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Based on random sampling and structured data collection. ◦ that fit diverse experiences into predetermined response
categories. ◦ produce results that are easy to summarize, compare,
and generalize.
Testing hypotheses derived from theory and/or being able to estimate the size of a phenomenon of interest.
Typical strategies : ◦ Experiments/clinical trials ◦ Observing and recording ◦ Obtaining relevant data from information systems ◦ Administering surveys with closed-ended questions
(Interviews & questionnaires)
Validity: the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. ◦ The study’s success at measuring what the researcher
set out to measure.
◦ Internal (the research design) and external (generalisation and transferability).
Reliability: the accuracy of the actual measuring instrument or procedure. ◦ Reliability: the extent to which an experiment, test, or
procedure yields the same result on replication.
‘Assumption’ based on what you expect your research to refute or accept.
Null (Ho) and alternate (Ha).
Causality ◦ ‘smoking causes cancer’
Test for relationship ◦ ‘long term smoking increases the risk of cancer’
Not all research needs an hypothesis but should have questions you wish to address
Research phenomena under investigation
Research questions
Study aims and objectives
Research design and methodology ◦ Experimental
◦ Field survey and observation
Sampling framework ◦ Probability sampling
Margin of error
Experimental/ clinical trials ◦ Rigour and accuracy ◦ Replication and method is crucial ◦ Researcher has the ability to influence and control
variables
Field survey and observation ◦ Limited control of variables by researcher ◦ Similar to case study- using a reality to understand how
different aspects are linked and/ or impact each other
Cross-sectional studies: understanding variables/ phenomena within a specified reality. ◦ Not time dependent
Longitudinal studies: examine the phenomena over a certain time period ◦ Time-series analyses
◦ Seasonality studies
Researcher has minimal influence on the selection of individual units- Objectivity
Probability - All units in that population has an equal opportunity of being selected. ◦ Random selection of units
Non-probability- selection criterion that defines how units are chosen within a population. ◦ Units are systematically or purposively selected
Dependent on your research aim/ intention
Quantitative assessments Qualitative assessments
Measurable ◦ Turbidity
◦ pH
◦ E.coli levels
Observation ◦ Colour
◦ Odour
◦ Surrounding environments
Cross-sectional and longitudinal
Longitudinal studies
Measure varaibles Interpretation
Measurable • Root & shoot length • Height • Leaf chemistry
Observation • Colour • Occurrence of
disease • Shape of leaves
Measureable ◦ Income
◦ Energy expense
◦ Access
Observation ◦ Cooking practices
◦ Ventilation during cooking
◦ Collection of energy sources
Table 5.1 Household income (in %)
Categories Inanda (n=400) Bergville
(n=400)
None 2.8 4
< 1000 12.7 24.7
1001-3000 48.1 62.2
3001-5000 21 8.7
5001-7000 9.1 1.8
7001-9000 3 0.8
> 9001-15000 3.4 -
Average household
income R3109.25 R1841.38
Area Inanda
(n=400)
Bergville
(n=400)
Indoors 98.5 98.3
Outdoors 1.5 1.3
Table 5.2: Main cooking area (in %)
Cooking method Inanda
(n=400)
Bergville
(n=400)
Stove top 98.3 81.5
Fire top 1.8 42.3
Table 5.3: Main cooking method (in %)
Figure 5. Energy status of Bergville communities
Should be clear and detailed – not précised as in journal article
Must provide details of replication, type of data collected and explain how data was processed (where necessary)
Must indicate after whom the method was adapted from (according to/ after)
Be sure to link to experimental design (e.g. on what day of the experiment the measurements were taken)
Flow diagram or design diagrams may be useful in some cases
* See examples
(1) Results or Results and (2) Discussion
In (1) results are reported and interpreted - not explained, nor linked to broader literature
In (2) results are reported, interpreted, explained and linked to broader literature - usually in that order
Text associated with a figure or table should always precede it
Avoid including results of statistics in text (refer to Fig. or Table)
Avoid reporting marginal differences rather focus on significant and/or broad trends
When saying higher/lower/worse/better – always remember to relate it to something (e.g. the control)
Should incorporate replicate numbers
Title should describe data shown
Legend/Caption should indicate what the values represent, statistical tests (+p values) and replication
Treatment abbreviations should be expanded
Figure 7.8 Instantaneous leaf-based CO2-assimilation rates (at Ca: 400 µmol. mol-1) of seedlings recovered from fresh (F), partially dried (D) and cryopreserved (C) embryos, subjected to watering (W) or water deficit (S). Columns labelled with different letters are significantly different when compared within experimental days (p < 0.01 for Embryo on days 0 and 12 and = 0.01 on day 8; p = 0.04 for Stress and = 0.01 for EmbryoStress on day 8, ANOVA, n = 7). Bars represent ±SD.
