Psychology - Experiments And Correlation

A negative correlation refers to a relationship between two variables where, as one variable increases, the other variable decreases. In other words, the two variables move in opposite directions. This means that when one variable goes up, the other tends to go down, and vice versa. This type of correlation is commonly seen in situations where an increase in one factor leads to a decrease in another, such as the relationship between the price of a product and the demand for it.

A weakness of an opportunity sample is that it is unlikely to be representative of the target population. This means that the individuals who are included in the sample may not accurately reflect the characteristics and diversity of the entire population being studied. This can lead to biased results and limit the generalizability of the findings to the larger population.

A matched pairs design refers to a research design where participants only experience one condition of the independent variable but are carefully matched into groups based on their characteristics. This means that each participant is paired with another participant who has similar characteristics, such as age, gender, or IQ, and one participant from each pair is assigned to each condition. This design helps to control for individual differences and increases the internal validity of the study by reducing the potential confounding effects of participant characteristics.

The definition of a null hypothesis is a statement that assumes there is no significant difference or relationship between variables being tested. It is used in hypothesis testing to determine if there is enough evidence to reject the null hypothesis in favor of an alternative hypothesis. The null hypothesis represents the default position that there is no effect or relationship, and any observed difference or relationship is due to chance or random variation.

Demand characteristics refers to the cues or clues in a research study that may lead participants to guess the researcher's hypothesis or expectations, and subsequently alter their behavior accordingly. While demand characteristics can affect the validity of a study, they are not considered an ethical issue. Ethical issues involve principles of fairness, respect, and protection of participants' rights, which are not directly related to demand characteristics.

The researcher will produce quantitative data because they are interested in measuring the time it takes for the sample to complete the task. Quantitative data involves numerical measurements and can be analyzed using statistical methods to draw conclusions and make predictions. In this case, the researcher will likely collect data such as the time in seconds or minutes it takes for each sample to complete the task, allowing for quantitative analysis.

The opinions people expressed about the task they had to do is an example of qualitative data because it involves subjective information that cannot be measured or quantified. Qualitative data focuses on the quality or characteristics of something rather than the quantity or numerical value. In this case, the opinions of individuals provide insights into their thoughts, feelings, and perceptions about the task, which cannot be represented by numbers or statistics.

A disadvantage of a repeated measures experiment design is that it may be susceptible to order effects, which can reduce the validity of the results. Order effects refer to the potential influence that the order in which participants experience different conditions or treatments can have on their responses. For example, participants may become fatigued or bored as the experiment progresses, leading to changes in their behavior or responses. This can introduce bias and make it difficult to determine the true effect of the independent variable being studied.

The correct answer is the number of points plotted. In a scatter graph, the sample size can be determined by counting the number of data points that are plotted on the graph. Each point represents an individual data observation, and the total count of these points gives us the sample size. This is important for statistical analysis as it helps in determining the representativeness and reliability of the data.

An advantage of an Independent measures experiment design is that it eliminates the issue of practice effects. In this design, each participant is only exposed to one condition or treatment, which means they do not have the opportunity to improve their performance through practice or familiarity with the task. This helps to ensure that any observed differences between the groups are truly due to the independent variable being studied, rather than any learning or practice effects.

A correlation coefficient measures the strength and direction of the relationship between two variables. A value of -0.8 indicates a strong negative correlation, meaning that as one variable increases, the other variable decreases. This means that there is a strong inverse relationship between the two variables, where one tends to move in the opposite direction of the other.