Multiphase sampling free essay sample

Multiphase sampling is one of the probability sampling techniques that usually consist of two or more of both probability and non-probability techniques in choosing the target sample The researchers will going to use purposive sampling in the first step On the other hand, the researchers will use cluster sampling technique, a probability sampling technique to randomize the population. Simple randomization sampling can be done using fish bowl method to get the names of the participants that will be included into two groups; the experimental group and the control group. Between-group design of experimental research. In this design of experiments, a between-group design is an experiment that has two or more groups of subjects each being tested by a different testing factor simultaneously. The between-group design to measure the effect of colors on the participants’ memory using a control and experimental group. Within-Subjects Designs A within-subjects design is an experiment in which the same group of subjects serves in more than one treatment. We will write a custom essay sample on Multiphase sampling or any similar topic specifically for you Do Not WasteYour Time HIRE WRITER Only 13.90 / page Note that I’m using the word treatment to refer to levels of the independent variable, rather than group. It’s probably always better to use the word treatment, as opposed to group. The term group can be very misleading when you are using a within-subjects design because the same group of people is often in more than one treatment. As an example of a within-subjects design, let’s say that we are interested in the effect of different types of exercise on memory. We decide to use two treatments, aerobic exercise and anaerobic exercise. In the aerobic condition we will have participants run in place for five minutes, after which they will take a memory test. In the anaerobic condition we will have them lift weights for five minutes, after which they will take a different memory test of equivalent difficulty. Since we are using a within-subjects design we have all participants begin by running in place and taking the test, after which we have the same group of people lift weights and then take the test. We compare the memory test scores in order to answer the question as to what type of exercise aids memory the most. Strengths There are two fundamental advantages of the within subjects design: a) power and b) reduction in error variance associated with individual differences. A fundamental inferential statistics principle is that, as the number of subjects increases, statistical power increases, and the probability of beta error decreases (the probability of not finding an effect when one truly exists). This is why it is always better to have more subjects, and why, if you look at a significance table, such as the t-table, as the number of subjects increases the t value necessary for statistical significance decreases. The reason this is so relevant to the within subjects design is that, by using a within-subjects design you have in effect increased the number of subjects relative to a between subjects design. For example, in the exercise experiment, since you have the same subjects in both groups, you will have twice as many subjects as you would have had if you would have used a between-subjects design. If ten students sign up for the experiment, and you use a between-subjects design, with equal size groups, you will have five subjects in the aerobic condition and 5 in the anaerobic condition. However, if you use a within-subjects design you will in effect have 10 subjects in both conditions. Just as with the term groups vs. treatments, instead of using the term subjects it’s better to speak of observations, since the term subjects is misleading in the within-subjects design when the same person may effectively be more than one subject. The reduction in error variance is due to the fact that much of the error variance in a between-subjects’ design is due to the fact that, even though you randomly assigned subjects to groups, the two groups may differ with regard to important individual difference factors that effect the dependent variable. With within-subjects designs, the conditions are always exactly equivalent with respect to individual difference variables since the participants are the same in the different conditions. So, in our exercise example above, any factor that may effect performance on the dependent variable (memory) such as sleep the night before, intelligence, or memory skill, will be exactly the same for the two conditions, because they are the exact same group of people in the two conditions. Weaknesses There is also a fundamental disadvantage of the within-subjects’ design, which can be referred to as carryover effects. In general, this means the participation in one condition may effect performance in other conditions, thus creating a confounding extraneous variable that varies with the independent variable. Two basic types of carryover effects are practice and fatigue. As you read about the hypothetical exercise and memory experiment, you may very possibly have recognized that one problem with this experiment would be that participating in one exercise condition first, followed by the memory test, may inadvertently effect performance in the second condition. First of all, participants may very possibly be more tired from running in place and weight lifting than they are from just running in place so that they perform worse on the second memory test. If this is the case, they wouldnt do worse on the second test because aerobic exercise is better for memory than anaerobic, rather they would do worse because they were actually more worn out from exercising for ten minutes total than after only exercising for five. When one within-subjects treatment negatively effects performance on a later treatment this is referred to as a fatigue effect. On the other hand, in the exercise experiment the second memory test may be very similar to the first, so that by practicing with the first test they perform much better the second time. Again, the difference between the two conditions would not be due to the independent variable (aerobic vs. anaerobic), rather it would be due to practice with the test. When a within-subjects treatment positively effects performance on a later treatment this is referred to as a practice effect. Within-Subjects Designs Between-Subjects Designs Randomized designs and matched-groups designs are exampes of between-subjects designs. This means that every subject is tested under one, and only one, condition. For example, in a randomized experiment with a treatment condition and a control condition, each subject is testedeither under the treatment condition or under the control condition. Within-Subjects Designs Sometimes, however, it is desirable to use an experimental design in which each subject is tested under all conditions. This is called a within-subjects design or sometimes a repeated-measures design. For example, the very same subjects might be tested under a quiet conditionand a noisy condition to study the effect of noise level on concentration. Advantages of Within-Subjects Designs 1. Control of Extraneous Variables. Remember that random assignment and matching are intended to create groups that are highly similar to each other. Within-subjects designs go a step further, creating groups that are identical to each other in most ways. The IQs of the subjects in one condition are identical to those of the subjects in the other conditions because they are the samesubjects. The same holds true for most other person variables like race, sex, age, and so on. These designs do not control all extraneous variables to the same degree, however. Subjects’ moods, for example, can still differ from one condition to the next. Also, situation variables ortask variables (e. g. , time of day, temperature in the room) are still free to differ across levels of the independent variable. 2. Efficiency in Terms of Subjects and Time. Within-subjects designs are more efficient in their use of subjects and time. For example, a between-subjects design with three conditions and 20 subjects per condition requires 60 subjects. The same study conducted as a within-subjects design requires only 20 subjects. In addition, the within-subjects version can probably be completed in less time than the between-subjects version. 3. Statistical Efficiency. Within-subjects designs make it easier to detect differences across levels of the independent variable because each subject’s behavior under one condition is compared to that subject’s behavior under the other condition. The best way to see this is with an example