how well participants
perform in the categorisation test (scores are given in cat_test).
Did study type have any effect on categorisation performance? If so, what were those effects?
Question 2
The same team is interested in how caffeine intake might affect how quickly exemplars are categorised.
They teach a group of participants 3 new categories until they can identify members of the categories with
100% accuracy.
The next day, they ask all participants to return to complete a timed categorisation task on which they
measure reaction time (cat_RT; milliseconds). They estimated individuals’ caffeine intake that morning by
asking respondents to recall all food and drink consumed prior to testing (caffeine; mg).
Did caffeine affect reaction time?
Question 3
The team are then interested in whether participants learned all the different categories during study. They
want to look at whether there were any differences in whether or not participants learned all five of the
alien categories from question 1 (learned_cat, 0=no; 1=yes), depending on which study condition
(study_type) they were in.
Is there a relationship between study type and whether all five categories were learned or not?
Question 4
The research team were also interested in whether participating in the experiment has an effect on working
memory (WM) ability. Each participant also received a WM test before and after completing the
experiment (WM_before, WM_after).
Was there any difference in WM before and after the experiment?Page 4 of 4
Conceptual Question (choose one)
a) Discuss the difference between standard deviation and standard error.
b) Illustrate the qualities of a good estimator.
c) Illustrate the approaches that one can use to test a hypothesis.
Research Methods and Statistics 1 - PPLS08001
Coursework set: 12noon, Friday 1st March 2019
Coursework due: 12noon, Thursday 28th March 2019
Feedback returned: Thursday 19th April 2019
Online hand-in: read carefully!
An electronic copy of your report should be submitted online via the Turnitin link on the LEARN page for
RMS1. This will be located under the ‘Assessment Details & Submission’ tab. You should also submit your
R-code through the same link. The submission link will become available after you click on the “Own work
declaration” link.
IMPORTANT: Please name your files using your exam number only
Do not include any identifying information in the file name
(no name and no matriculation number)
You must follow this naming convention EXACTLY so that we can match your R-code to your script. Failure
to do so may result in your coursework not being graded.
Example of submission if your exam number was B00001 (you will use your own exam number, obviously!):
1. B000001.doc (or B000001.docx or B000001.pdf etc) file containing your report
Include your exam number inside the report too! In the header or footer of each page.
2. B000001.R file containing your R code
Include your exam number inside your R code too! This student could have used # B000001 as
first line in her script
You will be contacted by email by the course administrator, Alex McAndrew, to confirm all hand in
instructions.
Task
You are provided with a data set, a description of the data set, and a set of research questions. Your task
is to analyse the data in order to provide answers to the research questions. Analyses will draw on the
analytic procedures we have discussed in lectures and labs. You also have one conceptual question to
answer using knowledge you have built during this year.Page 2 of 4
Queries concerning the task
This document contains a basic overview of the task and of how to submit it.
If you have any questions concerning the coursework report, we ask that you post them on the
designated section of the on-line discussion board on Learn. If you have a question, it is likely your
classmates may have the same question. Before posting a question, please check the on-line board in
case it has already been answered.
Grading
Marks will be awarded for providing correct information for each element in the list above, for each of the
questions you are asked. Marks will be evenly distributed across questions.
You are required to submit your R-code which reproduces the answers you in the report. If the submitted
code runs and reproduces exactly the results reported, you will be awarded 10%. If the code fails to run,
or does not exactly reproduce the results reported, you will lose 10%.
Coursework body
Below are four research questions and one conceptual question. The research questions refer to data
from the file RMS1_1718_coursework_data.csv (available on Learn). Names of variables correspond to
column names from that file.
Your answer to each research question should include your analysis strategy and rationale why you are
choosing a particular method/analytical tool. You should aim to show us what you’ve learnt during the
course, making clear references to appropriate statistical tests, assumptions and providing detailed
interpretations.
These are some of the guidelines on what your answer should include.
Research Questions (Max:1750):
Data presentation: all necessary checks and data descriptions need to be reported
Analysis strategy (i.e. the hypotheses; choice of the test; where assumptions are required those
need to be referred to)
Present clearly the results from your analysis in R and provide clear interpretation.
Discuss the results in the context of the original research question using your own words. Is this
consistent with what you expected? Outline briefly the limitations of this research design, both
statistically and practically.
Conceptual Question (Max:250):
Provide a detailed answer to the question using your own words and statistical terminology.
Provide a clear example for illustration. Page 3 of 4
Research Questions
Question 1
A research team conducts a study examining the effects of various manipulations on participants’ ability to
learn novel categories. The experimenters create a set of cartoon aliens. Each alien belongs to one of five
imaginary alien species created by the experimenters.
In one study, participants study labelled examples of these cartoon aliens then take a categorisation test.
Participants either (a) study a set of 50 exemplars presented one at a time in a random order, (b) study 25
pairs of exemplars, each from the same category, (c) study 25 pairs of exemplars, each from a different
category, or (d) study 50 exemplars presented one at a time, but blocked by category (i.e., all the exemplars
from one category are presented, followed by the exemplars from the next category, and so on). The same
50 exemplars are used for each study condition.
The research team is interested in whether study type (study_type) has an effect on how well participants
perform in the categorisation test (scores are given in cat_test).
Did study type have any effect on categorisation performance? If so, what were those effects?
Question 2
The same team is interested in how caffeine intake might affect how quickly exemplars are categorised.
They teach a group of participants 3 new categories until they can identify members of the categories with
100% accuracy.
The next day, they ask all participants to return to complete a timed categorisation task on which they
measure reaction time (cat_RT; milliseconds). They estimated individuals’ caffeine intake that morning by
asking respondents to recall all food and drink consumed prior to testing (caffeine; mg).
Did caffeine affect reaction time?
Question 3
The team are then interested in whether participants learned all the different categories during study. They
want to look at whether there were any differences in whether or not participants learned all five of the
alien categories from question 1 (learned_cat, 0=no; 1=yes), depending on which study condition
(study_type) they were in.
Is there a relationship between study type and whether all five categories were learned or not?
Question 4
The research team were also interested in whether participating in the experiment has an effect on working
memory (WM) ability. Each participant also received a WM test before and after completing the
experiment (WM_before, WM_after).
Was there any difference in WM before and after the experiment?Page 4 of 4
Conceptual Question (choose one)
a) Discuss the difference between standard deviation and standard error.
b) Illustrate the qualities of a good estimator.
c) Illustrate the approaches that one can use to test a hypothesis.