“150”, Aptitude Test Questions and Answers
for Research officer Grade II (Forestry) – TAFORI.
ABSTRACT
This preparation guide provides 150 multiple-choice
aptitude test questions and answers for candidates applying for the position of
Research Officer Grade II (Forestry) at the Tanzania Forestry Research
Institute (TAFORI). The questions focus on forestry research, field data
collection, research methodology, data management and analysis, forest resource
assessment, scientific writing, research proposal development, project
reporting, supervision, environmental and natural resource management, and
practical research situations relevant to Tanzania. The questions are
deliberately challenging, with closely related answer choices designed to
assess candidates’ understanding, reasoning, analytical ability, and
application of knowledge rather than simple memorization. Each question is
accompanied by the correct answer and a detailed rationale to facilitate
effective self-assessment and deeper understanding during preparation for the
Public Service online aptitude test.
Prepared by: Research
officer Grade II (Forestry)
Based in Dar-es-salaam.
0628729934.
Date: August 08, 2026
Dear applicants,
This collection of questions and answers
has been carefully prepared to help all of you to understand the key areas
tested during the interview. The goal is to provide a useful, and practical
study guide so you can all perform confidently and fairly in the selection
process. I wish you the best of luck, and may this resource support you in
achieving success!
Warm regards,
Research officer Grade II (Forestry)
For Personal Use by Applicants Preparing
for Research officer Grade II (Forestry) TAFORI interview at Public Service
Recruitment Service.
ALL
QUESTIONS ARE COMPILED TOGETHER.
1. A TAFORI researcher wants to estimate the average diameter of
trees in a large forest where tree density varies considerably between
relatively distinct vegetation types. Which sampling approach would best ensure
that each vegetation type is adequately represented in the study?
A. Simple random sampling across the
entire forest B. Stratified random sampling within vegetation types C.
Systematic sampling along one forest access road D. Cluster sampling around
selected forest settlements
Answer: B. Stratified random sampling
within vegetation types
Rationale: Stratified random sampling is most
appropriate when the study population contains identifiable subgroups that
differ meaningfully in their characteristics. Dividing the forest into
vegetation types and then randomly selecting sample units within each stratum
ensures that important ecological conditions are represented in the sample.
Simple random sampling could unintentionally underrepresent smaller strata,
while systematic sampling along an access road could introduce location-related
bias. Cluster sampling would be useful where naturally occurring groups are the
principal sampling units, but it does not specifically guarantee proportional
representation of vegetation strata.
2. During a forest inventory, two researchers independently measure
the diameter at breast height (DBH) of the same trees using the same
instrument. Their measurements are consistently close to each other but
consistently higher than the true values. What does this pattern primarily
demonstrate?
A. High validity with low reliability B.
Low reliability with high validity C. Low precision with high accuracy D.
High precision with low accuracy
Answer: D. High precision with low
accuracy
Rationale: Precision concerns the consistency or
closeness of repeated measurements to one another, whereas accuracy concerns
how close a measurement is to the true value. If the researchers repeatedly
obtain measurements that are close together but systematically higher than the
actual DBH, the measurements are precise but inaccurate. This distinction is
important in forest research because a highly consistent measurement procedure
can still produce biased results if the instrument or method systematically
overestimates the variable being measured.
3. A researcher proposes to investigate whether increasing tree
density affects the growth rate of maize in an agroforestry system. Which of
the following represents the dependent variable?
A. Number of trees per hectare B. Type
of agroforestry system C. Growth rate of maize D. Spacing between planted
trees
Answer: C. Growth rate of maize
Rationale: The dependent variable is the outcome
that the researcher measures to determine whether it changes in response to
another factor. In this study, tree density is manipulated or categorized as
the explanatory variable, while maize growth is measured as the expected
response. Tree spacing and agroforestry system type may also influence maize
growth, but they are not the principal outcome specified in the research
question. Correctly identifying dependent and independent variables is
fundamental when designing experiments and interpreting relationships between
variables.
4. A forest researcher selects every 20th household from a
complete, ordered list of households after randomly selecting the first
household. Which sampling technique is being applied?
