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Published byBethanie Sanders Modified over 9 years ago
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The investigator passively observes and records information on observational units. Method often used to see how things behave in nature. Still tells us a lot of information BUT… does not tell use cause and effect.
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The investigator deliberately imposes some condition on the subjects or experimental units, observing and recording results. Experiments can lead us to know the cause and effect of variables
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1) Control 2) Randomization 3) Replication 4) Blocking
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Two purposes: ◦ This allows us to compare the effect of the treatment variable with no treatment at all. ◦ Shows the extent in which the treatment is effective (or ineffective) ◦ Try to “control” everything else so that the results can only be contributed to the treatment.
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Just as important in experimental design as surveying Need to randomly assign subjects to treatment and control groups. This could help eliminate hidden variables effecting the outcome.
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Replication has 2 purposes… 1) We need to be sure of our results so we can convince other people of our findings. A large number of subjects in both groups with supporting evidence. 2) If other researchers do not believe our results, the experiment should be replicable so that our evidence can be supported.
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This refers to separating subjects with something in common before assigning random groups. This could again eliminate hidden variables.
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Studying a drug that could limit heart attacks, a researcher splits groups based on age, activity level, diet, whether the subject is diabetic, and race. Each of the groups is then randomly assigned to treatment or control. For example: a control and treatment group for 20-40 year olds, a control and treatment group for 40-80 year olds, etc.
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Lurking variables and confounding varibles: ◦ variables that are not considered in the study but could have an effect on the response variable. This prevents the experimenter from isolating the effects of the experimental variable.
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Example: In the heart attack example we forgot Gender. A lurking variable would be that gender had an important role in whether this drug worked, but it was ignored. Now we don’t know if the results were due to the drug, or due to gender which was hidden.
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In an experiment to see if stress causes muscle cramps… The higher the stress, the more the subject has muscle cramps. BUT… the more the subject is stress, the more coffee they tend to drink. The caffeine in the coffee could instead by causing the muscle cramping and not the stress.
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Placebo effect: consider a medical case ◦ A subject who is receiving a trial drug that is believed to help may think they feel better even though in actuality, they are not improving. ◦ Likewise, a subject who is the control does not believe they will get better because they do not have the treatment.
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Single-blind experiment: ◦ Subject does not know if they are receiving the treatment or the “placebo” ◦ The placebo is usually a sugar pill, or something similar that has no effect on the patient negatively or positively. Double-blind experiment: ◦ Subject and researcher’s assistant responsible for analyzing results of the treatment BOTH do not know if the subject is getting a treatment or not.
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The subject is not the only one that can be effected by the placebo effect. The person responsible for analyzing the results of a treatment may be bias knowing one subject had a treatment and one did not.
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Refer to #1 of the experimental design practice worksheet… Step 1: Plan: What do you want to know? Whether tomato plants by optigrow are juicier, tastier tomatoes than plants raised otherwise without fertilizer.
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Response: Specify the response variable and how you will measure it. Evaluate the juiciness and tastiness of the tomatoes by asking a panel of judges to rate them on a scale of 1 to 10 in each category
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Treatments: specify what treatments will be given and at what levels. The treatment is fertilizer. I’ll grow tomatoes at three different levels; some with no fertilizer, some with half, and some with the full. These are the 3 treatments.
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Experimental units: specify the experimental units Obtain 24 tomato plants of the same variety.
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Experimental design: observe the principles of design Control: Farm plots near each other so that they get similar light and rain and experience same temperatures. I will weed the plots equally and otherwise treat the plants alike. Replicate: I’ll use 8 plants in each treatment group. Randomly assign: I will divide the plants into 3 groups. First I’ll label the plants with number 00- 23. I’ll look at pairs of digits across a random number table. The first 8 plants identified (ignoring digits 24-99 and any repeats) will go in Group 1, the next 8 in group 2 and the remaining plants in group 3.
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Specify experimental details: I will grow the plants until the tomatoes are mature. I’ll harvest the tomatoes when ripe and store them for evaluation. Judges will evaluate each tomato and I will record results. I will display the results in side-by-side box plots to compare the three treatments. I will compare the means. If the differences in taste and juiciness among the groups are greater than I would expect by knowing the usual variation among tomatoes, I will be able to conclude that these differences can be attributed to the treatment with fertilizer.
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