Types of Science
Factual evidence that was peer reviewed and been critique. This shows accurate measurements based on the data or experiments that they have collected.
Science
As a way to gain more knowledge researchers manipulate these variables. These are conditions in psychology that are used in their experiments also using dependent variables to show results of experiments.
Independent variable
A very large group that is being tested on. It is almost impossible to survey everyone in the group, so in order to learn more about the group, researchers typically create samples.
Population
A smaller portion of the population, with the intention of using the results as a way to make generalizations about that population. If you want accurate results, you have to limit bias and represent all subgroups within the population.
Sample
Exam scores serve as the dependent variable in an experiment to determine how different study strategies impact exam scores. This is because they are reliant on the manipulation of the study technique (the independent variable), which the researcher modifies in order to detect its influence.
Dependent variable
A sample where everyone in the population has an equal chance of getting selected for the sample. A common option of sampling that reduces the bias that comes from the sampler, but also has the chance of not completely representing the whole population.
Simple Random Sample
NOT REAL SCIENCE because it is only based on beliefs and claims that are first-glance but are not. It is not peer-reviewed where it has been looked at other people to look over for feedback. For example, there was a claim that vaccines cause autism but there was no factual evidence of it happening to other people. In comparison to Science, science is peer reviewed, it's open to new criticism and takes accurate measurements. Science doesn’t make a claim based on belief but on something that has been experimentally proven from many other experiments and peer reviewed.
Pseudoscience
If researchers are looking at the association between exercise (independent variable) and weight reduction (dependent variable), nutrition might be a confounding factor because it also influences weight loss. Without controlling for nutrition, researchers cannot determine if weight changes are attributable to exercise alone, thereby misrepresenting the findings.
Confounding variable
Results that are collected from taking data by using predetermined sets of questions to create what we are looking for and collecting. This can help show us a visual of what went well and what didn’t go well. The advantages are the effectiveness of the experiment, large amounts of data quickly and a lot more cheaper than experiments. The disadvantages are the misunderstanding of the questions, the limitations of insights, and dishonesty, population sample.
Surveys
If researchers are investigating the influence of a new educational curriculum, they may compare test results of children from two separate schools, one using the new curriculum and the other not. Because there is no randomization in quasi-experimental research, they are more susceptible to confounding variables than fully experimental designs.
Quasi-experimental
The significance of association between two different variables. The relationship between two variables is labeled with a coefficient, from -1 to 1, and the further the number is from 0, the more associated the variables are (whether positive or negative).
Correlation
Pollsters want to sample a large University to see whether students at that University are leaning towards voting for Kamala or Trump. They split the University population of students by age groups and will randomly sample from each group. The amount of students selected per age group remains constant.
Stratified Random Sample
Employ random assignment to control groups to demonstrate a clear cause-and-effect link. For example, evaluating the efficacy of a new medicine includes randomly assigning volunteers to receive either the treatment or the control group, ensuring that changes in results may be ascribed to the drug rather than environmental effects.
Experimental studies
It’s how two (or more) variables affect each other. An event may only occur because of one or several factors. It’s the explanation of questions researchers may have. To try and root out this explanation, they must observe a relationship between an independent and dependent variable, with the IV occurring before the DV. They must also acknowledge and eliminate any other reasons or causes.
Causation