A. Systematic sampling B. Cluster
sampling C. Purposive sampling D. Stratified sampling
Answer: A. Systematic sampling
Rationale: Systematic sampling involves selecting
units from an ordered sampling frame at a predetermined interval after
establishing a random starting point. In this case, selecting every twentieth
household after randomly choosing the first household creates a fixed sampling
interval. Cluster sampling would involve selecting groups or clusters rather
than individual units at regular intervals. Stratified sampling requires
dividing the population into relevant subgroups before sampling, while
purposive sampling involves deliberately selecting units based on
researcher-defined criteria.
5. A researcher collects field data from permanent sample plots
every year for ten consecutive years to determine how forest composition
changes over time. What is the most appropriate description of this research
design?
A. Cross-sectional study B. Longitudinal
study C. Case-control study D. Experimental laboratory study
Answer: B. Longitudinal study
Rationale: A longitudinal study repeatedly observes
the same subjects, sites, or units over an extended period to examine changes
through time. Permanent sample plots are particularly useful for this purpose
because measurements can be repeated on the same locations, allowing
researchers to assess forest dynamics such as recruitment, mortality, growth
and species composition changes. A cross-sectional study normally provides
information at one point in time, whereas case-control designs are commonly
used to compare groups based on an outcome or condition rather than to monitor
ecological change continuously.
6. A researcher obtains a statistically significant positive
correlation between annual rainfall and tree growth. Which conclusion is most
scientifically defensible?
A. Rainfall definitely causes all
observed tree growth B. Tree growth necessarily increases whenever rainfall
increases C. Rainfall and tree growth are positively associated in the study D.
Rainfall is the only factor responsible for tree growth
Answer: C. Rainfall and tree growth are
positively associated in the study
Rationale: A statistically significant correlation
indicates that two variables are associated in the observed data, but
correlation alone does not establish causation. Tree growth may also be
influenced by soil fertility, temperature, species characteristics, competition,
pests, disturbance and other environmental factors. Even where rainfall is
biologically plausible as a causal factor, the researcher should avoid claiming
that it is the sole cause unless the research design adequately establishes
causality. Scientific interpretation therefore requires distinguishing
statistical association from causal inference.
7. A TAFORI researcher wants to determine whether two different
silvicultural treatments produce significantly different mean tree growth rates
across several experimental plots. Which statistical procedure would generally
be most appropriate when comparing the means of two independent treatment
groups?
A. Independent-samples t-test B. Pearson
correlation analysis C. Chi-square goodness-of-fit test D. Principal
component analysis
Answer: A. Independent-samples t-test
Rationale: An independent-samples t-test is
commonly used to assess whether the means of two independent groups differ
significantly, provided its assumptions are reasonably satisfied. In this
example, the two silvicultural treatments constitute the groups and tree growth
is the continuous outcome. Pearson correlation examines relationships between
continuous variables rather than comparing group means. Chi-square procedures
are generally used for categorical data, while principal component analysis is
mainly used to reduce dimensions and identify patterns among multiple
correlated variables.
8. Before entering field measurements into a statistical software
package, a researcher notices that some trees have been recorded with a DBH of
0 cm even though the field sheets indicate that those trees were measured. What
should the researcher do first?
A. Replace all zero values with the
sample mean B. Delete every observation containing a zero value C. Verify the
original field records and measurement entries D. Transform all DBH values
using a logarithmic function
Answer: C. Verify the original field
records and measurement entries
Rationale: An unexpected value should first be
investigated against the original source before it is corrected, deleted or
statistically transformed. A zero DBH could represent a data-entry mistake, a
coding convention, an incorrectly measured individual or another legitimate
circumstance. Automatically replacing it with the mean would introduce
artificial information, while deleting observations could reduce the sample and
introduce bias. Data cleaning should therefore begin with verification and
documentation of the original record and the reason for the questionable value.
9. A researcher is preparing a literature review on the effects of
forest fragmentation on biodiversity. Which approach would provide the
strongest scientific foundation for the review?
A. Selecting only studies supporting the
researcher's hypothesis B. Summarizing studies without assessing their
methodological quality C. Critically comparing relevant studies, methods and
findings D. Listing published articles according to their publication dates
Answer: C. Critically comparing relevant
studies, methods and findings
Rationale: A strong literature review does more
than compile or summarize publications. It critically examines existing
evidence, identifies similarities and differences among studies, evaluates
methodological strengths and weaknesses, and identifies knowledge gaps that
justify the proposed research. Selecting only supportive studies creates
confirmation bias, while merely listing or summarizing publications does not
demonstrate critical engagement with the evidence. A well-constructed
literature review should ultimately establish what is known, what remains
uncertain and how the proposed research contributes to the field.
