The Research Proposal

Researchable question itself

Why it's important (i.e., the rationale and significance of your research)

Propositions that are known or assumed to be true (i.e., axiomsand assumptions)

Propositions that will be tested (i.e., hypotheses or postulates)

Goals and specific objectives of your research activities

Methods you will use to test hypotheses and achieve objectives

Expected results and scope of inference

Describes the:

Define the researchable question

Develop hypotheses, predictions, and objectives

Develop materials and methods, including replication

Gather data

Analyze the data (contingency plans if things go wrong?)

Draw conclusions (accept, modify, reject the hypothesis)

Steps in the scientific method

HypothesesGeneral definitions

A new idea A statement to be tested - an 'educated guess' that needs more

study to be confirmed or disproved

A proposition that explains some phenomenon

Scientific hypothesis - The researchable question restated as a declarative sentence that is assumed to be true for testing purposes

Stated as what you believe to be true not what you want to disprove (i.e., not a statistical 'null' hypothesis)

Must be testable (e.g., generate predictions) The most valuable hypotheses are simple, consistent with what is

already known, and have broad applicability

The materials and methods must describe the:

Proposed experiments or investigations Materials and techniques that you will use, including their feasibility Statistical techniques and other methods used to analyze the data

Your expected results and interpretations must describe the:

Results that will lead you to conclude that the hypotheses are proved or disproved

Scope of inference (i.e., to what extent are the results applicable to other locations, times, or situations?)

Pitfalls that may be encountered Limitations to the proposed methods

Methods and expected results

Think it through!

Typical formatsEach hypothesis or objective often has its own set of methods

OBJECTIVES My objectives are to:Objective 1Objective 2

MATERIALS AND METHODSObjective 1

Hypotheses - RationaleExperimental designMeasurementsData analysisExpected results

Objective 2Hypotheses - RationaleExperimental designMeasurementsData analysisExpected results

Pitfalls and limitations (summary)

HYPOTHESES I hypothesize that:Hypothesis 1Hypothesis 2

MATERIALS AND METHODSHypothesis 1

Objectives - RationaleExperimental designMeasurementsData analysisExpected results

Hypothesis 2Objectives - RationaleExperimental designMeasurementsData analysisExpected results

Pitfalls and limitations (summary)

The materials and methods must describe the:

Proposed experiments or investigations Materials and techniques that you will use, including their feasibility Statistical techniques and other methods used to analyze the data

Connection between methods and conclusions must be clear -

why are you doing these things?

ApproachThe strategy connecting hypotheses to conclusionsObservational, experimental, modeling?

DesignRandomization, replication, etcHow do you know replication is sufficient?

Measurements - Response variablesSurvey, lab, field?Have you done these before?Are you collaborating with someone who has?

Statistical approaches

Expected results and interpretationsThe results you expect to see if your hypotheses are true (i.e., the predictions that flow from your hypotheses)

What will conclude if you do not see your expected results (i.e., if your predictions are not observed)?

Prediction

Hypothesis

Researchable question

Observations (axioms)

TestFalse True

deduction

Accept hypoth. (induction)

Reject hypoth. (deduction)

Expected results

Materials and methods

Expected results and interpretations must describe the:

Results that will lead you to conclude that the hypotheses are proved or disproved

The conditions to which the conclusions from the research will apply:

Scope of inference

Scientific Scope of inference Biological Geographical Temporal

Statistical Scope of InferenceClo

sely

lin

ked

Important to consider when you design your research

How broadly do you want to apply your results?

Pitfalls and limitations

Pitfalls

Demonstrates a realistic knowledge of your materials and methods Which procedures are risky? What can go wrong? How will you keep things from going wrong? What will you do if things go wrong - backup plans? What are the consequences if things go wrong?

Limitations

Scope of inference limitations Describe constraints - i.e., resource, time constraints

Evaluation Are the materials and methods adequate to test the

hypotheses and achieve the objectives?

Is the scope of inference defined, realistic, and adequate?

Are issues of representation, replication, and randomization appropriate to the proposal and if so, are they addressed?

Is it clear how conclusions will be drawn?

Is the proposed study doable and repeatable?

Are the pitfalls and limitations understood?

Are the experiments novel or creative?

