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STA408 Design and Analysis of Experiments GDB Spring 2020 Solution & Discussion Last Date: 07-06-2020

STA408 Design and Analysis of Experiments GDB Spring 2020 Solution & Discussion Last Date: 07-06-2020

Total Marks 5
Starting Date Monday, June 01, 2020
Closing Date Sunday, June 07, 2020
Status Open
Question Title Experimental Design
Question Description

Dear Students,

Write down steps involved to design an experiment.

Note:

Don’t Paste the answer in MDB. This GDB is graded and marks will be awarded on its performance.

Note: Answer should be relevant. Irrelevant and unnecessary lengthy materials will not be considered.

Also it is strictly informed that the answer will not be received through emails.


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STA408_Assignment_No_01_Solution_Spring_2020

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STA408_Assignment_No_01_Solution_Spring_2020

Write down steps involved to design an experiment.

An experiment is a type of research method in which you manipulate one or more independent variables and measure their effect on one or more dependent variables. Experimental design means creating a set of procedures to test a hypothesis.

A good experimental design requires a strong understanding of the system you are studying. By first considering the variables and how they are related (Step 1), you can make predictions that are specific and testable (Step 2).

How widely and finely you vary your independent variable (Step 3) will determine the level of detail and the external validity of your results. Your decisions about randomization, experimental controls, and independent vs repeated-measures designs (Step 4) will determine the internal validity of your experiment.

Step 1: Define your research question and variables
Step 2: Write your hypothesis
Step 3: Design your experimental treatments
Step 4: Assign your subjects to treatment groups

Step 1: Define your research question and variables

You should begin with a specific research question in mind. You may need to spend time reading about your field of study to identify knowledge gaps and to find questions that interest you.

We will work with two research question examples throughout this guide, one from health sciences and one from ecology:

Example question 1: Phone use and sleep
You want to know how phone use before bedtime affects sleep patterns. Specifically, you ask how the number of minutes a person uses their phone before sleep affects the number of hours they sleep.

Example question 2: Temperature and soil respiration
You want to know how temperature affects soil respiration. Specifically, you ask how increased air temperature near the soil surface affects the amount of carbon dioxide (CO2) respired from the soil.

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables.

Phone use and sleep
Minutes of phone use before sleep
Hours of sleep per night
Temperature and soil respiration
Air temperature just above the soil surface
CO2 respired from soil
Then you need to think about possible confounding variables and consider how you might control for them in your experiment.

Phone use and sleep
Natural variation in sleep patterns among individuals.
Control statistically: measure the average difference between sleep with phone use and sleep with phone use rather than the average amount of sleep per treatment group.
Temperature and soil respiration
Soil moisture also affects respiration, and moisture can decrease with increasing temperature.
Control experimentally: monitor soil moisture and add water to make sure that soil moisture is consistent across all treatment plots.

Finally, put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.
experimental-design-1.png

Diagram of the relationship between variables in a sleep experiment

Here we predict that increasing phone use is negatively correlated with hours of sleep, and predict an unknown influence of natural variation on hours of sleep.
Diagram of the relationship between variables in a soil respiration experiment
experimental-design-2.png

Here we predict a positive correlation between temperature and soil respiration and a negative correlation between temperature and soil moisture, and predict that decreasing soil moisture will lead to decreased soil respiration.

Step 2: Write your hypothesis

Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

Phone use and sleep
Phone use before sleep does not correlate with the amount of sleep a person gets.
Increasing phone use before sleep leads to a decrease in sleep.
Temperature and soil respiration
Air temperature does not correlate with soil respiration.
Increased air temperature leads to increased soil respiration.
The next steps will describe how to design a controlled experiment. In a controlled experiment, you must be able to:

Systematically and precisely manipulate the independent variable(s).
Precisely measure the dependent variable(s).
Control any potential confounding variables.
If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

Step 3: Design your experimental treatments

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalized and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

Soil-warming experiment
You can choose to increase air temperature:

just slightly above the natural range for your study region.
over a wider range of temperatures to mimic future warming.
over an extreme range that is beyond any possible natural variation.
Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

Step 4: Assign your subjects to treatment groups

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size: how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power, which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups. Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group, which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

A completely randomized design vs a randomized block design.
An independent measures design vs a repeated measures design.
Randomization
An experiment can be completely randomized or randomized within blocks (aka strata):

In a completely randomized design, every subject is assigned to a treatment group at random.
In a randomized block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

STA408_Assignment_No_01_Solution_Spring_2020

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STA408_Assignment_No_01_Solution_Spring_2020

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