10. A researcher is conducting a field study in which several
technicians will measure tree height and DBH. Which action would best improve measurement
consistency among technicians?
A. Allow each technician to select a
preferred measurement method B. Provide standardized procedures and practical
calibration training C. Assign each technician to measure different tree
species only D. Increase the number of researchers recording each measurement
Answer: B. Provide standardized
procedures and practical calibration training
Rationale: Standardization and calibration are
essential for reducing observer-related variation in field research.
Technicians should understand the same definitions, measurement points,
instruments and procedures and should receive practical training before data
collection begins. Allowing individuals to use different methods can introduce
systematic differences between observers. Increasing the number of observers
does not necessarily improve consistency and may actually increase measurement
variation unless all observers follow a common protocol.
11. A research proposal states that the study will “determine the
effects of different tree planting densities on the survival and growth of
seedlings.” Which feature would make this objective substantially stronger?
A. Making it broad enough to include
every forest variable B. Expressing the expected findings before collecting
data C. Defining measurable variables and a specific study context D.
Replacing measurable outcomes with general research intentions
Answer: C. Defining measurable variables
and a specific study context
Rationale: A strong research objective should be
sufficiently specific and measurable to guide the methodology, data collection
and subsequent analysis. Identifying planting density, seedling survival and
growth provides measurable components, but the objective becomes stronger when
the species, site or experimental context and relevant treatment levels are
clearly defined. Objectives should not presuppose the findings because doing so
introduces bias. Nor should they become unnecessarily broad, since broad objectives
can make the research difficult to implement and evaluate.
12. During field research, a researcher discovers that several
sample plots have been accidentally established outside the boundaries of the
selected forest study area. What is the most appropriate response?
A. Retain the plots without mentioning
the location error B. Move the plots and silently replace their original
observations C. Exclude the plots only if their
results appear unusual D. Document the
error and follow the approved sampling protocol
Answer: D. Document the error and follow
the approved sampling protocol
Rationale: Research errors should be transparently
documented and handled according to the established methodology or an approved
modification. Silently changing observations or selectively excluding unusual
results can compromise research integrity and introduce bias. If the plots are
outside the defined population, their data may not be valid for the intended
analysis, but the appropriate treatment should be determined systematically and
documented. Transparent handling of deviations is particularly important when research
findings may influence forest management decisions.
13. A forest inventory team wants to estimate total standing timber
volume in a forest. Which information would generally be most directly relevant
to calculating tree volume for individual sampled trees?
A. Tree diameter and height measurements B.
Soil colour and annual rainfall measurements C. Canopy species and household
population data D. Forest ownership and road accessibility data
Answer: A. Tree diameter and height
measurements
Rationale: Individual tree volume is commonly
estimated using measurements such as diameter and height together with an
appropriate volume equation or form factor. Diameter provides an estimate of
stem cross-sectional dimensions, while height contributes to the estimated stem
volume. Soil properties, rainfall and socioeconomic variables can be important
for understanding forest productivity and management but do not directly
provide the principal measurements needed to estimate individual tree stem
volume. Forest inventory therefore depends heavily on accurate quantitative
measurements of tree characteristics.
14. A researcher obtains a 95% confidence interval for the estimated
mean annual tree growth of a population. What does the confidence interval
primarily communicate?
A. The probability that every tree has
identical growth B. The plausible range for the population parameter based on
the sample C. The percentage of trees that will survive another year D. The
exact value of the population mean without sampling uncertainty
Answer: B. The plausible range for the
population parameter based on the sample
Rationale: A confidence interval provides a range
of values generated from sample data that is intended to capture the unknown
population parameter with a specified level of confidence under repeated
sampling. It communicates uncertainty around the estimate rather than claiming
that the population parameter is known exactly. It does not describe the
proportion of individual trees that will survive or imply that every tree has
the same growth rate. Understanding confidence intervals is important because
research estimates should be interpreted together with their uncertainty rather
than as isolated point values.
15. A researcher is comparing the effectiveness of three different
nursery treatments on seedling height after six months. Why would a one-way
ANOVA generally be preferable to conducting several separate pairwise t-tests?
A. ANOVA eliminates the need for
replication B. ANOVA guarantees that treatment differences are biologically
important C. ANOVA controls the overall risk of false positive findings better D.