Design the study

Carry out the study

Analyze the data

Define the question

Draw conclusions

Analyze the data

Define the question

Draw conclusions

Does the foliar boron concentration of seedlings differ among the nursery grown Douglas-fir seedlings in western Oregon that receive one of 4 different fertilizer regimes, the standard fertilizer with 0 lb/ac of boron, 1 lb/ac of boron, 2 lb/ac of boron, and 4 lb/ac of boron?

The Question of Interest defines responses to measure population to which inference is made groups to compare

Relating the Question of Interest to the Conclusions in the planning stages

What outcomes are possible?- Multiple or one?

What are the explanations for the outcomes?- a priori decide what you will conclude from potential outcomes

Does an outcome lead to more than one explanation?

- Not satisfying if an outcome corroborates many explanations

Before we accept the existence of an

effect, the effect must be observable

in replicates that represent the range

of variation* over which inference is to

be made.

-Hurlbert (1983)

Replication

*The scope of inference!

Replication

is the repetition of independent applications of a treatment or

protocol

Experimental Unit - smallest piece of material that receives an independent application of the treatment, a replicate

Sampling Unit - smallest piece of material on which a measurement is made, a sub-sample.

Pine

Doug-FirPine

Doug-Fir

What gets replicated?

Boron Fertilizer applied to sections of nursery beds.

How is the fertilizer applied!What gets an independent application?

a bed?

or a section of a bed?

or a or a seedling?

Effect of Herbicide on Apple weight

Two Orchards, tractor-sprayed herbicide. Assign each set of two rows to either herbicide or water

treatment. In each orchard mix up one tank of herbicide and one tank

of distilled water and apply each to assigned rows of trees.

Herb waterHerb

Effect of fire severity on re-growth of herbaceous cover

Severe

Low

Low

Medium

Pine

Doug-Fir

Pine

Doug-Fir

Pine

Doug-Fir

Compare tree regeneration rate after fires in Douglas-fir and Pine Stands.

Confound: To confuseTo mingle so that the elements cannot be distinguished

Confounding is the state in which 2 or more phenomena occur together in such a way that the study cannot separate the effects of one from the other.

Detecting Differences AccuratelyAvoid Confounding

Confounding: an example

Interest in whether bats forage more along streams then within forest stands.

In August, sample nighttime foraging activity of bats along streams in the coastal range.

In October, sample nighttime foraging activity of bats in forest stands in McDonald Dunn Forest (near Corvallis).

(Note that in the literature it says that nighttime foraging activity of bats increases with increasing nighttime temperature)

Confounding: an example In August, sample nighttime foraging activity of

bats along streams in the coastal range.

In October, sample nighttime foraging activity of bats in forest stands in McDonald Dunn Forest (near Corvallis)

To what should you attribute a difference in foraging activity?

Forest type Nighttime temperature Other seasonal effects (e.g. day length, seasonally

available food, day or night light levels)

Randomization

What we do:

Randomly select pieces of material to sample.randomly select

Randomly assign a piece of material to a protocol.randomly assign

Order items or protocols randomly.randomly order

Physically place items randomly.randomly placed

Randomization is somewhat analogous to insurance, in that it is a precaution against disturbances that may or may not occur, and that may or may not be serious if they do occur.

Cochran and Cox 1957

Randomization ensures that a particular treatment will not be consistently favored or handicapped in successive replications by some extraneous sources of variation, known or unknown. Steele and Torrie 1997

The function of randomization is to ensure that we have a valid or unbiased estimate of experimental error and of treatment means and the differences among the means.

Steele and Torrie 1997

Why do we randomize?

Randomization

What do we mean by randomization?

Mixed up the order? Cant repeat a selection or an assignment? See no pattern in a selection or an assignment? Cant explain how we did a selection or

assignment?

Randomization

Each replicate unit has a known chance of being assigned to a treatment.

Or

Each sample has a known chance of being sampled

The process is definable and repeatable.Randomization ensures that the effects we estimate are reasonably believed to be true for the whole set were interested in, not just for the subset.

Randomly selecting a unit to sample or measure can insure no systematic difference between units intended to be replicates

Inferences Observational studies can only report associations

between responses and groups Because you dont know and cant be sure that

something unknown is responsible for the difference you see between your groups

Controlled designed experiments allow you to draw cause and effect conclusions Because in theory, all other effects known to affect

the response have been controlled

Note: natural resource studies are commonly a mix of observational and design studies. It is not easy to have an natural resource study that can make cause and effect conclusions!