Furthermore, hypotheses must be testable by means of using if statements to make a point. The if statement in fact has a very good effect on manipulating one variable has on another. Hypotheses should also have a prediction, be testable, and have a certain falseness to it in order for it to be accepted. With that being said as well, it must also take into account current knowledge about the topic and the different techniques used to derive at a solution to the problem. Hypotheses actually use statistical and analytical data to ensure that it is verifiable, and this allows for the falsification or verification, in which I mentioned earlier.
However, some results may be invalidated by the participants knowing either the true aim of the study or the fact that they are being studied at all. If the participant was to know the true nature of the study, they may adapt their behaviour in order to fit in (socially desirable) or they may act in a way that they think the researcher is expecting (demand characteristics). For example, in Milgram's electric shock experiment, it is highly likely that more participants would have delivered the higher shocks to the 'learner' if they had known the reality of the entire study. This makes the participants actions and behaviour unnatural and could invalidate the data completely. When considering this issue, sociologists should also consider that participants should also be offered the right to refuse.
CONFOUND: A confound means that there is an alternative explanation beyond the experimental variables for any observed differences in the dependent variable EXTRANEOUS VARIABLES: Variables that naturally exist in the environment that may have some systematic effect on the dependent variable DEMAND CHARACTERISTIC: Experimental design element or procedure that unintentionally provides subjects with hints about the research hypothesis DEMAND EFFECT: Occurs when demand characteristics actually affect the dependent variables HAWTHORNE EFFECT: People will perform differently from normal when they know they are experimental subjects PLACEBO: A false experimental condition aimed at creating the impression of an effect PLACEBO EFFECT: The effect in a dependent variable associated with the psychological impact that goes along with knowledge of some treatment being administered CONSTANCY OF CODITIONS: Means that subjects in all experimental groups are exposed to identical conditions except for the differing experimental treatments COUNTERBALANCING: Attempts to eliminate the confounding effects of order of presentation by requiring that one-fourth of the subjects be exposed to treatment A first, one-fourth to treatment B first, one-fourth to treatment C first, and finally one-fourth to treatment D
If the study is qualitative, personal bias can skew the data. Lab study subjects should be debriefed for the reason for the study after participation has ended. The researcher should take responsibility for the safety of the subjects. They should not be subjected to physical or mental abuse. The data reported must not be misrepresented or distorted.
My impression of the IAT is that it may be accurate, but it really depends on the person taking it. These test are not accurate just used for research but I still feel as though it’s a better way to administer the test. The test made me think about the way they ordered to images and words and kept rearranging them making you use both your dominant and non-dominant hand to
Bias in research- refers to beliefs that interfere with objectivity Placebo effect- a fake treatment, an inactive substance like sugar, distilled water, or saline solution can sometimes improve a patient’s condition simply because the person has the expectation that it will help them. Research Methods (*Study Chart, p.19) Case study-an in depth analysis of one person
If analysis was run before completing data collection, the researcher would not be able to accurately interpret the results. The researcher may not collect the correct data. This could lead to making assumptions about the research at hand. It may also result in flawed findings. Therefore, making the conclusion of the research incorrect because the researcher is going to base his/her findings on the information gathered.
You would have to rely on the patient giving you the information for it not is socially desirable or have demand characteristics. On the other hand, it is better than individual differences as people may have the same thought patterns and processes. You can only obtain this information by self reports, which would probably give both of those issues; social desirability and demand characteristics. These would affect your results and therefore they would not be reliable or valid. If you were using the cognitive approach you would only get qualitative data which could be a problem as not everyone interprets the same answer in the same way.
When conducted honestly and thoroughly, the scientific method can and has provided valuable information about the world and the world’s people (Jackson, 2009). Though some people rely on other methods for gaining knowledge, scientists only accept knowledge gained through science to arrive at plausible truths (Jackson, 2009). Due in part to human error and the tendency of human nature to succumb to temptations to bias research, the results of the scientific method should be viewed with skepticism (Garzon, n.d.). The scientific method of seeking knowledge and finding truth must stay within the limits of scientific ability and allow for human fragility in order to be effective (Slick, 2012). References Garzon, F. (n.d.).
Bias occurs when there is a systematic error within the specific research and their findings. Bias can come from several sources, and it can also be classified into two categories: non-sampling error and sampling error. The non-sampling error includes non-response bias, sample selection bias, and systematic measurement error. Sample selection bias can be encountered within real property studies, which are often relied on observational samples like the occurrence of a comparable sale that cannot be assumed to have been a random event. Sampling error stems from the fact that a random sample can differ from the underlying population simply by