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Measurement Errors
Introduction to Study Skills & Research Methods (HL10040)
Dr James Betts
Lecture Outline:•Measurement Errors Continued
•Types of Errors
•Assessment of Error
•Introduction to Inferential Statistics
•Chi-Squared tests
•Assessment Details.
Measurement Errors• Virtually all measurements have errors
• Reliability and Measurement Error are not the same, rather Reliability infers an acceptable degree of Measurement Error.
Energy Intake (calories per day)
1500 2500 3500 4500 5500
Nu
mb
er
of
Pe
op
le
0
20
40
60
80
100
120
140
160
SD
TotalVariance
This total variance can then be
‘partitioned’
Systematic/Random Error
Skin-Fold Callipers
Hydrostatic Weighing
% Body-fatSubject 1 Subject 2 Subject 3 Subject 4
Body-Fat
0
5
10
15
20
25
Condition
%
Assessment of Error
• Systematic Error
Descriptive Statistics
4 12.00 22.00 16.2500 4.34933
4 8.00 12.00 10.2500 1.70783
4
Hydrostat
Callipers
Valid N (listwise)
N Minimum Maximum Mean Std. Deviation
Assessment of Error• Random
Error
12.00 14.00 16.00 18.00 20.00 22.00
Hydrostat
8.00
9.00
10.00
11.00
12.00
Cal
liper
s
Correlations
1 .527
. .473
4 4
.527 1
.473 .
4 4
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Callipers
Hydrostat
Callipers Hydrostat
Assessment of Error• Systematic &
Random Error
12.00 14.00 16.00
Mean
0.00
5.00
10.00
dif
fere
nce
s
Mean = 4.63
3 points of visual assessment:
-Systematic Error:
-Random Error:
-Nature of error:
12.00 13.00 14.00 15.00 16.00
Mean
0.00
5.00
10.00
dif
fere
nc
es
Mean differenceMean difference
Zero
12.00 13.00 14.00 15.00 16.00
Mean
0.00
5.00
10.00
dif
fere
nc
es
Mean differenceMean difference
Zero
12.00 13.00 14.00 15.00 16.00
Mean
0.00
5.00
10.00
dif
fere
nc
es
Mean differenceMean difference
Zero
12.00 13.00 14.00 15.00 16.00
Mean
0.00
5.00
10.00
dif
fere
nc
es
Mean differenceMean difference
Zero
SystematicVarianceTotal Variance
between trial 1 & trial 2
Dependent Variable
Extraneous/Confounding
(Error) Variables
Independent Variable
Smallest Worthwhile Effect
Re-Run
Introduction to Inferential Statistics
• Before our next lecture you will be conducting some inferential statistics in your lab classes
• All you need to be aware of at this stage is that the ‘P-value’ represents the probability that total variance is not due to primary variance
Gender
62 75.0 -13.0
88 75.0 13.0
150
Male
Female
Total
Observed N Expected N Residual
Goodness of fit χ2 testSPSS Output
Test Statistics
4.507
1
.034
Chi-Square a
df
Asymp. Sig.
Gender
0 cells (.0%) have expected frequencies less than5. The minimum expected cell frequency is 75.0.
a.
Chi-Square Tests
3.270b 1 .071
2.403 1 .121
3.301 1 .069
.120 .060
3.216 1 .073
60
Pearson Chi-Square
Continuity Correctiona
Likelihood Ratio
Fisher's Exact Test
Linear-by-LinearAssociation
N of Valid Cases
Value dfAsymp. Sig.
(2-sided)Exact Sig.(2-sided)
Exact Sig.(1-sided)
Computed only for a 2x2 tablea.
0 cells (.0%) have expected count less than 5. The minimum expected count is 14.50.
b.
Group * Response Crosstabulation
Count
18 12 30
11 19 30
29 31 60
Athletes
Non-Athletes
Group
Total
Do takesupplements
Dont takesupplements
Response
Total
Contingency χ2 test
SPSS Output
Selected Reading• I know error and variance can be confusing topics, try these:
• Atkinson, G. and A. M. Nevill. Statistical methods for assessing measurement error (Reliability) in variables relevant to sports medicine. Sports Medicine. 26:217-238, 1998.
• Hopkins, W. G. et al. Design and analysis of research on sport performance enhancement. Med. Sci. Sport and Exerc. 31:472-485, 1999.
• Hopkins, W. G. et al. Reliability of power in physical performance tests. Sports Medicine. 31:211-234, 2001.
• Atkinson, G., ''What is this thing called measurement error?'' , in Kinanthropometry VIII: Proceedings of the 8th International Conference of the International Society for the Advancement of Kinanthropometry (ISAK) , Reilly, T. and Marfell-Jones, M. (Eds.), Taylor and Francis, London , 2003.
Coursework (60% overall grade)• Your coursework will require you to address
2 of the following research scenarios:
– 1) Effect of Plyometric Training on Vertical Jump
– 2) Effect of Ice Baths on Recovery of Strength
– 3) Effect of Diet on the Incidence of Muscle Injury
– 4) Effect of Footwear on Sprint Acceleration
– 5) Effect of PMR on Competitive Anxiety.
Coursework Outline• For each of the 2 scenarios you will need to:
– Perform a literature search in order to provide a
comprehensive introduction to the research area
– Identify the variables of interest and evaluate the
research design which was adopted
– Formulate and state appropriate hypotheses
– Summarise descriptive statistics in an appropriate
and well presented manner…
Coursework Outline• Cont’d…
– Select the most appropriate statistical test with justification for your decision
– Transfer the output of your inferential statistics into your word document
– Interpret your results and discuss the validity and reliability of the study
– Draw a meaningful conclusion (state whether hypotheses are accepted or rejected).
Coursework Details (see unit outline)• 2000 words maximum (i.e. 1000 for each)
• Any supporting SPSS data/outputs to be appended
• To be submitted on Tuesday 14th December
Assessment Weighting
Evaluation & Analysis (30 %)
Reading & Research (20 %)
Communication & Presentation (20 %)
Knowledge (30 %)
Coursework Details• All information relating to your coursework
(including the relevant data files) are accessible via the unit web page:
www.bath.ac.uk/~jb335/Y1%20Research%20Skills%20(FH10040).html
Web address also referenced on shared area
Mid-Term Test (40% overall grade)• NEXT WEEK• This test will involve short answer questions
covering all the information covered so far• Mostly knowledge recall but will require
understanding and possibly some calculations• Duration = 50 min
So…
Mid-Term Test (40% overall grade)
• Surnames: A-F– Arrive promptly at 08.10 am for start of test at 08.15 am– Exit in silence afterwards
• Surnames: G-Z– Arrive promptly at 09.10 am for start of test at 09.15 am– Exit however you like!