Effects of Caffeine on Memory - Essay Example

Effects of Caffeine on Memory Introduction Even though experiments may be utilized in examining associations between variables, their key aim is to address causal questions. That is why this experiment tests causal relation of the stimulant caffeine effect on memory. This implies that the independent variable, which is the consumption of caffeine, can be well defined and manipulated in relation to the dependent variable, which happens to how the humankind memory can be affected in relation to sleeping hours or duration. In this experiment, we were able to control the independent variable and obtain its effect on the dependent variable. We conducted this experiment in a controlled environment which helped us to minimize the effects of the extraneous variable which are age and gender of the two groups of participants (Philip 1999: 18). We did this by random assignment to the two subjects to the experimental conditions. This hence helped us to know the cause and effect relation between the independent variable and the dependent variable. Aim of the experiment.   In this particular experiment, one wants to know if there is a significant difference between the data gathered from each of the condition, caffeine administered and the condition where no caffeine was administered on memory and their effects to humankind. One seeks to establish if caffeine actually does have an effect or impact on the amount of sleep that one obtains (Philip 1999: 21). Questions can be posed from these conditions. Can intake of caffeine significantly decrease or cause an increase in the amount of sleep a person acquires? Is there any or zero difference in the amount of sleep for caffeine administered and no caffeine administered conditions?  Planning the study This research depended on the critical planning and execution of the study. Decisions made at every point of this study had an effect on the final amount of data to be analyzed, and research questions was addressed. Various texts were used in this study too. Sufficient time was also an input in this study (Philip 1999: 47). The experiment involved the use of two groups, less number of participants that were enough. We randomly assigned participants to each of the conditions. A within subjects design A within subjects design is a kind of design which all participants become exposed to every condition, unlike a between subjects design where participants become randomly assigned to treatments and conditions. The data in the table below, shows within designs subject, using only 8 subjects, which is half that of between subjects design. The 8 subjects become tested under both designs. There is a one point difference, but this difference can be shown by every subject, and not due to chance as it was in the case of between subjects design. Within subjects design Control Treatment Difference Subject 1 100 101 1 Subject 2 98 99 1 Subject 3 108 109 1 Subject 4 104 105 1 Subject 5 89 90 1 Subject 6 99 100 1 Subject 7 106 107 1 Subject 8 112 113 1 M=102 M=103 M=1 A between subjects design This design serves as a vital way in evading the carryover effects common in within subjects design. Here, participants can be part of the control group or treatment group, but cannot be part of both. This implies that if more than one treatment becomes tested, a new group would be required for each treatment. The data in this table represents a between subjects design. The data shows the one point mean difference. It uses 16 subjects in this experiment. It is not clear whether this difference can be considered to be reliable, either due to the treatment or by chance. Between subjects design Control Treatment Subject 1 100 Subject 2 109 Subject 4 98 Subject 3 113 Subject 5 108 Subject 6 101 Subject 8 104 Subject 7 105 Subject 9 89 Subject 10 99 Subject 12 99 Subject 11 107 Subject 13 106 Subject 14 100 Subject 16 112 Subject 15 90 M=102 M=103 Advantages and disadvantages of a within and a between subjects design in this experiment One of the advantages of this design is that it never needs a huge pool of participants. It can also aid in reduction of errors linked with individual variations (Philip 1999: 212). In a between subjects design, they would use twice as much individuals compared to a within subjects design. In a between subjects design, even though individuals can be indiscriminately assigned to a condition, as in the case with this experiment, there is still a likelihood that there maybe certain variations between the groups that might affect the results. In a within subjects design, individuals can be exposed to all stages of a condition, hence the results or outcome would not have any effects of distortion by individual variations. This is because each and every participant serves a self baseline. Furthermore, a within subjects design has its’ drawbacks. One type of drawback is that a sheer act of having participants take part in one condition can affect overall performance or trait on all other conditions, an issue known as carryover effects. In this experiment of effect of caffeine on humankind memory, consumption of caffeine may impact their performance on memory. Fatigue is another disadvantage of using a within subjects design. Participants may become bored and lose interest after undergoing multiple tests (Philip 1999: 254). Moreover, performance on related tests can also be affected by practice effects. Periodical consumption may make them may make it hard for them to skew and establish their own findings based on the results of the practice. A long type of experiment such as the case of sleeping hours duration in this experiment, may cause fatigue. Hence this would decrease their performance on these tests. A counterbalance measures design in a within subjects design It is important to carry out experiments using a counterbalance measures design. This aids in avoiding disparities of standard recurring measures design, where the subjects can be exposed to all treatments. In a normal test, the sequence in which treatments can be given can impact on the trait and behavior of the subjects, and may result in a false response, that may be caused by fatigue or external factors, altering the trait of many of the participants to counteract