ANOVA requires no assumptions about the collected data
Answer: C. ANOVA controls the overall
risk of false positive findings better
Rationale: When more than two group means are
compared, performing many separate t-tests increases the overall probability of
obtaining at least one statistically significant result by chance. One-way
ANOVA provides an overall test of whether there is evidence that the group
means differ while controlling the initial comparison framework more
appropriately. If the ANOVA is significant, suitable post-hoc procedures can
then identify which groups differ. ANOVA does not eliminate the need for
replication, guarantee biological importance or remove the assumptions
associated with statistical analysis.
16. A researcher receives a dataset containing 2,000 observations
from forest plots. Before conducting regression analysis, the researcher
notices that one variable has several extremely large values. What should
primarily be investigated before deciding how to handle those values?
A. Whether the values are genuine
observations or data errors B. Whether deleting them produces a stronger
statistical result C. Whether replacing them with the median improves
normality D. Whether excluding them makes the regression coefficient smaller
Answer: A. Whether the values are genuine
observations or data errors
Rationale: Extreme observations should first be
investigated to determine whether they represent legitimate characteristics of
the population or errors arising from measurement, recording or data entry.
Genuine extreme values may contain important information and should not
automatically be removed simply because they influence the statistical model.
Conversely, confirmed errors may need correction or exclusion according to a
documented data-cleaning procedure. Statistical decisions should be based on
methodological and substantive reasoning rather than on whether removing
observations produces a preferred result.
17. A research officer is asked to prepare a manuscript based on a
completed forest ecology study. Which section should primarily explain the
meaning and implications of the study findings in relation to previous
research?
A. Introduction B. Methodology C.
Results D. Discussion
Answer: D. Discussion
Rationale: The discussion section interprets the
findings and explains their meaning in relation to the research questions,
existing literature and broader scientific understanding. The results section
primarily presents what the analysis revealed without extensive interpretation,
while the methodology explains how the research was conducted. The introduction
establishes the research problem, background and objectives. A strong
discussion may compare findings with previous studies, explain possible reasons
for similarities or differences, identify implications and acknowledge
limitations without presenting unsupported conclusions.
18. A researcher wants to determine whether local communities'
participation in forest management is associated with improved compliance with
forest-use regulations. Which research question is the most appropriately
formulated?
A. Why are communities always responsible
for forest protection? B. Does community participation relate to compliance
with forest-use regulations? C. Are forest regulations generally useful for
all Tanzanian communities? D. How can researchers prove that participation
causes compliance?
Answer: B. Does community participation
relate to compliance with forest-use regulations?
Rationale: A well-formulated research question
should identify measurable concepts and establish a relationship that can be
investigated empirically. Community participation and compliance can be
operationalized using appropriate indicators and examined using qualitative or
quantitative methods. Option A assumes a conclusion, while C is excessively
broad and difficult to investigate within a defined study. Option D presupposes
causation and focuses on proving a predetermined relationship rather than
objectively investigating whether an association or causal relationship exists.
19. A forest research team plans to collect data from villages
surrounding a forest reserve. Which action would most directly improve the
representativeness of the selected villages?
A. Selecting villages based solely on
researcher convenience B. Selecting only villages with experienced forest
committees C. Using a defined sampling frame and an appropriate probability
method D. Selecting villages recommended by the most influential local leader
Answer: C. Using a defined sampling frame
and an appropriate probability method
Rationale: Representativeness is strengthened when
the sampling frame appropriately covers the target population and units are
selected using a method that gives eligible units a known or defensible chance
of selection. Convenience sampling, selection through influential individuals
or choosing only villages with particular characteristics can systematically
exclude relevant parts of the population. A properly designed probability
sampling method reduces selection bias and provides a stronger basis for
generalizing findings from sampled villages to the wider study population.
20. A researcher is preparing a funding proposal for a study on
climate-related changes in forest productivity. Which component most directly
demonstrates why the proposed research deserves support?
A. A detailed list of all equipment owned
by the institution B. A clear problem statement supported by evidence and
research gaps C. A general description of forests without identifying a
knowledge gap D. A list of researchers' academic qualifications without study
justification
Answer: B. A clear problem statement
supported by evidence and research gaps
Rationale: A fundable research proposal must
establish the significance of the problem and demonstrate why the proposed
study is necessary. A strong problem statement uses existing evidence to show
what is happening, why it matters, what is not adequately understood and how
the proposed research will address the identified gap. Institutional resources
and researcher qualifications may strengthen the feasibility section, but they
do not by themselves establish the need for the research. Funders generally
need to see both a meaningful problem and a credible pathway toward producing
useful knowledge or outcomes.