0
2
4
6
8
10
12
0 8 12Time (days)
CO
2 a
ssim
ilatio
n (
µm
ol m
-2 s
-1)
FW DW CW FS DS CS
a
bb
a
abc
bc
bc
ab
c
cdc
c
b
a
cdd
48.8
14.6
29.3
48.8
17.1
65.2
43.5
13
34.8 34.8
0
10
20
30
40
50
60
70
Cheaper Safe to use No negative healthimpacts
Environmentallyfriendly
Reliable
%
Inanda (n=99) Bergville (n=98)
Figure 5.15: Perceived benefits of renewable energy
Ratio was calculated for seedlings recovered from fresh (F), partially dried (D) and cryopreserved (C) embryos, subjected to watering (W) or water deficit (S). Values followed by different letters are significantly different when compared within a measurement day (p < 0.01 for Embryo on days 8 and 12 and for Stress and EmbryoStress on day 12; p < 0.05 for Stress and EmbryoStress on day 8, ANOVA). Values represent mean±SD (n = 7). NA = not applicable.
Table 7.3 Ratio of CO2-assimilation rate at Ca: 600 µmol. mol-1 : CO2-assimilation rate at Ca: 400 µmol. mol-1.
Day FW DW CW FS DS CS
0 2.29±0.60a 2.11±0.55
a 1.85±0.35
a NA NA NA
8 1.68±0.44b 1.66±0.70
b 1.81±0.35
b 2.48±0.23
a 1.57±0.15
b 1.76±0.47
b
12 1.68±0.10b 1.61±0.17
b 1.51±0.15
b 2.36±0.53
a 1.66±0.45
b 1.43±0.20
b
Statements Inanda (n=400)
Strongly
disagree
Disagree Neutral Agree Strongly
agree
Mean
Is expensive 3 9.3 4 30 53.8 4.39
Is bad for
health 5 6.3 25.5 25.3 38 4.06
Is unreliable 14 15.3 36.6 18.3 16 3.17
Causes
environmental
pollution
12 15.3 12.3 27 33.8 3.62
Inefficient 29 35.8 16 10 9.3 1.83
Is inaccessible 13 11.3 22.3 27 26.8 3.56
20
22
24
26
28
30
32
34
36
38
0 7 14 21 28 35 42 49
Mid
da
y a
ir t
emp
era
ture
(oC
)
Days After Initiation
Control OTC
0
2
4
6
8
10
Control pH 4.5 pH 3.0
Chlo
rophyll
conte
nt cm
-2
Treatments
Chl a Chl b Total chlorophyll
a
a
ab
a
b
a
aab
b
Working with raw data and means
Statistics always on raw data
Pool data from different experiments except where it is done over different seasons or populations
Export into SPSS by copying and pasting from excel file
Parametric versus non-parametric (KS-test; Shapiro Wilks)
Transforming data (log, square root transform) – only for analysis; not for figs and tables
Percentiles need to be arcsin transformed Parametric = ANOVA, T-test Non-parametric = Mann Whitney-U Correlation/Regression to test for
relationships between parameters - p-value tells you when relationship is significant; R2 describes strength of relationship