such a scenario, the use of a counterbalance design which minimizes the of the possibility of the order of the treatment to affect the final results (Philip 1999: 282). Counterbalance measures in a within subjects design The counterbalance measures design can be utilized in the case of two groups as it was in this experiment. A test would be done to each subject in both conditions of this test, into first and second condition. One group would be treated with first condition followed by the second condition, and the other group becomes tested with the second condition followed by the first condition. It must be noted that this process must be carried out perfectly to avoid misleading results. Controlling extraneous variables in within subjects design One should know that random assignment can be intended to create groups which are similar to one another. In a within subjects design, there exits creation of groups considered to be identical to each other in numerous aspects. The memories of the subjects in one condition, is identical to other conditions since they are the same subjects (Philip 1999: 300). The same would continue to be true and be applicable to person variables such as race, sex, age of persons. One must know that within and between subjects designs do not control all extraneous variables to the same extent. However, moods of the subjects, may still differ from one condition to the next. Moreover, task variables such as time, are free to vary across levels of the independent variable in this experiment. A summary of data collection stage In this stage, we chose appropriate scales and measures for use during the process of data collection. They were in accordance to the nature of this experiment that involves measuring of the performance and output of the two caffeine conditions and the behavior of the two groups under study. The scales chosen were reliable and valid during consideration. This was because I collected vital information concerning the validity and reliability of each of these scales. A pilot-test was done prior to this experiment. We did an assessment of the reliability of this scale by administering it to the same people on various occasions and calculating the correlation between the two scores obtained. We also made an assessment of its internal consistency. It was noted that internal consistency can be measured in various ways (Philip 1999: 453). The commonly utilized method was Cronbach’s coefficient alpha, contained in the SPSS application. It provided an indication of the average correlation of all items of the scale. Values ranged from 0 to 1, with greater values showing the possibility of higher reliability. We used a Likert-type scale. Using of questionnaires. In this study, it was vital to gather information from the participants and the various respondents through the use of questionnaires. A selected sample of humankind population became chosen randomly in this case. The questionnaires were well-planned since reliable data from the research questions were obtained. This was because during its preparation, we had in mind the kind of statistical methods we were to use and it was in accordance to those techniques. This resulted in different response formats (Philip 1999: 53). We used both closed and open-ended questions. We also decided on a desirable response format, since they gave us an upper hand during the process of statistical analyses. This worked well in correlation analyses in the SPSS application. We used a Likert-type scale which ranged from strongly disagrees to strongly agree, a range of 1 to 6. This scale gave us a broad range of possible scores and hence fastening statistical analyses. The questionnaires were clear, concise and precise and simple for any person to understand. Discussion and further analysis of data collected Caffeine, its use and addiction to it are things that can be of concern in this world. That is why an initiative was created for the controlled study of this substance, by scrutinizing the effect of caffeine (Independent Variable) on the number of hours which participants sleep (Dependent Variable). Thus, two conditions were created in this experiment namely, caffeine that was administered to participants and a second situation where no caffeine was administered to the chosen individuals. It can be noted also that each and every participant participated in both conditions of this experiment. Each and every condition of this experiment was separated by a week’s period. Hence, we will use the paired samples T-test. The data is below. One can observe participants in each condition and the average number of approximate hours they sleep each night.   Condition one: Caffeine administered       Condition two: No caffeine administered Participant 1 = 6 hours Participant 2 = 5 hours Participant 3 = 4 hours Participant 4 = 7 hours Participant 5 = 5 hours Participant 1 = 9 hours Participant 2 = 10 hours Participant 3 = 8 hours Participant 4 = 9 hours Participant 5 = 11 hours The act of merely observing the data, one can observe that there is a difference in the amount of sleep in the two conditions. One can thus observe that amount of sleep in the no caffeine conditions looks to be more than the quantity of sleep in the no caffeine criteria. Persons generally tend to acquire more sleep when consumption of caffeine is zero. The question can be now posed as to why the T-test needs to be conducted. The sole reason is that we are not merely physically figuring out if there is a difference in the quantity of sleep between both groups of participants, but we want to establish if there is a difference that is significant in statistical terms. This means that we must establish a real difference that can only be defined by statistics. This is why the paired samples T-test are capable of deciphering true results of such an experiment. Just like the independent samples T-test, one will utilize the first two columns of SPSS data file to make an entry of the data for the paired samples T-test. Nonetheless, one will be utilizing these two columns in a different manner. Both columns will have data points gathered in the experiment done. References Philip, M., 1999, Research methods on effetcs of caffeine. London: Oxford Publishers. Print. Read More