21. A researcher compares two silvicultural treatments, but
treatment A was deliberately assigned to plots with high soil fertility while
treatment B was assigned to plots with low soil fertility. Treatment A shows
greater tree growth. What methodological problem most threatens the validity of
attributing the growth difference to the silvicultural treatment?
A. Confounding B. Randomisation C.
Replication D. Measurement precision
Answer: A. Confounding
Rationale: Soil fertility is a confounding variable
because it differs systematically between the treatment groups and can
independently influence tree growth. Therefore, the observed difference in
growth cannot confidently be attributed to the silvicultural treatment alone.
Random allocation or appropriate blocking could help distribute or control
differences in soil fertility between treatments. Replication concerns the
number of experimental units, while measurement precision concerns the
consistency of observations.
22. A research officer is supervising technicians collecting forest
data. One technician reports a measurement that appears inconsistent with the
team's established protocol. What is the best immediate supervisory approach?
A. Delete the measurement without
consulting the technician B. Accept the value because field workers rarely
make errors C. Review the procedure and verify the measurement against the
protocol D. Replace the value using the average measurement from other
technicians
Answer: C. Review the procedure and
verify the measurement against the protocol
Rationale: Effective research supervision requires
maintaining data quality while avoiding arbitrary alteration of observations.
The supervisor should determine whether the technician correctly followed the
measurement protocol and, where necessary, repeat or verify the measurement
according to the established procedure. Automatically deleting or replacing
data can introduce bias and conceal problems in the field process. The
objective is not simply to obtain values that look reasonable but to ensure
that the final dataset accurately reflects observations collected using a
consistent and defensible methodology.
23. A TAFORI research team completes the first six months of a
project and is required to submit a progress report. Which information would be
most important for assessing whether the project is progressing
according to plan?
A. Personal opinions of team members
about the project B. Completed activities, outputs, challenges and planned
corrective actions C. The number of meetings held without reference to
research outputs D. A general description of the importance of forestry
research
Answer: B. Completed activities, outputs,
challenges and planned corrective actions
Rationale: A meaningful research progress report
should allow supervisors, funders or project managers to compare actual
progress with the approved work plan. It should therefore document activities
undertaken, outputs achieved, deviations or challenges encountered, resource or
implementation issues where relevant, and actions planned to address delays or
emerging problems. Merely listing meetings or describing the importance of
forestry research does not demonstrate project performance. Progress reporting
is fundamentally an accountability and management tool rather than a general
description of the research field.
24. A researcher wants to determine whether a new silvicultural
treatment causes greater seedling growth than the existing treatment. Which
feature would provide the strongest basis for making a causal inference?
A. Comparing treated seedlings with a
suitable control under controlled allocation B. Measuring only treated
seedlings before and after the intervention C. Selecting the fastest-growing
seedlings for the new treatment D. Comparing results from different forests
without controlling site differences
Answer: A. Comparing treated seedlings
with a suitable control under controlled allocation
Rationale: Strong causal inference requires a
research design that allows the effect of the intervention to be distinguished
from other factors that could influence the outcome. A suitable control group
provides a basis for comparison, while controlled allocation, preferably
through randomisation where appropriate, reduces systematic differences between
groups. A simple before-and-after comparison may be affected by environmental
changes over time, while selecting only vigorous seedlings creates selection
bias. Comparing different forests without controlling site differences also
makes it difficult to determine whether observed growth differences result from
the treatment or from environmental variation.
25. A researcher has completed a statistical analysis and obtains a
p-value of 0.03 for a pre-specified hypothesis test using a significance level
of 0.05. Which interpretation is most appropriate?
A. The null hypothesis has been proven
false with certainty B. The result provides statistical evidence against the
null hypothesis C. There is a 3% probability that the research hypothesis is
true D. The treatment has a 97% probability of producing a useful effect
Answer: B. The result provides
statistical evidence against the null hypothesis
Rationale: When the p-value is 0.03 and the
pre-specified significance level is 0.05, the result meets the conventional
criterion for statistical significance, meaning the observed data provide
evidence against the null hypothesis under the assumptions of the test.
However, this does not prove the null hypothesis false with certainty, nor does
the p-value represent the probability that either hypothesis is true.
Statistical significance also does not establish that an observed effect is
large, practically important or economically valuable; those issues require
consideration of effect size, uncertainty and the substantive context of the
research.
26. A researcher wants to estimate the number of trees per hectare
in a forest using circular sample plots. The plot radius is increased
substantially while the number of plots remains unchanged. What is the most
direct consequence of this change?
A. Each plot represents a larger sampled
area B. Each plot represents a smaller sampled area C. The sampling interval
automatically becomes smaller D. The probability of selecting each plot
automatically doubles
Answer: A. Each plot represents a larger
sampled area
Rationale: Increasing the radius of a circular plot
increases its area because plot area is proportional to the square of the
radius. Consequently, each plot covers a larger portion of the forest and
contains more potential observations, although the number of independent
sampling locations has not changed. This distinction is important in forest
inventory because plot size influences sampling intensity, the probability of
encountering trees, measurement effort and the precision of estimated forest
characteristics. Changing plot size does not by itself alter the sampling
interval or automatically change the selection probability of locations.
27. A forest inventory team records 18 trees in a circular plot with
a radius of 10 metres. If the observations are to be expressed as trees per
hectare, which principle should guide the conversion?
A. Multiply the count by the plot area in
hectares B. Divide the count by the plot area in hectares C. Divide the count
by the plot radius in hectares D. Multiply the count by the plot circumference
in hectares
Answer: B. Divide the count by the plot
area in hectares
Rationale: A hectare represents 10,000 square
metres, so observations from a plot must be scaled according to the fraction of
a hectare represented by that plot. The density estimate is obtained by
dividing the number of trees observed by the plot area expressed in hectares.
Using the radius or circumference would not correctly represent the sampled
surface area. This principle is fundamental in forest inventories because
measurements collected from sample plots often need to be converted into
standardized per-hectare estimates before they can be compared across sites or
aggregated to larger forest areas.
28. A study investigates the relationship between forest canopy
cover and understory plant diversity. The researcher finds a strong negative
correlation. Which additional evidence would be most useful before claiming
that reduced canopy cover causes increased understory diversity?
A. A larger list of species recorded in
the study B. A statistically significant correlation coefficient C. A
research design capable of controlling alternative explanations D. A stronger
statement of the researcher's original hypothesis
Answer: C. A research design capable of
controlling alternative explanations
Rationale: A correlation can demonstrate an
association but cannot by itself establish causation. To argue that canopy
cover causes changes in understory diversity, the researcher needs evidence
from a design that addresses alternative explanations, such as controlled
experimentation, longitudinal evidence with appropriate adjustment, or a robust
quasi-experimental design. Other factors including soil conditions,
disturbance, moisture, elevation and grazing could influence both variables.
Increasing the number of species recorded or obtaining a stronger correlation
does not automatically resolve the causal inference problem.
29. A researcher divides a forest into northern, central and
southern zones and then randomly selects plots separately within each zone.
What is the principal methodological advantage of this design?
A. It guarantees identical tree densities
in every zone B. It can improve representation of geographically distinct
areas C. It eliminates the need to calculate sampling error D. It ensures
that every tree in the forest is measured
Answer: B. It can improve representation
of geographically distinct areas
Rationale: Dividing the study area into meaningful
geographic strata before selecting random plots can ensure that each important
area is represented in the sample. This can be particularly useful where
environmental conditions, forest composition or management history differ
across the zones. However, stratification does not guarantee equal tree
densities, eliminate sampling error or require measuring every tree. Its
principal value is improving the structure and representativeness of the sample
and, where appropriate, potentially improving estimation precision by
accounting for known spatial differences.
30. During a forest inventory, a team consistently records tree DBH
at different heights because individual technicians interpret the measurement
point differently. What type of error is most directly being introduced?
A. Sampling frame error B.
Coverage error C. Measurement error D. Non-response error
Answer: C. Measurement error
Rationale: Measurement error occurs when the
recorded value differs from the value that should have been obtained because of
problems in the measurement instrument, observer technique, protocol or
recording process. In this case, inconsistent interpretation of the DBH
measurement point creates differences in the recorded diameter even when the
same tree is being measured. Sampling frame error concerns problems in
identifying the population from which the sample is drawn, while non-response
error is associated with selected units failing to provide information.
Standardized training and field protocols can substantially reduce this type of
error.
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